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Nrf2-mediated Antioxidant Defense and 6 are Linked to Biosynthesis of

Palmitic Acid Ester of 9-Hydroxystearic Acid

running title PAHSA biosynthetic pathway

Ondrej Kuda*1, Marie Brezinova1, Jan Silhavy1, Vladimir Landa1, Vaclav Zidek1, Chandra

Dodia2, Franziska Kreuchwig3, Marek Vrbacky1, Laurence Balas4, Thierry Durand4, Norbert

Hübner3, Aron B. Fisher2, Jan Kopecky1 and Michal Pravenec1

1Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14220 Praha 4,

Czech Republic

2Institute for Environmental Medicine of the Department of Physiology, University of

Pennsylvania, Philadelphia, United States

3MaxDelbrückCenter for Molecular Medicine (MDC), Berlin, Germany; DZHK (German

Centre for Cardiovascular Research), Partner Site, Berlin, Germany; Charité

Universitätsmedizin, Berlin, Germany

4Institut des Biomolécules Max Mousseron (IBMM), UMR 5247, CNRS, Université Montpellier,

ENSCM, Faculté de Pharmacie, Montpellier Cedex 5, France

* Corresponding author:

Ondrej Kuda, Department of Adipose Tissue Biology, Institute of Physiology of the Czech

Academy of Sciences, Videnska 1083, 142 20 Prague, Czech Republic, Email:

[email protected], Telephone: +420 296443707, Fax: +420 296442599

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Diabetes Publish Ahead of Print, published online March 16, 2018 Diabetes Page 2 of 44

Abstract

Fatty acid esters of hydroxy fatty acids (FAHFAs) are lipid mediators with promising anti

diabetic and antiinflammatory properties that are formed in white adipose tissue (WAT) via de

novo lipogenesis, but their biosynthetic are unknown. Using a combination of lipidomics in WAT, QTL mapping and correlation analyses in rat BXH/HXB recombinant inbred strains, and response to oxidative stress in murine models, we elucidated the potential pathway of biosynthesis of several FAHFAs.

Comprehensive analysis of WAT samples identified ~160 regioisomers documenting the

complexity of this lipid class. The linkage analysis highlighted several members of Nuclear

factor, erythroid 2like 2 (Nrf2)mediated antioxidant defense system (Prdx6, Mgst1, Mgst3), lipidhandling (Cd36, Scd6, Acnat1, Acnat2, Baat) and family of Flavin Containing

Monooxygenase (Fmo) as the positional candidate . Transgenic expression of Nrf2 and deletion of Prdx6 genes resulted in reduction of palmitic acid ester of 9hydroxystearic acid (9

PAHSA) and 11PAHSA levels, while oxidative stress induced by an inhibitor of glutathione synthesis increased PAHSA levels nonspecifically.

Our results indicate that the synthesis of FAHFAs via carbohydrateresponsive elementbinding (ChREBP)driven de novo lipogenesis depends on the adaptive antioxidant system and suggest that FAHFAs may link activity of this system with insulin sensitivity in peripheral tissues.

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INTRODUCTION:

White adipose tissue (WAT) metabolism plays an important role in whole body energy balance.

Moreover, dysregulation of both glucose and lipid metabolism in this tissue underlies

development of disease associated with obesity and type 2 diabetes. However, the mechanistic

links between glucose and lipid metabolism in WAT of obese subjects and systemic insulin

resistance are not fully explored. De novo lipogenesis (DNL) converts excess energy from

carbohydrates to energydense neutral lipids both in the liver and WAT (14). Although DNL

in the liver is usually associated with systemic insulin resistance, DNL in WAT correlates

with insulin sensitivity (58) and besides generation of lipid stores, DNL might serve also as a

source of signaling molecules. Within the last decade, a number of bioactive lipids produced in

WAT (lipokines) via DNL have been described, including palmitoleate (7), alkyl etherlipids (9),

and fatty acid esters of hydroxy fatty acids (FAHFAs) (6), which all promote insulin sensitivity

and ameliorate insulin resistance. Namely FAHFAs represent a new immunometabolic link

between DNL in WAT and systemic metabolism due to multiple beneficial effects of these

extremely potent lipokines on both glucoseinsulin homeostasis and inflammation as observed in

insulinresistant mice as well as humans, while their reduced levels may contribute to diabetes

risk (6; 1012).

