A defect in mitochondrial fatty acid synthesis impairs iron metabolism and causes elevated ceramide levels.

In most eukaryotic cells, fatty acid synthesis (FAS) occurs in the cytoplasm and in mitochondria. However, the relative contribution of mitochondrial FAS (mtFAS) to the cellular lipidome is not well defined. Here we show that loss of function of Drosophila mitochondrial enoyl coenzyme A reductase (Mecr), which is the enzyme required for the last step of mtFAS, causes lethality, while neuronal loss of Mecr leads to progressive neurodegeneration. We observe a defect in Fe-S cluster biogenesis and increased iron levels in flies lacking mecr, leading to elevated ceramide levels. Reducing the levels of either iron or ceramide suppresses the neurodegenerative phenotypes, indicating an interplay between ceramide and iron metabolism. Mutations in human MECR cause pediatric-onset neurodegeneration, and we show that human-derived fibroblasts display similar elevated ceramide levels and impaired iron homeostasis. In summary, this study identifies a role of mecr/MECR in ceramide and iron metabolism, providing a mechanistic link between mtFAS and neurodegeneration.

Characterization of Lipid Alterations by Oncogenic PIK3CA Mutations Using Untargeted Lipidomics in Breast Cancer.

Lipids play crucial biological roles in health and disease, including in cancers. The phosphatidylinositol 3-kinase (PI3K) signaling pathway is a pivotal promoter of cell growth and proliferation in various types of cancer. The somatic mutations in PIK3CA, the gene coding for the catalytic subunit p110α of PI3K, are frequently present in cancer cells, including breast cancer. Although the most prominent mutants, represented by single amino acid substitutions in the helical domain in exon 9 (E545K) and the kinase domain in exon 20 (H1047R) are known to cause a gain of PI3K function, activate AKT signaling and induce oncogenic transformation, the effect of these mutations on cellular lipid profiles has not been studied. We carried out untargeted lipidomics using liquid chromatography-tandem mass spectrometry to detect the lipid alterations in mammary gland epithelial MCF10A cells with isogenic knockin of these mutations. A total of 536 species of lipids were analyzed. We found that the levels of monosialogangliosides, signaling molecules known to enhance cell motility through PI3K/AKT pathway, were significantly higher in both mutants. In addition, triglycerides and ceramides, lipid molecules known to be involved in promoting lipid droplet production, cancer cell migration and invasion, were increased, whereas lysophosphatidylcholines and phosphatidylcholines that are known to inhibit cancer cell motility were decreased in both mutants. Our results provide novel insights into a potential link between altered lipid profile and carcinogenesis caused by the PIK3CA hotspot mutations. In addition, we suggest untargeted lipidomics offers prospects for precision/personalized medicine by unpacking new molecular substrates of cancer biology.

An exploratory study of plasma ceramides in comorbidities in Down syndrome.

