Cross-Platform Comparison of Untargeted and Targeted Lipidomics Approaches on Aging Mouse Plasma

Comparative lipid profiling reveals the differential response of distinct lipid subclasses in blast and blunt-induced mild traumatic brain injury

Head trauma from blast exposure is a growing health concern, particularly among active military personnel, and is considered the signature injury of the Gulf War. However, it remains elusive whether fundamental differences exist between blast-related Traumatic Brain Injuries (TBI) and TBI due to other mechanisms. Considering the importance of lipid metabolism associated with neuronal membrane integrity and its compromise during TBI, we sought to find changes in lipidomic profiling during blast or blunt (Stereotaxically Controlled Contusison-SCC)-mediated TBI. In the current study, we have developed the mild TBI (mTBI) model of blast (130 ± 10 kPa) and SCC (1.5 mm dorsal-ventral) on C57BL/6 mice, followed by the serum collection on days 1 and 7. Lipidomics was performed via ultra-high performance liquid chromatography (UHPLC) quadrupole time-of-flight mass spectrometry (qTOF-MS). Additionally, neurobehavioral outcomes were estimated using a revised neurobehavioral severity score for mice (mNSS-R) and an open field test (OFT). The study found that blast-exposed group exhibited more lipid dysregulation, as evidenced by a higher number of significant lipids and associated pathways at both time points. However, the comparative investigation further reveals eight significantly common lipids that can characterize the mTBI regardless of the manner of induction (blast or blunt). Besides, modulated neurobehavioral, locomotor and anxiety functions were also observed post-mTBI. The study illustrates the distinct systemic lipid metabolism intended to preserve the brain's lipid homeostasis post-mTBI. This approach may provide novel insights into lipid metabolism and identification of individual lipid species that aids in understanding the pathophysiology of mTBI.

Applications of Metabolomics and Lipidomics in the Neonatal Intensive Care Unit

The metabolome and lipidome comprise the thousands of molecular compounds in an organism. Molecular compounds consist of the upstream metabolic components of intracellular reactions or the byproducts of cellular pathways. Molecular and biochemical perturbations are associated with disorders in newborns and infants. The diagnosis of inborn errors of metabolism has relied on targeted metabolomics for several decades. Newer approaches offer the potential to identify novel biomarkers for common diseases of the newborn and infant. They may also elucidate novel predictive or diagnostic measures for a variety of health trajectories. Here, we review the relevance of the metabolome and lipidome for common disorders and highlight challenges and opportunities for future investigations.

NAFPD exacerbation by hyperlipidemia combined with hyperuricemia: a pilot rat experiment in lipidomics

Background

Hyperuricemia and non-alcoholic fatty pancreas disease (NAFPD) are prevalent metabolic diseases, but the relationship between them remains underexplored.

Methods

Eighteen Sprague-Dawley rats were randomly assigned to three groups: normal (CON), high-fat (PO), and high-fat high-uric acid (PH). After 12 weeks, serum uric acid (SUA) and triacylglycerol levels were measured. Pathological changes in the pancreas were assessed using hematoxylin-eosin (HE) staining. Serum samples were analyzed using lipidomics technology, and multivariate statistical analysis was employed to identify differences in lipid metabolism.

Results

SUA levels in the PO group were not significantly different from those in the CON group (p > 0.05). However, from the 4th week onward, SUA levels in the PH group were significantly higher than those in both the PO and CON groups (p < 0.05). HE staining revealed that most rats in the CON group exhibited normal pancreatic islet and acinar cell morphology. The pathological NAFPD score in the PH group was higher than that in the PO group. Lipidomics analysis identified 34 potential serum biomarkers in the CON and PO groups, 38 in the CON and PH groups, and 32 in the PH and PO groups. These metabolites primarily included sphingolipids, cholesterol esters, fatty acids, triacylglycerols, phosphatidylcholines, lysophosphatidylcholine, phosphatidylethanolamine, and lysophosphatidylethanolamine.

Conclusion

Hyperlipidemia combined with hyperuricemia might exacerbates NAFPD. Glycerophospholipids may serve as key biomarkers in this process, potentially linked to a chronic inflammatory response mediated by glycerophospholipids.

Interlaboratory comparison of standardised metabolomics and lipidomics analyses in human and rodent blood using the MxP® Quant 500 kit

Metabolomics and lipidomics are pivotal in understanding phenotypic variations beyond genomics. However, quantification and comparability of mass spectrometry (MS)-derived data are challenging. Standardised assays can enhance data comparability, enabling applications in multi-center epidemiological and clinical studies. Here we evaluated the performance and reproducibility of the MxP® Quant 500 kit across 14 laboratories. The kit allows quantification of 634 different metabolites from 26 compound classes using triple quadrupole MS. Each laboratory analysed twelve samples, including human plasma and serum, lipaemic plasma, NIST SRM 1950, and mouse and rat plasma, in triplicates. 505 out of the 634 metabolites were measurable above the limit of detection in all laboratories, while eight metabolites were undetectable in our study. Out of the 505 metabolites, 412 were observed in both human and rodent samples. Overall, the kit exhibited high reproducibility with a median coefficient of variation (CV) of 14.3 %. CVs in NIST SRM 1950 reference plasma were below 25 % and 10 % for 494 and 138 metabolites, respectively. To facilitate further inspection of reproducibility for any compound, we provide detailed results from the in-depth evaluation of reproducibility across concentration ranges using Deming regression. Interlaboratory reproducibility was similar across sample types, with some species-, matrix-, and phenotype-specific differences due to variations in concentration ranges. Comparisons with previous studies on the performance of MS-based kits (including the AbsoluteIDQ p180 and the Lipidyzer) revealed good concordance of reproducibility results and measured absolute concentrations in NIST SRM 1950 for most metabolites, making the MxP® Quant 500 kit a relevant tool to apply metabolomics and lipidomics in multi-center studies.

Multiomic analysis of familial adenomatous polyposis reveals molecular pathways associated with early tumorigenesis

Familial adenomatous polyposis (FAP) is a genetic disease causing hundreds of premalignant polyps in affected persons and is an ideal model to study transitions of early precancer states to colorectal cancer (CRC). We performed deep multiomic profiling of 93 samples, including normal mucosa, benign polyps and dysplastic polyps, from six persons with FAP. Transcriptomic, proteomic, metabolomic and lipidomic analyses revealed a dynamic choreography of thousands of molecular and cellular events that occur during precancerous transitions toward cancer formation. These involve processes such as cell proliferation, immune response, metabolic alterations (including amino acids and lipids), hormones and extracellular matrix proteins. Interestingly, activation of the arachidonic acid pathway was found to occur early in hyperplasia; this pathway is targeted by aspirin and other nonsteroidal anti-inflammatory drugs, a preventative treatment under investigation in persons with FAP. Overall, our results reveal key genomic, cellular and molecular events during the earliest steps in CRC formation and potential mechanisms of pharmaceutical prophylaxis.