FAHFAs consist of a fatty acid (e.g. palmitic acid, PA) esterified to the hydroxyl group of a

hydroxy fatty acid (e.g. hydroxystearic acid, HSA), abbreviated as PAHSA, and the position of

the branching carbon defines a regioisomer (e.g. 9PAHSA). There are several regioisomer

families derived from palmitic (PA), palmitoleic (PO), stearic (SA), oleic (OA), linoleic (LA),

and docosahexaenoic (DHA) acid with tissuespecific distribution documented so far (6; 10; 11;

1315). WAT represents a major site of carbohydrateresponsive elementbinding protein

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dependent (ChREBP) FAHFA synthesis (6; 11; 16). Serine carboxyl ester lipase (17;

18) and threonine (19) were identified as FAHFAmetabolizing enzymes, but the biosynthetic enzymes involved are unknown (18). Given the low susceptibility of saturated acyl

chains to oxidation (20), the complexity of FAHFA family, and their stereospecific metabolism

(10; 21), a combination of nonenzymatic and enzymatic reactions is probably involved in

FAHFA biosynthesis. Although all FAHFAs are structurally related, they are probably biologically as heterogenous as eicosanoids – they are composed of different fatty acids and even

the regioisomers within one family respond differently to physiological stimulations (6; 11).

Therefore, there could be individual genes/proteins responsible for the differences among

regioisomers (substrate specificity towards the branching position and/or acyl chain) as well as

genes responsible for major regulation of the whole pathway (e.g. ChREBP (16)).

In this study, the BXH/HXB recombinant inbred (RI) strains, derived from the spontaneously

hypertensive rat (SHR) strain and the normotensive Brown Norway (BN) strain (22), were used

for linkage and correlational analyses of physiological traits, lipidomics data and expression

levels to investigate potential candidate genes involved in FAHFA biosynthesis.

MATERIALS AND METHODS

Materials and reagents

All chemicals were purchased from SigmaAldrich (Czech Republic) unless stated otherwise.

13 FAHFA standards (5,9,10,12,13PAHSA, OAHSA, SAHSA and C49PAHSA) were purchased from Cayman Pharma (Neratovice, Czech Republic) and 5,7,9,OAHPA, 7OAHSA,

5,7,9PAHPA and 13DHAHLA, 12DHAHOA synthesized as before (11; 13). PA, palmitic

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acid; PO, palmitoleic acid; SA, stearic acid; OA, oleic acid; LA, linoleic acid; AA, arachidonic

acid; DHA, docosahexaenoic acid; H prefix stands for hydroxy fatty acid.

Animals

BXH/HXB recombinant inbred (RI) strains (n=30) were derived from SHR/OlaIpcv (referred to

as the SHR) and BNLx/Cub (referred to as the BN) progenitor strains (22). Nuclear factor

erythroid 2related factor2 (Nrf2) transgenic SHR (23) (referred to as the SHRNrf2) were

derived by microinjecting SHR zygotes with the mix of Sleeping Beauty construct containing

mouse Nrf2 cDNA under control of the SV universal promoter and mRNA of the SB100X

transposase (23). Genotyping of positive rats was done by PCR with the following primers:

mNrf2413F: GCA ACT CCA GAA GGA ACA GG and mNrf2573R: AGG CAT CTT GTT

TGG GAA TG (23). All rats were housed in an airconditioned animal facility at 22 °C and

allowed free access to food and water. Lipidomic, biochemical, and metabolic phenotypes were

assessed in 6weekold 14hours fasted male rats that were raised on standard laboratory chow

(Altromin, Germany). Animals were killed by cervical dislocation in a fasted state (food

removed at 6 p.m., animals killed at 8 a.m. 9 a.m. next day) and samples of epididymal WAT

were stored in liquid nitrogen to prevent degradation until assay, as the samples from specific

strains were collected during a period of 6 months. To explore the interaction between metabolic

status and Nrf2, SHRNrf2 and SHR males (n=7) were fasted for 24 hours (9 a.m. – 9.a.m.)