Plasma ceramide levels (henceforth, "ceramides") are biomarkers of some diseases that are comorbidities of Down syndrome (DS). We sought to determine if comorbidities in DS were associated with ceramides, studying a convenience cohort of 35 study participants, all ≥12 months old. To identify comorbidities, we reviewed the problem lists in electronic health records that were concurrent with sample collection. We placed clinically related comorbidities into one of five categories of comorbidities, henceforth, categories: obesity/overweight; autoimmune disease; congenital heart disease; bacterial infection; and central nervous system (CNS) condition. We measured the eight ceramides most frequently associated with disease using liquid chromatography-tandem mass spectrometry. We calculated a ceramide composite outcome score (CCOS) for each participant by normalizing each ceramide level to the mean for that level in the study population and then summing the normalized levels, to be proxy variable for all eight ceramides in aggregate. We used multivariable linear regression models adjusted for age and sex to test associations of categories with ceramides and with CCOSs. Post hoc, we realized that co-occurring comorbidities might interfere with establishing associations between predictor categories and ceramides and that stratified analyses might eliminate their influence on associations. We posited that CCOSs could be used to screen for associations of categories with multiple ceramides, since most diseases have been associated with more than one ceramide. We chose to omit in the stratified analyses the two categories that were the most different from one another in their associations with their CCOSs, having the most divergent regression coefficients (the highest positive and lowest negative coefficients). We first omitted one of these two divergent categories in a stratified analysis and tested in the remaining participants (those without a comorbidity in the interfering category) for associations of the other four categories with their CCOSs and then did the same for the other divergent category. In each of these two screening stratified analyses, we found one category was significantly associated with its CCOS. In the two identified categories, we then tested for associations with each of the eight ceramides, using the appropriate stratified analysis. Next, we sought to determine if the associations of the two categories with ceramides we found by omitting participants in the interfering categories held in our small sample for participants in the omitted categories as well. For each of the two categories, we therefore omitted participants without the interfering category and determined associations between the predictor category and individual ceramides in the remaining participants (those with a comorbidity in the interfering category). In the a priori analyses, autoimmune disease was inversely associated with C16 and CNS condition was inversely associated with C23. Obesity/overweight and CNS condition were the two categories with the most divergent regression coefficients (0.037 vs. -0.048). In post hoc stratified analyses, after omitting participants with obesity/overweight, thereby leaving participants without obesity/overweight, bacterial infection was associated with its CCOS and then with C14, C20, and C22. However, in the companion stratified analyses, omitting participants without obesity/overweight, thereby leaving participants with obesity/overweight, bacterial infection was not associated with any of the eight ceramides. Similarly, in post hoc stratified analyses after omitting participants with a CNS condition, thereby leaving participants without a CNS condition, obesity/overweight was associated with its CCOS and then with C14, C23, and C24. In the companion analyses, omitting participants without a CNS condition, thereby leaving participants with a CNS condition, obesity/overweight was inversely associated with C24.1. In conclusion, CNS and autoimmune disease were inversely associated with one ceramide each in a priori analyses. In post hoc analyses, we serendipitously omitted categories that interfered with associations of other categories with ceramides in stratified analyses. We found that bacterial infection was associated with three ceramides in participants without obesity/overweight and that obesity/overweight was associated with three ceramides in participants without a CNS condition. We therefore identified obesity/overweight and CNS conditions as potential confounders or effect modifiers for these associations. This is the first report of ceramides in DS and in human bacterial infection. Further study of ceramides in comorbidities of DS is justified.

Exploring therapeutic strategies for infantile neuronal axonal dystrophy (INAD/PARK14).

Infantile neuroaxonal dystrophy (INAD) is caused by recessive variants in PLA2G6 and is a lethal pediatric neurodegenerative disorder. Loss of the Drosophila homolog of PLA2G6, leads to ceramide accumulation, lysosome expansion, and mitochondrial defects. Here, we report that retromer function, ceramide metabolism, the endolysosomal pathway, and mitochondrial morphology are affected in INAD patient-derived neurons. We show that in INAD mouse models, the same features are affected in Purkinje cells, arguing that the neuropathological mechanisms are evolutionary conserved and that these features can be used as biomarkers. We tested 20 drugs that target these pathways and found that Ambroxol, Desipramine, Azoramide, and Genistein alleviate neurodegenerative phenotypes in INAD flies and INAD patient-derived neural progenitor cells. We also develop an AAV-based gene therapy approach that delays neurodegeneration and prolongs lifespan in an INAD mouse model.

TRIT1 defect leads to a recognizable phenotype of myoclonic epilepsy, speech delay, strabismus, progressive spasticity, and normal lactate levels.