The effects of APOE4 and familial Alzheimer's disease mutations on free fatty acid profiles in mouse brain are age- and sex-dependent

APOE4 encoding apolipoprotein (Apo)E4 is the strongest genetic risk factor for Alzheimer's disease (AD). ApoE is key in intercellular lipid trafficking. Fatty acids are essential for brain integrity and cognitive performance and are implicated in neurodegeneration. We determined the sex- and age-dependent effect of AD and APOE4 on brain free fatty acid (FFA) profiles. FFA profiles were determined by LC-MS/MS in hippocampus, cortex, and cerebellum of female and male, young (≤3 months) and older (>5 months), transgenic APOE3 and APOE4 mice with and without five familial AD (FAD) mutations (16 groups; n = 7-10 each). In the different brain regions, females had higher levels than males of either saturated or polyunsaturated FFAs or both. In the hippocampus of young males, but not of older males, APOE4 and FAD each induced 1.3-fold higher levels of almost all FFAs. In young and older females, FAD and to a less extent APOE4-induced shifts among saturated, monounsaturated, and polyunsaturated FFAs without affecting total FFA levels. In cortex and cerebellum, APOE4 and FAD had only minor effects on individual FFAs. The effects of APOE4 and FAD on FFA levels and FFA profiles in the three brain regions were strongly dependent of sex and age, particularly in the hippocampus. Here, most FFAs that are affected by FAD are similarly affected by APOE4. Since APOE4 and FAD affected hippocampal FFA profiles already at young age, these APOE4-induced alterations may modulate the pathogenesis of AD.

Mitochondria targeted drug delivery system overcoming drug resistance in intrahepatic cholangiocarcinoma by reprogramming lipid metabolism

The challenge of drug resistance in intrahepatic cholangiocarcinoma (ICC) is intricately linked with lipid metabolism reprogramming. The hepatic lipase (HL) and the membrane receptor CD36 are overexpressed in BGJ398-resistant ICC cells, while they are essential for lipid uptake, further enhancing lipid utilization in ICC. Herein, a metal-organic framework-based drug delivery system (OB@D-pMOF/CaP-AC, DDS), has been developed. The specifically designed DDS exhibits a successive targeting property, enabling it to precisely target ICC cells and their mitochondria. By specifically targeting the mitochondria, DDS produces reactive oxygen species (ROS) through its sonodynamic therapy effect, achieving a more potent reduction in ATP levels compared to non-targeted approaches, through the impairment of mitochondrial function. Additionally, the DDS strategically minimizes lipid uptake through the incorporation of the anti-HL drug, Orlistat, and anti-CD36 monoclonal antibody, reducing lipid-derived energy production. This dual-action strategy on both mitochondria and lipids can hinder energy utilization to restore drug sensitivity to BGJ398 in ICC. Moreover, an orthotopic mice model of drug-resistant ICC was developed, which serves as an exacting platform for evaluating the multifunction of designed DDS. Upon in vivo experiments with this model, the DDS demonstrated exceptional capabilities in suppressing tumor growth, reprogramming lipid metabolism and improving immune response, thereby overcoming drug resistance. These findings underscore the mitochondria-targeted DDS as a promising and innovative solution in ICC drug resistance.

Oleic acid enhances proliferation and calcium mobilization of CD3/CD28 activated CD4+ T cells through incorporation into membrane lipids

Unsaturated fatty acids (UFA) are crucial for T-cell effector functions, as they can affect the growth, differentiation, survival, and function of T cells. Nonetheless, the mechanisms by which UFA affects T-cell behavior are ill-defined. Therefore, we analyzed the processing of oleic acid, a prominent UFA abundantly present in blood, adipocytes, and the fat pads surrounding lymph nodes, in CD4+ T cells. We found that exogenous oleic acid increases proliferation and enhances the calcium flux response upon CD3/CD28 activation. By using a variety of techniques, we found that the incorporation of oleic acid into membrane lipids, rather than regulation of cellular metabolism or TCR expression, is essential for its effects on CD4+ T cells. These results provide novel insights into the mechanism through which exogenous oleic acid enhances CD4+ T-cell function.

Comparing the Extraction Performance in Mouse Plasma of Different Biphasic Methods for Polar and Nonpolar Compounds

Many metabolomic studies are interested in both polar and nonpolar analyses. However, the available sample volume often precludes multiple separate extractions. Therefore, there are major advantages in performing a biphasic extraction and retaining both phases for subsequent separate analyses. To be successful, such approaches require the method to be robust and repeatable for both phases. Hence, we determined the performance of three extraction protocols, plus two variant versions, using 25 μL of commercially available mouse plasma. The preferred option for nonpolar lipids was a modified diluted version of a method employing methyl tert-butyl ether (MTBE) suggested by Matyash and colleagues due to its high repeatability for nonpolar compounds. For polar compounds, the Bligh-Dyer method performs best for sensitivity but with consequentially poorer lipid performance. Overall, the scaled-down version of the MTBE method gave the best overall performance, with high sensitivity for both polar and nonpolar compounds and good repeatability for polar compounds in particular.

Evolution of diapause in the African turquoise killifish by remodeling the ancient gene regulatory landscape

Suspended animation states allow organisms to survive extreme environments. The African turquoise killifish has evolved diapause as a form of suspended development to survive a complete drought. However, the mechanisms underlying the evolution of extreme survival states are unknown. To understand diapause evolution, we performed integrative multi-omics (gene expression, chromatin accessibility, and lipidomics) in the embryos of multiple killifish species. We find that diapause evolved by a recent remodeling of regulatory elements at very ancient gene duplicates (paralogs) present in all vertebrates. CRISPR-Cas9-based perturbations identify the transcription factors REST/NRSF and FOXOs as critical for the diapause gene expression program, including genes involved in lipid metabolism. Indeed, diapause shows a distinct lipid profile, with an increase in triglycerides with very-long-chain fatty acids. Our work suggests a mechanism for the evolution of complex adaptations and offers strategies to promote long-term survival by activating suspended animation programs in other species.

Single-Cell Untargeted Lipidomics Using Liquid Chromatography and Data-Dependent Acquisition after Live Cell Selection

We report the development and validation of an untargeted single-cell lipidomics method based on microflow chromatography coupled to a data-dependent mass spectrometry method for fragmentation-based identification of lipids. Given the absence of single-cell lipid standards, we show how the methodology should be optimized and validated using a dilute cell extract. The methodology is applied to dilute pancreatic cancer and macrophage cell extracts and standards to demonstrate the sensitivity requirements for confident assignment of lipids and classification of the cell type at the single-cell level. The method is then coupled to a system that can provide automated sampling of live, single cells into capillaries under microscope observation. This workflow retains the spatial information and morphology of cells during sampling and highlights the heterogeneity in lipid profiles observed at the single-cell level. The workflow is applied to show changes in single-cell lipid profiles as a response to oxidative stress, coinciding with expanded lipid droplets. This demonstrates that the workflow is sufficiently sensitive to observing changes in lipid profiles in response to a biological stimulus. Understanding how lipids vary in single cells will inform future research into a multitude of biological processes as lipids play important roles in structural, biophysical, energy storage, and signaling functions.