following or not by refeeding chow for 6 hours, and WAT was dissected and stored as described

above; eventually metabolipidomic, proteomic, and FAHFA analyses were

performed as before (11; 24). Oral glucose tolerance test (OGTT) was performed using a glucose

load of 300 mg/100 g body weight after overnight fasting. Blood was drawn from the tail without

anesthesia before the glucose load (0 min time point) and at 30, 60, and 120 min thereafter. To

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characterize the role of redox status, sixteen C57BL/6J adult male mice (Jackson Laboratory,

ME, USA) were randomly divided into 2 groups: untreated mice or mice treated with buthionine sulfoximine (BSO), an inhibitor of glutathione (GSH) synthesis. BSO was supplied in drinking water at the final concentration of 20 mM for 3 days. All mice were fed standard laboratory chow (extruded ssniff R/MH from Ssniff Spezialdiaten GmbH, Germany). Animals were killed in randomfed state under ether anesthesia and epididymal WAT was dissected and stored in liquid nitrogen till the analysis. The experiments were conducted in agreement with the Animal

Protection Law of the Czech Republic and were approved by the Ethics Committee of the

Institute of Physiology, Czech Academy of Sciences, Prague.

Wild type C57BL/6J mice (Jackson Laboratory, ME, USA) and peroxiredoxin 6 (Prdx6) null mice on the C57BL/6J background (25) were maintained and killed similarly as in the experiments above. Epididymal WAT of adult animals was dissected and stored at 80 °C till the analysis. Use of the mice was approved by the University of Pennsylvania Animal Care and Use

Committee. Thiobarbituric acid reactive substances and 8Isoprostane were measured using kits from Cayman chemicals (Ann Arbor, Michigan USA) (26).

FAHFA analysis

Analysis of FAHFAs was performed as before (10; 11) and optimized for a large set of samples.

Aliquots 5070 mg of WAT were homogenized using a MM400 bead mill (Retsch GmbH,

Germany) chilled to −20 °C in a mixture of citric acid buffer and ethyl acetate (27), and further

13 extracted with ethyl acetate (1:3 final ratio). An internal standard C49PAHSA was added to the homogenate (1 ng/sample). The organic phase was collected, dried in a Speedvac (Savant

SPD121P; Thermo), resuspended in dichloromethane and applied on HyperSep SPE columns

(500 mg/10 ml, 4060µm, 70Å, Thermo). FAHFAs were eluted from the SPE columns with ethyl

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acetate, concentrated using a Speedvac, resuspended in methanol and immediately analyzed

using liquid chromatographymass spectrometry (LCMS) as follows.

Chromatographic separation was performed in a UPLC Ultimate 3000 RSLC (Thermo) equipped

with a YMCTriart C18 ExRS 1.9 µm 2.1x150 mm column (YMC, Japan). The flow rate was

200 µl/min at 50 ºC using gradient elution: solvent A (70% water, 30% acetonitrile, 0.01% acetic

acid, pH 4), solvent B (50% acetonitrile, 50% isopropanol), for 1 min (100% solvent A), 5 min

(10% solvent A), 23 min (10% solvent A), 25 min (100% solvent A), while a linear gradient was

maintained between the steps. UPLC was coupled to a QTRAP 5500/SelexION mass

spectrometer (Sciex, Massachusetts, USA). FAHFAs were detected in negative electrospray

mode using MRM (Table S1) and MS/MS/MS as before (11).

Statistical Analyses

Linkage and correlation analyses of WAT FAHFA levels in BXH/HXB RI strains were

performed using Matrix eQTL (28) to identify QTLs at genomewide statistical significance at p

< 0.05 and FDR < 0.1. To identify the best candidate genes, we used biological knowledge

driven analysis using databases such as Rat Genome Database (rgd.mcw.edu) and PubMed.