TRIT1 defect is a rare, autosomal-recessive disorder of transcription, initially described as a condition with developmental delay, myoclonic seizures, and abnormal mitochondrial function. Currently, only 13 patients have been reported. We reviewed the genetic, clinical, and metabolic aspects of the disease in all known patients, including two novel, unrelated TRIT1 cases with abnormalities in oxidative phosphorylation complexes I and IV in fibroblasts. Taken together the features of all 15 patients, TRIT1 defect could be identified as a potentially recognizable syndrome including myoclonic epilepsy, speech delay, strabismus, progressive spasticity, and variable microcephaly, with normal lactate levels. Half of the patients had oxidative phosphorylation complex measurements and had multiple complex abnormalities.

Neuronal activity induces glucosylceramide that is secreted via exosomes for lysosomal degradation in glia.

Recessive variants in GBA1 cause Gaucher disease, a prevalent form of lysosome storage disease. GBA1 encodes a lysosomal enzyme that hydrolyzes glucosylceramide (GlcCer) into glucose and ceramide. Its loss causes lysosomal dysfunction and increased levels of GlcCer. We generated a null allele of the Drosophila ortholog Gba1b by inserting the Gal4 using CRISPR-Cas9. Here, we show that Gba1b is expressed in glia but not in neurons. Glial-specific knockdown recapitulates the defects found in Gba1b mutants, and these can be rescued by glial expression of human GBA1. We show that GlcCer is synthesized upon neuronal activity, and it is transported from neurons to glia through exosomes. Furthermore, we found that glial TGF-ß/BMP induces the transfer of GlcCer from neurons to glia and that the White protein, an ABCG transporter, promotes GlcCer trafficking to glial lysosomes for degradation.

Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study.

BACKGROUND: COVID-19 is a multi-system disorder with high variability in clinical outcomes among patients who are admitted to hospital. Although some cytokines such as interleukin (IL)-6 are believed to be associated with severity, there are no early biomarkers that can reliably predict patients who are more likely to have adverse outcomes. Thus, it is crucial to discover predictive markers of serious complications. METHODS: In this retrospective cohort study, we analysed samples from 455 participants with COVID-19 who had had a positive SARS-CoV-2 RT-PCR result between April 14, 2020, and Dec 1, 2020 and who had visited one of three Mayo Clinic sites in the USA (Minnesota, Arizona, or Florida) in the same period. These participants were assigned to three subgroups depending on disease severity as defined by the WHO ordinal scale of clinical improvement (outpatient, severe, or critical). Our control cohort comprised of 182 anonymised age-matched and sex-matched plasma samples that were available from the Mayo Clinic Biorepository and banked before the COVID-19 pandemic. We did a deep profiling of circulatory cytokines and other proteins, lipids, and metabolites from both cohorts. Most patient samples were collected before, or around the time of, hospital admission, representing ideal samples for predictive biomarker discovery. We used proximity extension assays to quantify cytokines and circulatory proteins and tandem mass spectrometry to measure lipids and metabolites. Biomarker discovery was done by applying an AutoGluon-tabular classifier to a multiomics dataset, producing a stacked ensemble of cutting-edge machine learning algorithms. Global proteomics and glycoproteomics on a subset of patient samples with matched pre-COVID-19 plasma samples was also done. FINDINGS: We quantified 1463 cytokines and circulatory proteins, along with 902 lipids and 1018 metabolites. By developing a machine-learning-based prediction model, a set of 102 biomarkers, which predicted severe and clinical COVID-19 outcomes better than the traditional set of cytokines, were discovered. These predictive biomarkers included several novel cytokines and other proteins, lipids, and metabolites. For example, altered amounts of C-type lectin domain family 6 member A (CLEC6A), ether phosphatidylethanolamine (P-18:1/18:1), and 2-hydroxydecanoate, as reported here, have not previously been associated with severity in COVID-19. Patient samples with matched pre-COVID-19 plasma samples showed similar trends in muti-omics signatures along with differences in glycoproteomics profile. INTERPRETATION: A multiomic molecular signature in the plasma of patients with COVID-19 before being admitted to hospital can be exploited to predict a more severe course of disease. Machine learning approaches can be applied to highly complex and multidimensional profiling data to reveal novel signatures of clinical use. The absence of validation in an independent cohort remains a major limitation of the study. FUNDING: Eric and Wendy Schmidt.