Integrative multi-omics profiling in human decedents receiving pig heart xenografts

In a previous study, heart xenografts from 10-gene-edited pigs transplanted into two human decedents did not show evidence of acute-onset cellular- or antibody-mediated rejection. Here, to better understand the detailed molecular landscape following xenotransplantation, we carried out bulk and single-cell transcriptomics, lipidomics, proteomics and metabolomics on blood samples obtained from the transplanted decedents every 6 h, as well as histological and transcriptomic tissue profiling. We observed substantial early immune responses in peripheral blood mononuclear cells and xenograft tissue obtained from decedent 1 (male), associated with downstream T cell and natural killer cell activity. Longitudinal analyses indicated the presence of ischemia reperfusion injury, exacerbated by inadequate immunosuppression of T cells, consistent with previous findings of perioperative cardiac xenograft dysfunction in pig-to-nonhuman primate studies. Moreover, at 42 h after transplantation, substantial alterations in cellular metabolism and liver-damage pathways occurred, correlating with profound organ-wide physiological dysfunction. By contrast, relatively minor changes in RNA, protein, lipid and metabolism profiles were observed in decedent 2 (female) as compared to decedent 1. Overall, these multi-omics analyses delineate distinct responses to cardiac xenotransplantation in the two human decedents and reveal new insights into early molecular and immune responses after xenotransplantation. These findings may aid in the development of targeted therapeutic approaches to limit ischemia reperfusion injury-related phenotypes and improve outcomes.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Quantifying yeast lipidomics by high-performance thin-layer chromatography (HPTLC) and comparison to mass spectrometry-based shotgun lipidomics

Lipidomic analysis in diverse biological settings has become a frequent tool to increase our understanding of the processes of life. Cellular lipids play important roles not only as being the main components of cellular membranes, but also in the regulation of cell homeostasis as lipid signaling molecules. Yeast has been harnessed for biomedical research based on its good conservation of genetics and fundamental cell organisation principles and molecular pathways. Further application in so-called humanised yeast models have been developed which take advantage of yeast as providing the basics of a living cell with full control over heterologous expression. Here we present evidence that high-performance thin-layer chromatography (HPTLC) represents an effective alternative to replace cost intensive mass spectrometry-based lipidomic analyses. We provide statistical comparison of identical samples by both methods, which support the use of HPTLC for quantitative analysis of the main yeast lipid classes.

Integrative Analysis of Cytokine and Lipidomics Datasets Following Mild Traumatic Brain Injury in Rats

Traumatic brain injury (TBI) is a significant source of disability in the United States and around the world and may lead to long-lasting cognitive deficits and a decreased quality of life for patients across injury severities. Following the primary injury phase, TBI is characterized by complex secondary cascades that involve altered homeostasis and metabolism, faulty signaling, neuroinflammation, and lipid dysfunction. The objectives of the present study were to (1) assess potential correlations between lipidome and cytokine changes after closed-head mild TBI (mTBI), and (2) examine the reproducibility of our acute lipidomic profiles following TBI. Cortices from 54 Sprague Dawley male and female rats were analyzed by ultra-high-performance liquid chromatography mass spectrometry (LC-MS) in both positive and negative ionization modes and multiplex cytokine analysis after single (smTBI) or repetitive (rmTBI) closed-head impacts, or sham conditions. Tissue age was a variable, given that two cohorts (n = 26 and n = 28) were initially run a year-and-a-half apart, creating inter-batch variations. We annotated the lipidome datasets using an in-house data dictionary based on exact masses of precursor and fragment ions and removed features with statistically significant differences between sham control batches. Our results indicate that lipids with high-fold change between injury groups moderately correlate with the cytokines eotaxin, IP-10, and TNF-α. Additionally, we show a significant decrease in the pro-inflammatory markers IL-1β and IP-10, TNF-α, and RANTES in the rmTBI samples relative to the sham control. We discuss the major challenges in correlating high dimensional lipidomic data with functional cytokine profiles and the implications for understanding the biological significance of two related but disparate analysis modes in the study of TBI, an inherently heterogeneous neurological disorder.

Combined untargeted and targeted lipidomics approaches reveal potential biomarkers in type 2 diabetes mellitus cynomolgus monkeys

BACKGROUND

The significantly increasing incidence of type 2 diabetes mellitus (T2DM) over the last few decades triggers the demands of T2DM animal models to explore the pathogenesis, prevention, and therapy of the disease. The altered lipid metabolism may play an important role in the pathogenesis and progression of T2DM. However, the characterization of molecular lipid species in fasting serum related to T2DM cynomolgus monkeys is still underrecognized.

METHODS

Untargeted and targeted LC-mass spectrometry (MS)/MS-based lipidomics approaches were applied to characterize and compare the fasting serum lipidomic profiles of T2DM cynomolgus monkeys and the healthy controls.

RESULTS

Multivariate analysis revealed that 196 and 64 lipid molecules differentially expressed in serum samples using untargeted and targeted lipidomics as the comparison between the disease group and healthy group, respectively. Furthermore, the comparative analysis of differential serum lipid metabolites obtained by untargeted and targeted lipidomics approaches, four common serum lipid species (phosphatidylcholine [18:0_22:4], lysophosphatidylcholine [14:0], phosphatidylethanolamine [PE] [16:1_18:2], and PE [18:0_22:4]) were identified as potential biomarkers and all of which were found to be downregulated. By analyzing the metabolic pathway, glycerophospholipid metabolism was associated with the pathogenesis of T2DM cynomolgus monkeys.

CONCLUSION

The study found that four downregulated serum lipid species could serve as novel potential biomarkers of T2DM cynomolgus monkeys. Glycerophospholipid metabolism was filtered out as the potential therapeutic target pathway of T2DM progression. Our results showed that the identified biomarkers may offer a novel tool for tracking disease progression and response to therapeutic interventions.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Study Highlights

The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.

Multi-omics microsampling for the profiling of lifestyle-associated changes in health

Current healthcare practices are reactive and use limited physiological and clinical information, often collected months or years apart. Moreover, the discovery and profiling of blood biomarkers in clinical and research settings are constrained by geographical barriers, the cost and inconvenience of in-clinic venepuncture, low sampling frequency and the low depth of molecular measurements. Here we describe a strategy for the frequent capture and analysis of thousands of metabolites, lipids, cytokines and proteins in 10 μl of blood alongside physiological information from wearable sensors. We show the advantages of such frequent and dense multi-omics microsampling in two applications: the assessment of the reactions to a complex mixture of dietary interventions, to discover individualized inflammatory and metabolic responses; and deep individualized profiling, to reveal large-scale molecular fluctuations as well as thousands of molecular relationships associated with intra-day physiological variations (in heart rate, for example) and with the levels of clinical biomarkers (specifically, glucose and cortisol) and of physical activity. Combining wearables and multi-omics microsampling for frequent and scalable omics may facilitate dynamic health profiling and biomarker discovery.

