**4. Discussion**

In this study, we applied lipidomics techniques to monitor the comprehensive lipid profiles of mouse plasma and tissues, and their changes following the dietary intake of different PUFAs: ARA, EPA, and DHA. Importantly, we examined the effect of dietary supplementation of pure ARA, EPA, or DHA instead of dietary oils such as fish, linseed, and sunflower oils, and investigated the plasma and nine organs to better understand the common and/or differential lipid modulations in tissues. Mouse tissues, except for the brain, effectively incorporated the dietary PUFAs into glycerolipids and glycerophospholipids, and tissue levels of free fatty acids and oxylipins were well correlated with dietary PUFA intakes. It should be noted that our lipidomics data provided the lipidome result from "bulk" cells summing the heterogeneous nature in each tissue, and the results mainly reflect the lipid profiles of the major cell type or the major part of tissue. As for the brain, Arnold et al. reported similar results [42] when they examined cerebral cortex upon dietary EPA and DHA intake; the lipid changes in cerebral cortex were compared with other tissues including liver, kidney, heart, lung, and pancreas. Since cerebral cortex is the largest part of the brain, our whole brain data would have been significantly by the cerebral cortex. This was also the case for other tissues such as liver, white adipose, and skeletal muscle. Therefore, the lipidomes of different cell populations in each tissue should be investigated to further understand the mechanism of PUFA dietary intake in more detail.

ARA, EPA, and DHA supplementation induced various changes in lipid profiles. Dietary PUFA intake substantially increased the levels of free PUFAs and oxylipins, as well as the incorporation of PUFAs in phospholipids and triglycerides. In contrast, this side-by-side study revealed the unique features of ARA, EPA, and DHA metabolism. The basal amount of EPA was much lower than that of ARA and DHA in the plasma and tissues. This may have been because EPA easily undergoes degradation and/or conversion in tissues [43,44]. Dietary supplementation of EPA for 2 weeks elevated tissue EPA levels, and the profile of EPA-derived oxylipins was similar to that of ARA-derived oxylipins. However, the profile of DHA-derived oxylipins was a little bit different from those of ARA and EPA. These results may sugges<sup>t</sup> that EPA and DHA have different metabolic compartments, which may be associated with their difference in biological effects.

In addition, dietary DHA was selectively incorporated into a unique phospholipid BMP. BMP is known as an acyl chain positional isomer of phosphatidylglycerol (PG), in which one acyl moiety is incorporated into the glycerol polar head, and the structures can be distinguished by positive ion mode MS/MS spectra, while the MS/MS spectra are the same in negative ion mode (Figure 5c). The biosynthetic and degradation pathways of BMP are still unclear; however, several enzymes, such as AGPAT8 and α/β hydrolase domain-containing 6 (ABHD6), have been reported as candidate enzymes involved in these pathways [40,41,45,46]. The subcellular localization of BMP is in the multivesicular membranes of late endosomes, where it enhances sphingolipid activator protein activity, resulting in (glyco) sphingolipid degradation [47–49]. In addition, BMP lipids contribute to membrane deformation, fusion, and transportation, as well as the incorporation of proteins and lipids [50], and one study reported that DHA-rich BMP is prone to peroxidation to prevent cholesterol oxidation [51]. However, the biological significance of DHA-BMP in endosome function and regulation is not well understood.

PCA analysis (Figure 2) and circus plots (Figure 4 and Supplementary Figure S5) displayed the metabolic fingerprints of different tissues. In the immune organs, the spleen, small intestine, and lung, high levels of PGs, TXs and fatty acid hydroxides were detected. In contrast, PUFA epoxides were the major metabolites in plasma and other tissues. CYPs are responsible for fatty acid epoxidation, and ARA-, EPA-, and DHA-derived epoxides have various actions, such as vasodilation, anti-inflammation, anticoagulation, and anti-allergy activity [23–27].