Automated data-driven mass spectrometry for improved analysis of lipids with dual dissociation techniques.

Lipidomics is an important component of most multi-Omics systems biology studies and is largely driven by mass spectrometry (MS). Because lipids are tight regulators of multiple cellular functions, including energy homeostasis, membrane structures and cell signaling, lipidomics can provide a deeper understanding of variations underlying disease states and can become an even more powerful platform when combined with other omics, including genomics or proteomics. However, data analysis, especially in lipid annotation, poses challenges due to the heterogeneity of functional head groups and fatty acyl chains of varying hydrocarbon lengths and degrees of unsaturation. As there are various MS/MS fragmentation sites in lipids that are class-dependent, obtaining MS/MS data that includes as many fragment ions as possible is critical for structural characterization of lipids in lipidomics workflow. Here, we report an improved lipidomics methodology that resulted in increased coverage of lipidome using: 1) An automated data-driven MS/MS acquisition scheme in which inclusion and exclusion lists were automatically generated from the full scan MS of sample injections, followed by creation of updated lists over iterative analyses; and, 2) Incorporation of dual dissociation techniques of higher-energy collision dissociation and collision-induced dissociation for more accurate characterization of phosphatidylcholine species. Inclusion lists were created automatically based on full scan MS signals from samples and through iterative analyses, ions in the inclusion list that were fragmented were automatically moved to the exclusion list in subsequent runs. We confirmed that analytes with low MS response that did not undergo MS/MS events in conventional data-dependent analysis were successfully fragmented using this approach. Overall, this automated data-driven data acquisition approach resulted in a higher coverage of lipidome and the use of dual dissociation techniques provided additional information that was critical in characterizing the side chains of phosphatidylcholine species.

Maternal serum lipidomics identifies lysophosphatidic acid as a predictor of small for gestational age neonates.

To discover lipidomic alterations during pregnancy in mothers who subsequently delivered small for gestational age (SGA) neonates and identify predictive lipid markers that can help recognize and manage these mothers, we carried out untargeted lipidomics on maternal serum samples collected between 24-28 weeks of gestation. We used a nested case-control study design and serum from mothers who delivered SGA and appropriate for gestational age babies. We applied untargeted lipidomics using mass spectrometry to characterize lipids and discover changes associated with SGA births during pregnancy. Multivariate pattern recognition software Collaborative Laboratory Integrated Reports (CLIR) was used for the post-analytical recognition of range differences in lipid ratios that could differentiate between SGA and control mothers and their integration for complete separation between the two groups. Here, we report changes in lipids from serum collected during pregnancy in mothers who delivered SGA neonates. In contrast to normal pregnancies where lysophosphatidic acid increased over the course of the pregnancy owing to increased activity of lysophospholipase D, we observed a decrease (32%; P = 0.05) of 20:4-lysophosphatidic acid in SGA mothers, which could potentially compromise fetal growth and development. Integration of lipid ratios in an interpretive tool (CLIR) could completely separate SGA mothers from controls demonstrating the power of untargeted lipidomic analyses for identifying novel predictive biomarkers. Additional studies are required for further assessment of the lipid biomarkers identified in this report.

High-resolution mass spectrometric analysis of cardiolipin profiles in Barth syndrome.

Barth syndrome is an X-linked recessive disorder caused by pathogenic variants in TAZ, which leads to a reduction in cardiolipin with a concomitant elevation of monolysocardiolipins. There is a paucity of studies characterizing changes in individual species of monolysocardiolipins, dilysocardiolipins and cardiolipin in Barth syndrome using high resolution untargeted lipidomics that can accurately annotate and quantify diverse lipids. We confirmed the structural diversity monolysocardiolipins, dilysocardiolipins and cardiolipin and identified individual species that showed previously unreported alterations in BTHS. Development of mass spectrometry-based targeted assays for these lipid biomarkers should provide an important tool for clinical diagnosis of Barth syndrome.