Analysis of tissue lipidomics and computed tomography pulmonary fat attenuation volume (CTPFAV ) in idiopathic pulmonary fibrosis

BACKGROUND AND OBJECTIVE

There is increasing interest in the role of lipids in processes that modulate lung fibrosis with evidence of lipid deposition in idiopathic pulmonary fibrosis (IPF) histological specimens. The aim of this study was to identify measurable markers of pulmonary lipid that may have utility as IPF biomarkers.

STUDY DESIGN AND METHODS

IPF and control lung biopsy specimens were analysed using a unbiased lipidomic approach. Pulmonary fat attenuation volume (PFAV) was assessed on chest CT images (CTPFAV ) with 3D semi-automated lung density software. Aerated lung was semi-automatically segmented and CTPFAV calculated using a Hounsfield-unit (-40 to -200HU) threshold range expressed as a percentage of total lung volume. CTPFAV was compared to pulmonary function, serum lipids and qualitative CT fibrosis scores.

RESULTS

There was a significant increase in total lipid content on histological analysis of IPF lung tissue (23.16 nmol/mg) compared to controls (18.66 mol/mg, p = 0.0317). The median CTPFAV in IPF was higher than controls (1.34% vs. 0.72%, p < 0.001) and CTPFAV correlated significantly with DLCO% predicted (R2  = 0.356, p < 0.0001) and FVC% predicted (R2  = 0.407, p < 0.0001) in patients with IPF. CTPFAV correlated with CT features of fibrosis; higher CTPFAV was associated with >10% reticulation (1.6% vs. 0.94%, p = 0.0017) and >10% honeycombing (1.87% vs. 1.12%, p = 0.0003). CTPFAV showed no correlation with serum lipids.

CONCLUSION

CTPFAV is an easily quantifiable non-invasive measure of pulmonary lipids. In this pilot study, CTPFAV correlates with pulmonary function and radiological features of IPF and could function as a potential biomarker for IPF disease severity assessment.

Dynamic lipidome alterations associated with human health, disease and ageing

Lipids can be of endogenous or exogenous origin and affect diverse biological functions, including cell membrane maintenance, energy management and cellular signalling. Here, we report >800 lipid species, many of which are associated with health-to-disease transitions in diabetes, ageing and inflammation, as well as cytokine-lipidome networks. We performed comprehensive longitudinal lipidomic profiling and analysed >1,500 plasma samples from 112 participants followed for up to 9 years (average 3.2 years) to define the distinct physiological roles of complex lipid subclasses, including large and small triacylglycerols, ester- and ether-linked phosphatidylethanolamines, lysophosphatidylcholines, lysophosphatidylethanolamines, cholesterol esters and ceramides. Our findings reveal dynamic changes in the plasma lipidome during respiratory viral infection, insulin resistance and ageing, suggesting that lipids may have roles in immune homoeostasis and inflammation regulation. Individuals with insulin resistance exhibit disturbed immune homoeostasis, altered associations between lipids and clinical markers, and accelerated changes in specific lipid subclasses during ageing. Our dataset based on longitudinal deep lipidome profiling offers insights into personalized ageing, metabolic health and inflammation, potentially guiding future monitoring and intervention strategies.

Ube4A maintains metabolic homeostasis and facilitates insulin signaling in vivo

OBJECTIVE

Defining the regulators of cell metabolism and signaling is essential to design new therapeutic strategies in obesity and NAFLD/NASH. E3 ubiquitin ligases control diverse cellular functions by ubiquitination-mediated regulation of protein targets, and thus their functional aberration is associated with many diseases. The E3 ligase Ube4A has been implicated in human obesity, inflammation, and cancer. However, its in vivo function is unknown, and no animal models are available to study this novel protein.

METHODS

A whole-body Ube4A knockout (UKO) mouse model was generated, and various metabolic parameters were compared in chow- and high fat diet (HFD)-fed WT and UKO mice, and in their liver, adipose tissue, and serum. Lipidomics and RNA-Seq studies were performed in the liver samples of HFD-fed WT and UKO mice. Proteomic studies were conducted to identify Ube4A's targets in metabolism. Furthermore, a mechanism by which Ube4A regulates metabolism was identified.

RESULTS

Although the body weight and composition of young, chow-fed WT and UKO mice are similar, the knockouts exhibit mild hyperinsulinemia and insulin resistance. HFD feeding substantially augments obesity, hyperinsulinemia, and insulin resistance in both sexes of UKO mice. HFD-fed white and brown adipose tissue depots of UKO mice have increased insulin resistance and inflammation and reduced energy metabolism. Moreover, Ube4A deletion exacerbates hepatic steatosis, inflammation, and liver injury in HFD-fed mice with increased lipid uptake and lipogenesis in hepatocytes. Acute insulin treatment resulted in impaired activation of the insulin effector protein kinase Akt in liver and adipose tissue of chow-fed UKO mice. We identified the Akt activator protein APPL1 as a Ube4A interactor. The K63-linked ubiquitination (K63-Ub) of Akt and APPL1, known to facilitate insulin-induced Akt activation, is impaired in UKO mice. Furthermore, Ube4A K63-ubiquitinates Akt in vitro.

CONCLUSION

Ube4A is a novel regulator of obesity, insulin resistance, adipose tissue dysfunction and NAFLD, and preventing its downregulation may ameliorate these diseases.

Exploring the Impact of Organic Solvent Quality and Unusual Adduct Formation during LC-MS-Based Lipidomic Profiling

Liquid chromatography-mass spectrometry (LC-MS) is the key technique for analyzing complex lipids in biological samples. Various LC-MS modes are used for lipid separation, including different stationary phases, mobile-phase solvents, and modifiers. Quality control in lipidomics analysis is crucial to ensuring the generated data's reliability, reproducibility, and accuracy. While several quality control measures are commonly discussed, the impact of organic solvent quality during LC-MS analysis is often overlooked. Additionally, the annotation of complex lipids remains prone to biases, leading to potential misidentifications and incomplete characterization of lipid species. In this study, we investigate how LC-MS-grade isopropanol from different vendors may influence the quality of the mobile phase used in LC-MS-based untargeted lipidomic profiling of biological samples. Furthermore, we report the occurrence of an unusual, yet highly abundant, ethylamine adduct [M+46.0651]+ that may form for specific lipid subclasses during LC-MS analysis in positive electrospray ionization mode when acetonitrile is part of the mobile phase, potentially leading to lipid misidentification. These findings emphasize the importance of considering solvent quality in LC-MS analysis and highlight challenges in lipid annotation.