The comprehensive lipidomics approach revealed many findings about dietary PUFA metabolism. Our untargeted/targeted lipidomics data incorporating 1026 unique lipid molecules (Supplementary Tables S2 and S3) are powerful when combined with other omics layers such as proteomics and transcriptomics. Recently, the lipidomics standards initiative (LSI) proposed three types of quantification in mass-spectrometry-based lipidomics: level 1, matching internal standards (IS) together with consideration of species-specific analytical response (essentially stating that stable-isotope-labeled lipids are preferred); level 2, matching IS where the lipid class between analyte and internal standard is identical; and level 3, non-matching IS where analytes are normalized with other lipid class molecules [52]. Although our untargeted lipidomics data have been displayed as the relative quantification in each tissue, our lipidome table can be normalized as level 3 and partially level 2 quantifications by using the internal standards. A consortium with the advances in analytical chemistry and informatics research would contribute to facilitating open data sciences through the reanalysis of deposited data [15].

This experimental design to investigate the PUFA metabolisms is expandable for further nutrient researches, and we believe that this study is a fundamental step towards clarification of the e ffects of dietary PUFA intakes in mice. Our lipidomics study o ffers a comprehensive picture of dietary PUFA metabolism in di fferent tissues, and could provide an opportunity for data-driven hypotheses and biological insights into the molecular mechanisms of how di fferent PUFA balances a ffect human and livestock health and disease.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2218-1989/9/10/241/s1, Figure S1. Calibration curves of standard compounds including internal standards. All of calibration curves of 111 metabolites and four internal standards was described. Three technical replicates were obtained for each concentration. The R-square and coe fficient value used for metabolite quantification were also described. The compound ID delimited by double underbars "\_\_" is matched with MRM transition ID described in Supplementary Table S2. The 95% confidence interval was also described by gray color. Figure S2. Factor loadings of PCA described in Figure 2. The top 20 factor loadings from the maximum and minimum values for first- and second principal components were described for each PCA result. Figure S3. Concentration of free fatty acids in each tissue after dietary intakes. Black, red, blue, and green colors represent the dietary conditions; control, ARA, EPA, and DHA supplementation respectively. The statistical significance was evaluated by Tukey's testing (\* *P* < 0.05 and \*\* *P* < 0.01) where one-way ANOVA showed the statistical significance among groups (*P* < 0.05). Figure S4. Detail of several oxylipin profiles under different dietary conditions. (a) The concentrations of 14,15-EET in control and ARA intake condition were described. (b) The concentrations of 17,18-EpETE in the control and following EPA intake were described. (c) The concentrations of 19,20-EpDPE in the control and following DHA intake were described. (d) The concentrations of 14,15-DHT in the control and following ARA intake were described. (e) The concentrations of 17,18-diHETE in the control and following EPA intake were described. (f) The concentrations of 19,20-diHDoPE in the control and following DHA intake were described. (g) The ratio of 14,15-DHT and 14,15-EET in ARA intake condition was described. (h) The ratio of 17,18-diHETE and 17,18-EpETE in EPA intake condition was described. (i) The ratio of 19,20-diHDoPE and 19,20-EpDPE in DHA intake condition was described. The significance was evaluated as \* *P* < 0.05 and \*\* *P* < 0.01. Figure S5. Circus plots for plasma, adipose, kidney, small intestine, spleen, lung, muscle, and heart. Table S1. Details of fish-meal free F1 diet. Table S2. Details of untargeted lipidomics results. The false discovery rate (FDA) was corrected by Benjamini-Hochberg (BH) method, and the Q-value was also described. Table S3. Details of targeted lipidomics results. The false discovery rate (FDA) was corrected by Benjamini-Hochberg (BH) method, and the Q-value was also described.

**Author Contributions:** S.N. and M.A. designed the research. S.N. performed the experiments, and K.I. supported them. S.N. performed most of the data analysis for targeted lipidomics, and H.T. and M.T. performed the analysis for untargeted and targeted lipidomics. S.N., H.T., and M.A. primarily wrote the manuscript, and all authors approved the final manuscript.

**Funding:** This work was partially supported by JSPS KAKENHI (15H05897, 15H05898, 18H02432, 18K19155) and JST National Bioscience Database Center (NBDC).

**Acknowledgments:** We thank to Yuuya Senoo, Aya Hori, and Mie Honda (RIKEN) for LC-MS analyses, and Yasutaka Jinno and Hiroyuki Kawano (Mochida Pharmaceutical Co.) for study supports.

**Conflicts of Interest:** Part of this study was funded by Mochida Pharmaceutical Co., Ltd., which S.N. belongs to Mochida Pharmaceutical Co. was in charge of animal experiments.