Cerebrospinal fluid lipidomics for biomarkers of Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia and is associated with serious neurologic sequelae resulting from neurodegenerative changes. Identification of markers of early-stage AD could be important for designing strategies to arrest the progression of the disease. The brain is rich in lipids because they are crucial for signal transduction and anchoring of membrane proteins. Cerebrospinal fluid (CSF) is an excellent specimen for studying the metabolism of lipids in AD because it can reflect changes occurring in the brain. We aimed to identify CSF lipidomic alterations associated with AD, using untargeted lipidomics, carried out in positive and negative ion modes. We found CSF lipids that were significantly altered in AD cases. In addition, comparison of CSF lipid profiles between persons with mild cognitive impairment (MCI) and AD showed a strong positive correlation between the lipidomes of the MCI and AD groups. The novel lipid biomarkers identified in this study are excellent candidates for validation in a larger set of patient samples and as predictive biomarkers of AD through future longitudinal studies. Once validated, the lipid biomarkers could lead to early detection, disease monitoring and the ability to measure the efficacy of potential therapeutic interventions in AD.

Expanding the clinical and metabolic phenotype of DPM2 deficient congenital disorders of glycosylation.

Pathogenic alterations in the DPM2 gene have been previously described in patients with hypotonia, progressive muscle weakness, absent psychomotor development, intractable seizures, and early death. We identified biallelic DPM2 variants in a 23-year-old male with truncal hypotonia, hypertonicity, congenital heart defects, intellectual disability, and generalized muscle wasting. His clinical presentation was much less severe than that of the three previously described patients. This is the second report on this ultra-rare disorder. Here we review the characteristics of previously reported individuals with a defect in the DPM complex while expanding the clinical phenotype of DPM2-Congenital Disorders of Glycosylation. In addition, we offer further insights into the pathomechanism of DPM2-CDG disorder by introducing glycomics and lipidomics analysis.

Signature Fragment Ions of Biotinylated Peptides.

The use of biotin or biotin-containing reagents is an essential component of many protein purification and labeling technologies. Owing to its small size and high affinity to the avidin family of proteins, biotin is a versatile molecular handle that permits both enrichment and purity that is not easily achieved by other reagents. Traditionally, the use of biotinylation to enrich for proteins has not required the detection of the site of biotinylation. However, newer technologies for discovery of protein-protein interactions, such as APEX and BioID, as well as some of the click chemistry-based labeling approaches have underscored the importance of determining the exact residue that is modified by biotin. Anti-biotin antibody-based enrichment of biotinylated peptides (e.g., BioSITe) coupled to LC-MS/MS permit large-scale detection and localization of sites of biotinylation. As with any chemical modification of peptides, understanding the fragmentation patterns that result from biotin modification is essential to improving its detection by LC-MS/MS. Tandem mass spectra of biotinylated peptides has not yet been studied systematically. Here, we describe the various signature fragment ions generated with collision-induced dissociation of biotinylated peptides. We focused on biotin adducts attached to peptides generated by BioID and APEX experiments, including biotin, isotopically heavy biotin, and biotin-XX-phenol, a nonpermeable variant of biotin-phenol. We also highlight how the detection of biotinylated peptides in high-throughput studies poses certain computational challenges for accurate quantitation which need to be addressed. Our findings about signature fragment ions of biotinylated peptides should be helpful in the confirmation of biotinylation sites.

Lipidomic differentiation of Graves' ophthalmopathy in plasma and urine from Graves' disease patients.