Considerations for reproducible omics in aging research

Technical advancements over the past two decades have enabled the measurement of the panoply of molecules of cells and tissues including transcriptomes, epigenomes, metabolomes and proteomes at unprecedented resolution. Unbiased profiling of these molecular landscapes in the context of aging can reveal important details about mechanisms underlying age-related functional decline and age-related diseases. However, the high-throughput nature of these experiments creates unique analytical and design demands for robustness and reproducibility. In addition, 'omic' experiments are generally onerous, making it crucial to effectively design them to eliminate as many spurious sources of variation as possible as well as account for any biological or technical parameter that may influence such measures. In this Perspective, we provide general guidelines on best practices in the design and analysis of omic experiments in aging research from experimental design to data analysis and considerations for long-term reproducibility and validation of such studies.

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.

Bioactive lipid lysophosphatidic acid species are associated with disease progression in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive disease with significant mortality. Prognostic biomarkers to identify rapid progressors are urgently needed to improve patient management. Since the lysophosphatidic acid (LPA) pathway has been implicated in lung fibrosis in preclinical models and identified as a potential therapeutic target, we aimed to investigate if bioactive lipid LPA species could be prognostic biomarkers that predict IPF disease progression. LPAs and lipidomics were measured in baseline placebo plasma of a randomized IPF-controlled trial. The association of lipids with disease progression indices were assessed using statistical models. Compared to healthy, IPF patients had significantly higher levels of five LPAs (LPA16:0, 16:1, 18:1, 18:2, 20:4) and reduced levels of two triglycerides species (TAG48:4-FA12:0, -FA18:2) (false discovery rate < 0.05, fold change > 2). Patients with higher levels of LPAs had greater declines in diffusion capacity of carbon monoxide over 52 weeks (P < 0.01); additionally, LPA20:4-high (≥median) patients had earlier time to exacerbation compared to LPA20:4-low ( Collapse

Key Words

• DLCO
• Lysophosphatidic acid
• exacerbation
• idiopathic pulmonary fibrosis
• mortality

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MESH Headings

• Humans
• Idiopathic Pulmonary Fibrosis/metabolism
• Disease Progression
• Lysophospholipids
• Biomarkers

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Grants Collapse

Affiliation(s)

Margaret Neighbors OMNI Translational Medicine, Genentech Inc., South San Francisco, USA
Qingling Li Department of Microchemistry, Proteomics & Lipidomics, Genentech Inc., South San Francisco, USA
Sha Joe Zhu PD Data Science, F Hoffmann-La Roche, Shanghai, China
Jia Liu PD Data Science, F Hoffmann-La Roche, Shanghai, China
Weng Ruh Wong Department of Microchemistry, Proteomics & Lipidomics, Genentech Inc., South San Francisco, USA
Guiquan Jia Department of Biomarker Discovery OMNI, Genentech Inc., South San Francisco, USA
Wendy Sandoval Department of Microchemistry, Proteomics & Lipidomics, Genentech Inc., South San Francisco, USA
Gaik W Tew I2O Technology and Translational Research, Genentech Inc., South San Francisco, USA.

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Multiomic signals associated with maternal epidemiological factors contributing to preterm birth in low- and middle-income countries

Preterm birth (PTB) is the leading cause of death in children under five, yet comprehensive studies are hindered by its multiple complex etiologies. Epidemiological associations between PTB and maternal characteristics have been previously described. This work used multiomic profiling and multivariate modeling to investigate the biological signatures of these characteristics. Maternal covariates were collected during pregnancy from 13,841 pregnant women across five sites. Plasma samples from 231 participants were analyzed to generate proteomic, metabolomic, and lipidomic datasets. Machine learning models showed robust performance for the prediction of PTB (AUROC = 0.70), time-to-delivery (r = 0.65), maternal age (r = 0.59), gravidity (r = 0.56), and BMI (r = 0.81). Time-to-delivery biological correlates included fetal-associated proteins (e.g., ALPP, AFP, and PGF) and immune proteins (e.g., PD-L1, CCL28, and LIFR). Maternal age negatively correlated with collagen COL9A1, gravidity with endothelial NOS and inflammatory chemokine CXCL13, and BMI with leptin and structural protein FABP4. These results provide an integrated view of epidemiological factors associated with PTB and identify biological signatures of clinical covariates affecting this disease.

Multi-omic screening of invasive GBM cells in engineered biomaterials and patient biopsies reveals targetable transsulfuration pathway alterations

While the poor prognosis of glioblastoma arises from the invasion of a subset of tumor cells, little is known of the metabolic alterations within these cells that fuel invasion. We integrated spatially addressable hydrogel biomaterial platforms, patient site-directed biopsies, and multi-omics analyses to define metabolic drivers of invasive glioblastoma cells. Metabolomics and lipidomics revealed elevations in the redox buffers cystathionine, hexosylceramides, and glucosyl ceramides in the invasive front of both hydrogel-cultured tumors and patient site-directed biopsies, with immunofluorescence indicating elevated reactive oxygen species (ROS) markers in invasive cells. Transcriptomics confirmed upregulation of ROS-producing and response genes at the invasive front in both hydrogel models and patient tumors. Amongst oncologic ROS, hydrogen peroxide specifically promoted glioblastoma invasion in 3D hydrogel spheroid cultures. A CRISPR metabolic gene screen revealed cystathionine gamma lyase (CTH), which converts cystathionine to the non-essential amino acid cysteine in the transsulfuration pathway, to be essential for glioblastoma invasion. Correspondingly, supplementing CTH knockdown cells with exogenous cysteine rescued invasion. Pharmacologic CTH inhibition suppressed glioblastoma invasion, while CTH knockdown slowed glioblastoma invasion in vivo. Our studies highlight the importance of ROS metabolism in invasive glioblastoma cells and support further exploration of the transsulfuration pathway as a mechanistic and therapeutic target.

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.

The unknown lipids project: harmonized methods improve compound identification and data reproducibility in an inter-laboratory untargeted lipidomics study

Untargeted lipidomics allows analysis of a broader range of lipids than targeted methods and permits discovery of unknown compounds. Previous ring trials have evaluated the reproducibility of targeted lipidomics methods, but inter-laboratory comparison of compound identification and unknown feature detection in untargeted lipidomics has not been attempted. To address this gap, five laboratories analyzed a set of mammalian tissue and biofluid reference samples using both their own untargeted lipidomics procedures and a common chromatographic and data analysis method. While both methods yielded informative data, the common method improved chromatographic reproducibility and resulted in detection of more shared features between labs. Spectral search against the LipidBlast in silico library enabled identification of over 2,000 unique lipids. Further examination of LC-MS/MS and ion mobility data, aided by hybrid search and spectral networking analysis, revealed spectral and chromatographic patterns useful for classification of unknown features, a subset of which were highly reproducible between labs. Overall, our method offers enhanced compound identification performance compared to targeted lipidomics, demonstrates the potential of harmonized methods to improve inter-site reproducibility for quantitation and feature alignment, and can serve as a reference to aid future annotation of untargeted lipidomics data.

