Development of pseudo-targeted profiling of isotopic metabolomics using combined platform of high resolution mass spectrometry and triple quadrupole mass spectrometry with application of 13C6-glucose tracing in HepG2 cells.

Isotope tracing assisted metabolic analysis is becoming a unique tool to understand metabolic regulation in cell biology and biomedical research. Targeted mass spectrometry analysis based on selected reaction monitoring (SRM) has been widely applied in isotope tracing experiment with the advantages of high sensitivity and broad linearity. However, its application for new pathway discovery is largely restrained by molecular coverage. To overcome this limitation, we describe a strategy called pseudo-targeted profiling of isotopic metabolomics (PtPIM) to expand the analysis of isotope labeled metabolites beyond the limit of known pathways and chemical standards. Pseudo-targeted metabolomics was first established with ion transitions and retention times transformed from high resolution (orbitrap) mass spectrometry. Isotope labeled MRM transitions were then generated according to chemical formulas of fragments, which were derived from accurate ion masses acquired by HRMS. An in-house software "PseudoIsoMRM" was developed to simulate isotope labeled ion transitions in batch mode and correct the interference of natural isotopologues. This PtPIM strategy was successfully applied to study 13C6-glucose traced HepG2 cells. As 313 molecules determined as analysis targets, a total of 4104 ion transitions were simulated to monitor 13C labeled metabolites in positive-negative switching mode of QQQ mass spectrometer with minimum dwell time of 0.3 ms achieved. A total of 68 metabolites covering glycolysis, TCA cycle, nucleotide biosynthesis, one-carbon metabolism and related derivatives were found to be labeled (> 2%) in HepG2 cells. Active pentose phosphate pathway was observed with diverse labeling status of glycolysis intermediates. Meanwhile, our PtPIM strategy revealed that rotenone severely suppressed mitochondrial function e.g. oxidative phosphorylation and fatty acid beta-oxidation. In this case, anaerobic respiration became the major source of energy metabolism by producing abundant lactate. Conclusively, the simulation based PtPIM method demonstrates a strategy to broaden metabolite coverage in isotope tracing analysis independent of standard chemicals.

A simulated strategy for analysis of Short- to Long- chain fatty acids in mouse serum beyond chemical standards.

Broadening coverage in fatty acid (FA) analysis benefits the understanding of metabolic regulation in biological system. However, the limited access of chemical standards makes it challenging. In this work, we introduced a simulation assisted strategy to analyze short-, medium-, long- and very-long-chain fatty acids beyond the use of chemical standards. This targeted analysis in selected reaction monitoring (SRM) mode incorporated 3-nitrophenylhydrazine derivatization and mathematical simulation of ion transitions, collision energies, RF values and retention times to identify and quantify the fatty acids without chemical standards. Serum analysis using high resolution mass spectrometry coupled with paired labeling was employed to refine the computational retention times. Based on the simulation, 116 free fatty acids from C1 to C24 were covered in a single analysis on use of 34 standard chemicals. Background interference is commonly observed in fatty acid analysis. For certain fatty acids, e.g. acetic acid or palmitic acid, reliable quantitation is largely restricted by contamination level instead of detection limit. Therefore, the background interference and quantifiable serum volume required for each fatty acid were also evaluated. At least 20 µL serum was suggested to cover most molecules. Using this approach, a total of 66 free fatty acids with various chain lengths and saturations were detected in NTCP knockout mice serum, of which 34 FAs were confirmed by chemical standards and 32 FAs were potentially assigned based on the simulation. Gender dependent fatty acid regulation was observed by NTCP knockout. This work provides a unique strategy that enables to broaden the fatty acid coverage with the absence of chemical standards and is applicable to other derivatizations.

SLC22A14 is a mitochondrial riboflavin transporter required for sperm oxidative phosphorylation and male fertility.

Ablation of Slc22a14 causes male infertility in mice, but the underlying mechanisms remain unknown. Here, we show that SLC22A14 is a riboflavin transporter localized at the inner mitochondrial membrane of the spermatozoa mid-piece and show by genetic, biochemical, multi-omic, and nutritional evidence that riboflavin transport deficiency suppresses the oxidative phosphorylation and reprograms spermatozoa energy metabolism by disrupting flavoenzyme functions. Specifically, we find that fatty acid ß-oxidation (FAO) is defective with significantly reduced levels of acyl-carnitines and metabolites from the TCA cycle (the citric acid cycle) but accumulated triglycerides and free fatty acids in Slc22a14 knockout spermatozoa. We demonstrate that Slc22a14-mediated FAO is essential for spermatozoa energy generation and motility. Furthermore, sperm from wild-type mice treated with a riboflavin-deficient diet mimics those in Slc22a14 knockout mice, confirming that an altered riboflavin level causes spermatozoa morphological and bioenergetic defects. Beyond substantially advancing our understanding of spermatozoa energy metabolism, our study provides an attractive target for the development of male contraceptives.

Quantitative molecular tissue atlas of Bis(monoacylglycero)phosphate and phosphatidylglycerol membrane lipids in rodent organs generated by methylation assisted high resolution mass spectrometry.

Bis(monoacylglycero)phosphate (BMP) and phosphatidylglycerol (PG) are structural isomeric phospholipids with very different properties and biological functions. Due to their isomeric nature, it has thus far been challenging to simultaneously quantify BMP and PG lipids in tissue samples by mass spectrometry. Therefore, we have developed a sensitive LC-MS/MS based approach with prior methylation derivatization that is able to handle large batches of samples. Using this high throughput platform, a simulated MS/MS database was established for confident lipid assignment. In this work, we have simultaneously identified and quantified BMP and PG lipid molecules in different body tissues of rats and mice. We report for the first time a quantitative molecular atlas of BMP and PG lipids for 14 different tissues and organs in Wistar rats, NMRI and CD1 mice. Organ- and species-specificity was analyzed and compared for both lipid molecule classes. A total of 34 BMP and 10 PG molecules were quantified, with PG concentrations being generally much higher across tissues than BMP, but BMP lipids showing a much higher molecular diversity between animal organs. The large diversity of the BMP lipids with regard to their abundance and molecular composition suggests distinct biological function(s) of the individual BMP molecules in different tissues and organs of body. Particularly high tissue levels of BMP were seen in spleen, lung, liver, kidney and small intestines, i.e. tissues that are known for their high abundance and/or activity level of lysosomes late and endosomes. Elevated BMP levels in brain tissue of APP/PSEN transgenic compared to age matched wild-type mice were also observed using this platform. This analytical methodology presented a high throughput LC-based approach incorporating simulated MS/MS database to identify and quantify BMP lipids as well as PG molecules.

Assessment of potential false positives via orbitrap-based untargeted lipidomics from rat tissues.

Untargeted lipidomics is increasingly popular due to the broad coverage of lipid species. Data dependent MS/MS acquisition is commonly used in order to acquire sufficient information for confident lipid assignment. However, although lipids are identified based on MS/MS confirmation, a number of false positives are still observed. Here, we discuss several causes of introducing lipid false identifications in untargeted analysis. Phosphotidylcholines and cholesteryl esters generate in-source fragmentation to produce dimethylated phosphotidylethanolamine and free cholesterol. Dimerization of fatty acid results in false identification of fatty acid ester of hydroxyl fatty acid. Realizing these false positives is able to improve confidence of results acquired from untargeted analysis. Besides, thresholds are established for lipids identified using LipidSearch v4.1.16 software to reduce unreliable results.