Approximately 50% of patients with Graves' disease (GD) develop retracted eyelids with bulging eyes, known as Graves' ophthalmopathy (GO). However, no simple diagnostic blood marker for distinguishing GO from GD has been developed yet. The objective of this study was to conduct comprehensive profiling of lipids using plasma and urine samples from patients with GD and GO undergoing antithyroid therapy using nanoflow ultrahigh performance liquid chromatography electrospray ionization tandem mass spectrometry. Plasma (n = 86) and urine (n = 75) samples were collected from 23 patients with GD without GO, 31 patients with GO, and 32 healthy controls. Among 389 plasma and 273 urinary lipids that were structurally identified, 281 plasma and 191 urinary lipids were quantified in selected reaction monitoring mode. High-abundance lipids were significantly altered, indicating that the development of GD is evidently related to altered lipid metabolism in both plasma and urine. Several urinary lysophosphatidylcholine species were found to be increased (3- to 10-fold) in both GD and GO. While the overall lipid profiles between GD and GO were similar, significant changes (area under receiver operating curve > 0.8) in GO vs. GD were observed in a few lipid profiles: 58:7-TG and (16:1,18:0)-DG from plasma, 16:1-PC and 50:1-TG from urine, and d18:1-S1P from both plasma and urine samples. An altered metabolism of lipids associated with the additional development of ophthalmopathy was confirmed with the discovery of several candidate markers. These can be suggested as candidate markers for differentiating the state of GO and GD patients based on plasma or urinary lipidomic analysis. Graphical abstract.

Lipidomic analysis of skeletal muscle tissues of p53 knockout mice by nUPLC-ESI-MS/MS.

Tumour suppressor p53 is known to be associated with the maintenance of mitochondrial functional properties in the skeletal muscles. As deactivation or mutation of p53 can affect the synthesis of lipids, investigating the relationship between p53-related energy generation metabolism and perturbation of lipid profile is critical. In this study, 329 lipid species (among 412 identified species) in two different skeletal muscle tissues (the gastrocnemius and soleus) from p53 knockout (KO) mice were quantitatively analysed using nanoflow ultrahigh performance liquid chromatography tandem mass spectrometry (nUPLC-MS/MS). Overall, lipids from the soleus tissues were more affected by p53 KO than those from the gastrocnemius in most lipid profiles. In p53 KO, lysophosphatidylcholine (LPC), lysophosphatidylserine (LPS), phosphatidic acid (PA), sphingomyelin (SM), and triacylglycerol (TAG), including 6 TAG (44:2, 46:0, 58:5, 58:8, 58:9, and 50:0), were significantly increased (p < 0.05) by 1.4-2-fold only in the soleus tissue. Overall monohexosylceramide (MHC) levels, including those of 3 MHC species (d18:0/24:0, d18:1/22:0, and d18:1/24:0), were significantly increased (p < 0.05) by 2-4 fold, only in the gastrocnemius tissue. The results suggest that lipid profiles are significantly altered by the lack of p53 in muscle tissues.

Relative Quantification of Phospholipids Based on Isotope-Labeled Methylation by Nanoflow Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectrometry: Enhancement in Cardiolipin Profiling.

In this study, lipid analysis based on isotope-labeled methlylation (ILM) was performed by nanoflow ultrahigh performance liquid chromatography-eletrospray ionization-tandem mass spectrometry (nUPLC-ESI-MS/MS) for enhanced detection and quantification of targeted phospholipids. ILM depends on methylation of phosphate groups by (trimethylsilyl)diazomethane, and the ILM based quantitation with reversed phase nUPLC-ESI-MS/MS provides advantages in PL profiling such as enhanced detectability of methylated PLs owing to increased hydrophobicity and substantial increase in resolution due to the increase of retention. Efficacy of ILM in nUPLC-ESI-MS/MS analysis was evaluated in the selected reaction monitoring (SRM) method by varying the mixing ratio of H-/D-methylated PL standards, which resulted in the successful quantification of 24 species, including phosphatidic acid (PA), phosphatidylserine (PS), phosphatidylglycerol (PG), ceramide-1-phosphate (Cer1P), phosphoinositides, and cardiolipin (CL), with ∼6.6% variation in the calculated ratio of H-/D-methylated PLs. The method was applied to the lipid extracts from a DU145 cell line after D-allose treatment, resulting in the quantification of 83 PLs of which results were not statistically different from those obtained by conventional quantification methods. Morever, detection and quantification of CLs and PAs were evidenced to be highly effective when used with the ILM method as 43 CLs and 20 PAs from cellular lipid extracts were analyzed while only 18 CLs and 12 PAs were identified when conventional methods were carried out. This proves the ILM combined with LC-MS to be a promising method for analysis of the aforementioned classes of lipids. Overall, the study highlighted the applicability of targeted quantification by the ILM method in lipidomic analysis and demonstrated an improvement in the detection of less abundant anionic PLs.

