Lipidomic Profiling for Serum Biomarkers in Mice Exposed to Ionizing Radiation

Targeted lipidomics-based study of radiation-induced metabolite profiles changes in plasma of total body irradiation cases

PURPOSE

Lipidomics is an important tool for triaging exposed individuals, and helps early adoption of prevention and control strategies. The purpose of this study was to screen significantly perturbed lipids between pre- and post-irradiation of human plasma samples after total body irradiation (TBI) and explore potential radiation biomarkers for early radiation classification.

METHODS

Plasma samples were collected before and after irradiation from 22 hospitalized cases of acute myeloid leukemia (AML) prepared for bone marrow transplantation. Acute total-body γ irradiation was performed at doses of 0, 4, 8, and 12 Gy. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) with multiple reaction monitoring (MRM) method was utilized. Self-paired studies before and after irradiation were performed to screen potential lipid categorization markers and markers of dose-response relationships for radiation perturbation in humans. Based on the screened potential markers, a human TBI dose estimation model was developed.

RESULTS

In total, 426 individual lipids from 14 major classes were quantified and 152 potential biomarkers with categorical characteristics were screened. A total of 80 lipids (32 TGs, 29 SMs, 9 FAs, 5 CEs, 5 PIs) were upregulated at 4 Gy, and a total of 91 lipids (39 SMs, 18 TGs, 15 HexCers, 7 CEs, 6 Cers, 3 LacCers, 2 LPEs, 1 PI) were upregulated at 12 Gy. Comparison of the ROC curves between the non-exposed and exposed groups at different doses showed AUC values ranging from 0.807 to 0.876. The metabolic pathways of potential lipid markers are mainly sphingolipid and glycerolipid metabolism, unsaturated fatty acid biosynthesis, fatty acid degradation and biosynthesis. Among the 13 dose-dependent radiosensitive lipids, CE (20:5), CE (18:1) and PI (18:2/18:2) were gradually incorporated into the TBI dose estimation model.

CONCLUSION

This study suggested that it was feasible to acquire quantitative lipid biomarker panels using targeted lipidomics platforms for rapid, high-throughput triage. Lipidomics strategies for radiation biodosimetry in humans were established with lipid biomarkers with good dose-response relationship.

Untargeted Plasma Lipidomics Reveal Perturbed Metabolites of Glycerophospholipids, and Sphingolipids in Moderate-to-Severe Acne

Background

Acne vulgaris (AV) is a common inflammatory disorder involving the pilosebaceous unit. The study aimed to explore the plasma lipidome signatures and identify specific lipid biomarkers in moderate-to-severe acne patients.

Patients and Methods

Untargeted plasma lipidomic analysis using ultra-high performance liquid chromatography system (UHPLC) coupled to q-extraction plus was employed on 30 moderate-to-severe acne patients aged between 16-25 years and 30 healthy controls. Multivariate data analyses were used to identify the distinguishing lipid metabolites.

Results

All 1449 species of 37 lipid subclasses were identified from the MS data. There were apparent differences in plasma lipid profiles between acne groups and control groups. With variable influence on projection (VIP) > 1.0 and P-value < 0.05, 26 significantly different lipid metabolites were identified. These metabolites consisted mainly of glycerophospholipids (GPs), sphingolipids (SPs), and glycerolipids (GLs). Combining with AUC≥0.800 as the elected criteria, we obtained five differential lipids with good diagnostic performance for acne severity, including 2 sphingomyelins (SM), 1 phosphatidylglycerol (PG), 1 trihexosylceramide (Hex3Cer), and 1 Phosphatidylcholine (PC). Among them, PG (44:0) had the highest AUC values.

Conclusion

Our study revealed the plasma lipidome signature of patients with moderate-to-severe acne. The results will provide a novel light into the perturbed lipid metabolism leading to the development of acne.

Nontargeted metabolomics to characterize the effects of isotretinoin on skin metabolism in rabbit with acne

Background: Acne vulgaris is a chronic inflammatory disease of the pilosebaceous unit. This study aimed to explore the pathogenesis of acne and the therapeutic mechanism of isotretinoin from the metabolic perspective in coal tar-induced acne in rabbits.

Methods: Ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-qTOF-MS) based metabolomics was used to identify skin metabolites in groups C (blank control), M (model group) and T (isotretinoin group). Multivariate statistical analysis was used to process the metabolomics data.

Results: 98 differential metabolites in group C and group M were identified. The highest proportion of differential metabolites were organic acids and derivatives, lipid metabolites, organic heterocyclic compounds, and nucleoside metabolites. The most significant metabolic pathways included protein digestion and absorption, central carbon metabolism in cancer, ABC transporters, aminoacyl-tRNA biosynthesis, biosynthesis of amino acids, and sphingolipid signaling pathway. Isotretinoin treatment normalized eight of these metabolites.

Conclusions: Our study will help to further elucidate the pathogenesis of acne, the mechanism of isotretinoin at the metabolite level, and identify new therapeutic targets for treating acne.