Compound Identification Strategies in Mass Spectrometry-Based Metabolomics and Pharmacometabolomics

The metabolome is composed of a vast array of molecules, including endogenous metabolites and lipids, diet- and microbiome-derived substances, pharmaceuticals and supplements, and exposome chemicals. Correct identification of compounds from this diversity of classes is essential to derive biologically relevant insights from metabolomics data. In this chapter, we aim to provide a practical overview of compound identification strategies for mass spectrometry-based metabolomics, with a particular eye toward pharmacologically-relevant studies. First, we describe routine compound identification strategies applicable to targeted metabolomics. Next, we discuss both experimental (data acquisition-focused) and computational (software-focused) strategies used to identify unknown compounds in untargeted metabolomics data. We then discuss the importance of, and methods for, assessing and reporting the level of confidence of compound identifications. Throughout the chapter, we discuss how these steps can be implemented using today's technology, but also highlight research underway to further improve accuracy and certainty of compound identification. For readers interested in interpreting metabolomics data already collected, this chapter will supply important context regarding the origin of the metabolite names assigned to features in the data and help them assess the certainty of the identifications. For those planning new data acquisition, the chapter supplies guidance for designing experiments and selecting analysis methods to enable accurate compound identification, and it will point the reader toward best-practice data analysis and reporting strategies to allow sound biological and pharmacological interpretation.

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

Prioritize biologically relevant ions for data-independent acquisition (BRI-DIA) in LC-MS/MS-based lipidomics analysis

INTRODUCTION

Data-dependent acquisition (DDA) is the most commonly used MS/MS scan method for lipidomics analysis on orbitrap-based instrument. However, MS instrument associated software decide the top N precursors for fragmentation, resulting in stochasticity of precursor selection and compromised consistency and reproducibility. We introduce a novel workflow using biologically relevant lipids to construct inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow.

OBJECTIVES

To ensure consistent coverage of biologically relevant lipids in LC-MS/MS-based lipidomics analysis.

METHODS

Biologically relevant ion list was constructed based on LIPID MAPS and lipidome atlas in MS-DIAL 4. Lipids were extracted from mouse tissues and used to assess different MS/MS scan workflow (DDA, BRI-DIA, and hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer.

RESULTS

DDA resulted in more MS/MS events, but the total number of unique lipids identified by three methods (DDA, BRI-DIA, and hybrid MS/MS scan mode) is comparable (580 unique lipids across 44 lipid subclasses in mouse liver). Major cardiolipin molecular species were identified by data generated using BRI-DIA and hybrid methods and allowed calculation of cardiolipin compositions, while identification of the most abundant cardiolipin CL72:8 was missing in data generated using DDA method, leading to wrong calculation of cardiolipin composition.

CONCLUSION

The method of using inclusion list comprised of biologically relevant lipids in DIA MS/MS scan is as efficient as traditional DDA method in profiling lipids, but offers better consistency of lipid identification, compared to DDA method. This study was performed using Orbitrap Exploris 480, and we will further evaluate this workflow on other platforms, and if verified by future work, this biologically relevant ion fragmentation workflow could be routinely used in many studies to improve MS/MS identification capacities.

Advanced Microsamples: Current Applications and Considerations for Mass Spectrometry-Based Metabolic Phenotyping Pipelines

Microsamples are collections usually less than 50 µL, although all devices that we have captured as part of this review do not fit within this definition (as some can perform collections of up to 600 µL); however, they are considered microsamples that can be self-administered. These microsamples have been introduced in pre-clinical, clinical, and research settings to overcome obstacles in sampling via traditional venepuncture. However, venepuncture remains the sampling gold standard for the metabolic phenotyping of blood. This presents several challenges in metabolic phenotyping workflows: accessibility for individuals in rural and remote areas (due to the need for trained personnel), the unamenable nature to frequent sampling protocols in longitudinal research (for its invasive nature), and sample collection difficulty in the young and elderly. Furthermore, venous sample stability may be compromised when the temperate conditions necessary for cold-chain transport are beyond control. Alternatively, research utilising microsamples extends phenotyping possibilities to inborn errors of metabolism, therapeutic drug monitoring, nutrition, as well as sport and anti-doping. Although the application of microsamples in metabolic phenotyping exists, it is still in its infancy, with whole blood being overwhelmingly the primary biofluid collected through the collection method of dried blood spots. Research into the metabolic phenotyping of microsamples is limited; however, with advances in commercially available microsampling devices, common barriers such as volumetric inaccuracies and the ‘haematocrit effect’ in dried blood spot microsampling can be overcome. In this review, we provide an overview of the common uses and workflows for microsampling in metabolic phenotyping research. We discuss the advancements in technologies, highlighting key considerations and remaining knowledge gaps for the employment of microsamples in metabolic phenotyping research. This review supports the translation of research from the ‘bench to the community’.

Adjustable Intragastric Balloon Leads to Significant Improvement in Obesity-Related Lipidome and Fecal Microbiome Profiles: A Proof-of-Concept Study

INTRODUCTION

Intragastric balloons (IGBs) are a safe and effective treatment for obesity. However, limited knowledge exists on the underlying biological changes with IGB placement.

METHODS

This single-institution study was part of an adjustable IGB randomized controlled trial. Subjects with obesity were randomized in a 2 is to 1 ratio to 32 weeks of IGB with diet/exercise counseling (n = 8) vs counseling alone (controls, n = 4). Diet/exercise counseling was continued for 24 weeks post-IGB removal to assess weight maintenance. We used mass spectrometry for nontargeted plasma lipidomics analysis and 16S rRNA sequencing to profile the fecal microbiome.

RESULTS

Subjects with IGBs lost 15.5% of their body weight at 32 weeks vs 2.59% for controls (P < 0.05). Maintenance of a 10.5% weight loss occurred post-IGB explant. IGB placement, followed by weight maintenance, led to a -378.9 μM/L reduction in serum free fatty acids compared with pre-IGB (95% confidence interval: 612.9, -145.0). This reduction was mainly in saturated, mono, and omega-6 fatty acids when compared with pre-IGB. Polyunsaturated phosphatidylcholines also increased after IGB placement (difference of 27 μM/L; 95% confidence interval: 1.1, 52.8). Compared with controls, saturated and omega-6 free fatty acids (linoleic and arachidonic acids) were reduced after IGB placement. The fecal microbiota changed post-IGB placement and weight maintenance vs pre-IGB (P < 0.05). Further analysis showed a possible trend toward reduced Firmicutes and increased Bacteroidetes post-IGB and counseling, a change that was not conclusively different from counseling alone.

DISCUSSION

IGB treatment is associated with an altered fecal microbiome profile and may have a better effect on obesity-related lipidome than counseling alone.