Size Dependent Lipidomic Analysis of Urinary Exosomes from Patients with Prostate Cancer by Flow Field-Flow Fractionation and Nanoflow Liquid Chromatography-Tandem Mass Spectrometry.

Exosomes are membrane-bound extracellular vesicles involved in intercellular communication and tumor cell metastasis. In this study, flow field-flow fractionation (FlFFF) was utilized to separate urinary exosomes by size, demonstrating a significant difference in exosome sizes between healthy controls and patients with prostate cancer (PCa). Exosome fractions of different sizes were collected for microscopic analysis during an FlFFF run and evaluated with exosome marker proteins using Western blot analysis. The results indicated that exosomes of different sizes originated from different types of cells. Collected exosome fractions were further examined using nanoflow ultrahigh performance liquid chromatography-electrospray ionization-tandem mass spectrometry (nUPLC-ESI-MS/MS) for lipidomic analysis. A total of 162 lipids (from 286 identified) were quantified using a selected reaction monitoring (SRM) method. The overall amount of lipids increased by 1.5- to 2-fold in patients with PCa and degree of increase was more significant in the smaller fractions (diameter <150 nm) than in the larger ones (diameter >150 nm) some classes of lipids. In addition, neutral lipids like diacylglycerol (DAG) and triacylglycerol (TAG) decreased in all exosomes without size dependency. Moreover, a dramatic increase in 22:6/22:6-phosphatidylglycerol (PG) was observed and significant decrease in (16:0,16:0)- and (16:1, 18:1)-DAG species (nearly 5-fold) and high abundant TAG species (>2.5-fold) was observed in patients with PCa. The results of this study indicate that FlFFF can be employed for the high-speed screening of urinary exosome sizes in patients with PCa and lipidomic analysis of the fractionated exosomes has potential for developing and distinguishing biomarkers of PCa.

Lipidomic Perturbations in Lung, Kidney, and Liver Tissues of p53 Knockout Mice Analyzed by Nanoflow UPLC-ESI-MS/MS.

Lipids are important signaling molecules regulating biological processes under normal and diseased conditions. Although p53 mutation is well-known for causing cancer, the relationship between p53-related tumorigenesis and altered lipid profile is unclear. We profiled differences in lipid expressions in liver, lung, and kidney in p53 knockout (KO) mice by high-speed quantitative analysis of 320 lipids (399 species identified) using nanoflow ultrahigh performance liquid chromatography-tandem mass spectrometry (nUPLC-MS/MS). Lung tissues were most severely affected by the lack of p53 gene, as shown by significant reduction (24-44%, P < 0.05) in total phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), diacylglycerol (DG), and triacylglycerol (TG), and significant increases (30-50%) in phosphatidylserine (PS), phosphatidylinositol (PI), and monohexosylceramide (MHC). MHC levels increased in all tissues. Dihexosylceramide (DHC) level decreased only in kidney tissue. Most PI, PS, and phosphatidic acid (PA) species showing significant increases contained a saturated acyl chain (18:0) in lung and liver tissues. Neutral glycerolipids (16:0/22:0-DG and most TGs with saturated and monounsaturated acyl chains) decreased 2-4-fold in the liver tissue. Our results suggest that the lack of p53 and altered lipid profiles are closely related, but as their changes vary from one tissue to another, the lipid alterations are tissue-specific.