An optimized method for the isolation of urinary extracellular vesicles for molecular phenotyping: detection of biomarkers for radiation exposure

Background

Urinary extracellular vesicles (EVs) are a source of biomarkers with broad potential applications across clinical research, including monitoring radiation exposure. A key limitation to their implementation is minimal standardization in EV isolation and analytical methods. Further, most urinary EV isolation protocols necessitate large volumes of sample. This study aimed to compare and optimize isolation and analytical methods for EVs from small volumes of urine.

Methods

3 EV isolation methods were compared: ultracentrifugation, magnetic bead-based, and size-exclusion chromatography from 0.5 mL or 1 mL of rat and human urine. EV yield and mass spectrometry signals (Q-ToF and Triple Quad) were evaluated from each method. Metabolomic profiling was performed on EVs isolated from the urine of rats exposed to ionizing radiation 1-, 14-, 30- or 90-days post-exposure, and human urine from patients receiving thoracic radiotherapy for the treatment of lung cancer pre- and post-treatment.

Results

Size-exclusion chromatography is the preferred method for EV isolation from 0.5 mL of urine. Mass spectrometry-based metabolomic analyses of EV cargo identified biochemical changes induced by radiation, including altered nucleotide, folate, and lipid metabolism. We have provided standard operating procedures for implementation of these methods in other laboratories.

Conclusions

We demonstrate that EVs can be isolated from small volumes of urine and analytically investigated for their biochemical contents to detect radiation induced metabolomic changes. These findings lay a groundwork for future development of methods to monitor response to radiotherapy and can be extended to an array of molecular phenotyping studies aimed at characterizing EV cargo.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03414-7.

Multi-Omics Approaches and Radiation on Lipid Metabolism in Toothed Whales

Lipid synthesis pathways of toothed whales have evolved since their movement from the terrestrial to marine environment. The synthesis and function of these endogenous lipids and affecting factors are still little understood. In this review, we focused on different omics approaches and techniques to investigate lipid metabolism and radiation impacts on lipids in toothed whales. The selected literature was screened, and capacities, possibilities, and future approaches for identifying unusual lipid synthesis pathways by omics were evaluated. Omics approaches were categorized into the four major disciplines: lipidomics, transcriptomics, genomics, and proteomics. Genomics and transcriptomics can together identify genes related to unique lipid synthesis. As lipids interact with proteins in the animal body, lipidomics, and proteomics can correlate by creating lipid-binding proteome maps to elucidate metabolism pathways. In lipidomics studies, recent mass spectroscopic methods can address lipid profiles; however, the determination of structures of lipids are challenging. As an environmental stress, the acoustic radiation has a significant effect on the alteration of lipid profiles. Radiation studies in different omics approaches revealed the necessity of multi-omics applications. This review concluded that a combination of many of the omics areas may elucidate the metabolism of lipids and possible hazards on lipids in toothed whales by radiation.

Lipid profiles and differential lipids in serum related to severity of community-acquired pneumonia: A pilot study

This study aimed to characterize the lipidomic responses to community-acquired pneumonia (CAP) and provide new insight into the underlying mechanisms of pathogenesis and potential avenues for diagnostic and therapeutic treatments. This study was performed from January 2017 to October 2018. Lipidomic profiles were generated using ultra high-performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) platform. Spearman's rank correlation test and multiple linear regression analysis were applied to explore the correlation between changes in the relative abundance of lipids and clinical parameters. Kaplan-Meier methods were used to build 30-day survival curves. From the UHPLC-MS/MS results, a total of 509 and 195 lipid species were detected in the positive and negative ionization mode respectively. Positive ionization covered six lipid classes (glycerol-phospholipids, glycerolipids, sphingolipids, sterol-lipids, prenol-lipids, and fatty acid), whilst negative ionization covered three (glycerol-phospholipids, sphingolipids, fatty acid). Four lipids were selected as targets: PC (16:0_18:1), PC (18:2_20:4), PC (36:4), and PC (38:6). The relative increase of the areas under the curves for all four lipids were superior to the pneumonia severity index and CURB-65 (confusion, urea, respiratory rate, blood pressure, and age ≥65 years old) for discriminating severe CAP from CAP. Decreasing relative levels of PC (18:2_20:4), PC (38:6), and PC (36:4) were negatively related to fraction of inspiration O2; Changes in the relative abundance of PC (16:0_18:1) and PC (18:2_20:4) had significantly linear relationship with procalcitonin. Patients with an elevated level of PC (16:0_18:1) had significantly longer duration of hospital stays. As the relative abundance of PC (18:2_20:4), PC (36:4), and PC (38:6) decreased, the length of hospitalization days and 30-day mortality rate increased significantly (all log-rank p<0.05). Therefore, using the UHPLC-MS/MS platform's serum lipidomic approach can help reveal changes in lipid abundance during CAP and establish lipid profiles related to disease severity.