Global, distinctive, and personal changes in molecular and microbial profiles by specific fibers in humans

Dietary fibers act through the microbiome to improve cardiovascular health and prevent metabolic disorders and cancer. To understand the health benefits of dietary fiber supplementation, we investigated two popular purified fibers, arabinoxylan (AX) and long-chain inulin (LCI), and a mixture of five fibers. We present multiomic signatures of metabolomics, lipidomics, proteomics, metagenomics, a cytokine panel, and clinical measurements on healthy and insulin-resistant participants. Each fiber is associated with fiber-dependent biochemical and microbial responses. AX consumption associates with a significant reduction in LDL and an increase in bile acids, contributing to its observed cholesterol reduction. LCI is associated with an increase in Bifidobacterium. However, at the highest LCI dose, there is increased inflammation and elevation in the liver enzyme alanine aminotransferase. This study yields insights into the effects of fiber supplementation and the mechanisms behind fiber-induced cholesterol reduction, and it shows effects of individual, purified fibers on the microbiome.

Identification of novel biomarkers for acute radiation injury using multi-omics approach and nonhuman primate model

PURPOSE

The availability of validated biomarkers to assess radiation exposure and to assist in developing medical countermeasures remains an unmet need.

METHODS AND MATERIALS

We used a cobalt-60 gamma-irradiated nonhuman primate (NHP) model to delineate a multi-omics-based serum probability index of radiation exposure. Both male and female NHPs were irradiated with different doses ranging from 6.0 to 8.5 Gy, with 0.5 Gy increments between doses. We leveraged high-resolution mass spectrometry for analysis of metabolites, lipids, and proteins at 1, 2, and 6 days post-irradiation in NHP serum.

RESULTS

A logistic regression model was implemented to develop a 4-analyte panel to stratify irradiated NHPs from unirradiated with high accuracy that was agnostic for all doses of gamma-rays tested in the study, up to six days after exposure. This panel was comprised of Serpin Family A9, acetylcarnitine, PC (16:0/22:6), and suberylglycine, which showed 2 - 4-fold elevation in serum abundance upon irradiation in NHPs and can potentially be translated as a molecular diagnostic for human use following larger validation studies.

CONCLUSIONS

Taken together, this study, for the first time, demonstrates the utility of a combinatorial molecular characterization approach using an NHP model for developing minimally invasive assays from small volumes of blood that can be effectively used for radiation exposure assessments.

A High Throughput Lipidomics Method Using Scheduled Multiple Reaction Monitoring

Lipid compositions of cells, tissues, and bio-fluids are complex, with varying concentrations and structural diversity making their identification challenging. Newer methods for comprehensive analysis of lipids are thus necessary. Herein, we propose a targeted-mass spectrometry based lipidomics screening method using a combination of variable retention time window and relative dwell time weightage. Using this method, we identified more than 1000 lipid species within 24-min. The limit of detection varied from the femtomolar to the nanomolar range. About 883 lipid species were detected with a coefficient of variance <30%. We used this method to identify plasma lipids altered due to vitamin B12 deficiency and found a total of 18 lipid species to be altered. Some of the lipid species with ω-6 fatty acid chains were found to be significantly increased while ω-3 decreased in vitamin B12 deficient samples. This method enables rapid screening of a large number of lipid species in a single experiment and would substantially advance our understanding of the role of lipids in biological processes.

Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)

INTRODUCTION

The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research.

OBJECTIVES

This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data.

RESULTS

The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities.

CONCLUSIONS

The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.

Testing the effects of processing on donor human Milk: Analytical methods

Holder pasteurization is the current recommended method for donor human milk treatment. This method effectively eliminates most life-threatening contaminants in donor milk, but it also greatly reduces some of its biological properties. Consequently, there is a growing interest for developing novel processing methods that can ensure both microbial inactivation and a higher retention of the functional components of donor milk. Our aim was to offer a comprehensive overview of the analytical techniques available for the evaluation of such methods. To suggest an efficient workflow for the analysis of processed donor milk, a safety analytical panel as well as a nutritional value and functionality analytical panel are discussed, together with the principles, benefits, and drawbacks of the available techniques. Concluding on the suitability of a novel method requires a multifactorial approach which can be achieved by a combination of analytical targets and by using complementary assays to cross-validate the obtained results.

Targeted Lipidomics To Measure Phospholipids and Sphingomyelins in Plasma: A Pilot Study To Understand the Impact of Race/Ethnicity in Alzheimer's Disease

The number of people suffering from Alzheimer's disease (AD) is increasing rapidly every year. One aspect of AD that is often overlooked is the disproportionate incidence of AD among African American/Black populations. With the recent development of novel assays for lipidomics analysis in recent times, there has been a drastic increase in the number of studies focusing on changes of lipids in AD. However, very few of these studies have focused on or even included samples from African American/Black individuals samples. In this study, we aimed to determine if the lipidome in AD is universal across non-Hispanic White and African American/Black individuals. To accomplish this, a targeted mass spectrometry lipidomics analysis was performed on plasma samples (N = 113) obtained from cognitively normal (CN, N = 54) and AD (N = 59) individuals from African American/Black (N = 56) and non-Hispanic White (N = 57) backgrounds. Five lipids (PS 18:0_18:0, PS 18:0_20:0, PC 16:0_22:6, PC 18:0_22:6, and PS 18:1_22:6) were altered between AD and CN sample groups (p value < 0.05). Upon racial stratification, there were notable differences in lipids that were unique to African American/Black or non-Hispanic White individuals. PS 20:0_20:1 was reduced in AD in samples from non-Hispanic White but not African American/Black adults. We also tested whether race/ethnicity significantly modified the association between lipids and AD status by including a race × diagnosis interaction term in a linear regression model. PS 20:0_20:1 showed a significant interaction (p = 0.004). The discovery of lipid changes in AD in this study suggests that identifying relevant lipid biomarkers for diagnosis will require diversity in sample cohorts.

Dynamic Progress in Technological Advances to Study Lipids in Aging: Challenges and Future Directions

Lipids participate in all cellular processes. Diverse methods have been developed to investigate lipid composition and distribution in biological samples to understand the effect of lipids across an organism’s lifespan. Here, we summarize the advanced techniques for studying lipids, including mass spectrometry-based lipidomics, lipid imaging, chemical-based lipid analysis and lipid engineering and their advantages. We further discuss the limitation of the current methods to gain an in-depth knowledge of the role of lipids in aging, and the possibility of lipid-based therapy in aging-related diseases.

E. coli strain-dependent lipid alterations in cocultures with endothelial cells and neutrophils modeling sepsis

Dysregulated lipid metabolism is common in infection and inflammation and is a part of the complex milieu underlying the pathophysiological sequelae of disease. Sepsis is a major cause of mortality and morbidity in the world and is characterized by an exaggerated host response to an infection. Metabolic changes, including alterations in lipid metabolism, likely are important in sepsis pathophysiology. Here, we designed an in vitro cell culture model using endothelial cells, E. coli, and neutrophils to mimic sepsis in a simplified cell model. Lipid alterations were studied in the presence of the pathogenic E. coli strain CFT073 and non-pathogenic E. coli strain JM109. We employed untargeted lipidomics to first identify lipid changes and then targeted lipidomics to confirm changes. Both unique and shared lipid signatures were identified in cocultures with these E. coli strains. In the absence of neutrophils, the CFT073 strain elicited alterations in lysophosphatidylcholine and diglyceride molecular species during coculture while both strains led to increases in phosphatidylglycerols. Lipid alterations in these cocultures changed with the addition of neutrophils. In the presence of neutrophils with E. coli and endothelial cells, triglyceride increases were a unique response to the CFT073 strain while phosphatidylglycerol and diglyceride increases occurred in response to both strains. Phosphatidylethanolamine also increased in neutrophils, E. coli and endothelial cells cocultures, and this response was greater in the presence of the CFT073 strain. We further evaluated changes in phosphatidylethanolamine in a rat model of sepsis, which showed multiple plasma phosphatidylethanolamine molecular species were elevated shortly after the induction of sepsis. Collectively, these findings demonstrate unique lipid responses by co-cultures of E. coli with endothelial cells which are dependent on the E. coli strain as well as the presence of neutrophils. Furthermore, increases in phosphatidylethanolamine levels in CFT073 urosepsis E. coli, endothelial cell, neutrophil cocultures were similarly observed in the plasma of septic rats.

Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Altered Cardiac Energetics and Mitochondrial Dysfunction in Hypertrophic Cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is a complex disease partly explained by the effects of individual gene variants on sarcomeric protein biomechanics. At the cellular level, HCM mutations most commonly enhance force production, leading to higher energy demands. Despite significant advances in elucidating sarcomeric structure-function relationships, there is still much to be learned about the mechanisms that link altered cardiac energetics to HCM phenotypes. In this work, we test the hypothesis that changes in cardiac energetics represent a common pathophysiologic pathway in HCM.

METHODS

We performed a comprehensive multiomics profile of the molecular (transcripts, metabolites, and complex lipids), ultrastructural, and functional components of HCM energetics using myocardial samples from 27 HCM patients and 13 normal controls (donor hearts).

RESULTS

Integrated omics analysis revealed alterations in a wide array of biochemical pathways with major dysregulation in fatty acid metabolism, reduction of acylcarnitines, and accumulation of free fatty acids. HCM hearts showed evidence of global energetic decompensation manifested by a decrease in high energy phosphate metabolites (ATP, ADP, and phosphocreatine) and a reduction in mitochondrial genes involved in creatine kinase and ATP synthesis. Accompanying these metabolic derangements, electron microscopy showed an increased fraction of severely damaged mitochondria with reduced cristae density, coinciding with reduced citrate synthase activity and mitochondrial oxidative respiration. These mitochondrial abnormalities were associated with elevated reactive oxygen species and reduced antioxidant defenses. However, despite significant mitochondrial injury, HCM hearts failed to upregulate mitophagic clearance.

CONCLUSIONS

Overall, our findings suggest that perturbed metabolic signaling and mitochondrial dysfunction are common pathogenic mechanisms in patients with HCM. These results highlight potential new drug targets for attenuation of the clinical disease through improving metabolic function and reducing mitochondrial injury.

A DMS Shotgun Lipidomics Workflow Application to Facilitate High-Throughput, Comprehensive Lipidomics

Differential mobility spectrometry (DMS) is highly useful for shotgun lipidomic analysis because it overcomes difficulties in measuring isobaric species within a complex lipid sample and allows for acyl tail characterization of phospholipid species. Despite these advantages, the resulting workflow presents technical challenges, including the need to tune the DMS before every batch to update compensative voltages settings within the method. The Sciex Lipidyzer platform uses a Sciex 5500 QTRAP with a DMS (SelexION), an LC system configured for direction infusion experiments, an extensive set of standards designed for quantitative lipidomics, and a software package (Lipidyzer Workflow Manager) that facilitates the workflow and rapidly analyzes the data. Although the Lipidyzer platform remains very useful for DMS-based shotgun lipidomics, the software is no longer updated for current versions of Analyst and Windows. Furthermore, the software is fixed to a single workflow and cannot take advantage of new lipidomics standards or analyze additional lipid species. To address this multitude of issues, we developed Shotgun Lipidomics Assistant (SLA), a Python-based application that facilitates DMS-based lipidomics workflows. SLA provides the user with flexibility in adding and subtracting lipid and standard MRMs. It can report quantitative lipidomics results from raw data in minutes, comparable to the Lipidyzer software. We show that SLA facilitates an expanded lipidomics analysis that measures over 1450 lipid species across 17 (sub)classes. Lastly, we demonstrate that the SLA performs isotope correction, a feature that was absent from the original software.

In-depth triacylglycerol profiling using MS3 Q-Trap mass spectrometry

Total triacylglycerol (TAG) level is a key clinical marker of metabolic and cardiovascular diseases. However, the roles of individual TAGs have not been thoroughly explored in part due to their extreme structural complexity. We present a targeted mass spectrometry-based method combining multiple reaction monitoring (MRM) and multiple stage mass spectrometry (MS³) for the comprehensive qualitative and semiquantitative profiling of TAGs. This method referred as TriP-MS3 - triacylglycerol profiling using MS³ - screens for more than 6,700 TAG species in a fully automated fashion. TriP-MS3 demonstrated excellent reproducibility (median interday CV ∼ 0.15) and linearity (median R² = 0.978) and detected 285 individual TAG species in human plasma. The semiquantitative accuracy of the method was validated by comparison with a state-of-the-art reverse phase liquid chromatography (RPLC)-MS (R² = 0.83), which is the most commonly used approach for TAGs profiling. Finally, we demonstrate the utility and the versatility of the method by characterizing the effects of a fatty acid desaturase inhibitor on TAG profiles in vitro and by profiling TAGs in Caenorhabditis elegans.

Aging and its treatment with vitamin C: a comprehensive mechanistic review

Aging and age-related disorders have become one of the prominent issue of world. Oxidative stress due to overproduction of reactive oxygen species is the most significant cause of aging. The aim of literature compilation was to elucidate the therapeutic effect of vitamin C against oxidative stress. Various mediators with anti-inflammatory and anti-oxidant properties might be probable competitors of vitamin C for the improvement of innovative anti-aging treatments. More attention has been paid to vitamin C due to its anti-oxidant property and potentially beneficial biological activities for inhibiting aging.Vitamin C acts as an antioxidant agent and free radical scavenger that can protect the cell from oxidative stress, disorganization of chromatin, telomere attrition, and prolong the lifetime. This review emphasizes mechanism of aging and various biomarkers that are directly related to aging and also focuses on the therapeutic aspect of vitamin C against oxidative stress and age-related disorders.