Specifically, within each identified genomic position (± 3 Mbp), we have also searched for any

protein linked to (i) lipid metabolism and an ability to handle acyl chain, (ii) peroxidation or

oxidation of lipids, (iii) formation of reactive oxygen species based on data from RGD (accessed

November 21, 2017). Substrate specificity of candidate proteins and their potential relevance to

FAHFA metabolism was further explored via PubMed search for primary publications (gene or

protein name, accessed November 21, 2017). GeneNetwork database includes RI strains gene

expression data in tissues relevant to the pathogenesis of metabolic syndrome (kidney, left

ventricle, epididymal fat, brown fat, hippocampus, and liver) (29). In addition, the database also

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includes parameters of glucose and lipid metabolism and was used to explore a link of FAHFAs to these traits (30).

The data in transgenic rats and mouse experiments are expressed as means ± SEM. Statistical analysis was performed with SigmaStat. For most experiments, unpaired twotailed Student’s t test was used to determine statistical significance among two groups and p < 0.05 was considered significant. Twoway ANOVA was used for the refeeding experiment (Figure 5).

RESULTS

Targeted lipidomics of FAHFAs

The analysis of FAHFAs from WAT is complicated due to the fact that the two step lipid extraction is followed by a prolonged chromatography to separate the regioisomers. We tested several lipid extraction techniques to optimize the analysis. Maximal recovery of very hydrophobic FAHFAs was achieved with ethyl acetate and citrate buffer mixture (11; 27). The chromatographic separation of FAHFA regioisomers was optimized for PAHSAs using the C18 column with high carbon load and the final method allowed near baseline peak separation of

PAHSA regioisomers as well as regioisomers of other FAHFAs. Using the MS/MS/MS fragmentation patterns (11) and retention times of synthetic standards (11; 13), we were able to identify ~160 regioisomers of 49 FAHFA derived from 7 physiologically relevant fatty acids

(Table 1 and Figure S1). There were several other FAHFA regioisomers detected, but their identification wasn’t definitive due to low intensities and coelution.

FAHFA profiles

We analyzed WAT levels of FAHFA regioisomers in 30 RI and two progenitor strains.

Distribution of 9PAHSA, 12/13PAHSA (6), and 13DHAHLA (11) among BXH/HXB RI

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strains was continuous suggesting a polygenic inheritance. BN rats showed significantly reduced

levels of FAHFA regioisomers when compared to SHR rats (Figure 1).

Relationships of FAHFAs with parameters of lipid and glucose metabolism

The regioisomer 9PAHSA was shown to be involved in enhanced glucose uptake and insulin

sensitivity of peripheral tissues (6). The correlation between 9PAHSA trait and physiological

parameters of the BXH/HXB RI strains (30) confirmed that 9PAHSA levels were positively

associated with the difference between maximal and basal glucose uptake into collagenase

liberated adipocytes from WAT (Pearson r = 0.466; p = 0.0156; Figure S2), thus supporting the

beneficial effect of 9PAHSA on glucose homeostasis. Interestingly, isoproterenolinduced

lipolysis of isolated adipocytes (22) correlated with 9PAHSA trait (Pearson r = 0.415; p =

0.0341) suggesting that 9PAHSA augments also the capacity of lipid mobilization from WAT.

QTL mapping

Genomewide linkage analysis revealed several significant QTLs associated with FAHFA

regioisomers on 4, 5, 10, 13 and 15 at FDR < 0.1. These QTLs were divided into

four groups based on the chemical structure of associated FAHFAs (Table 2). The first group

comprises QTLs associated with PAHSA regioisomers. The strongest association was observed

for 12/13PAHSA with the peak of QTL linkage in the immediate vicinity of the Prdx6 as a

positional candidate gene on 13 (Figure 2). Other positional candidate genes

relevant to FAHFA metabolism were the Fmo family and Mgst3, and Mgst1 in case of 9PAHSA

trait. Additional potential QTL for group 1 was found on chromosome 12 near the marker

D12Rat10 in the proximity of the ChREBPcoding gene Mlxipl.

The second group comprised QTLs associated with SAHPA regioisomers, the inverse

combination of parental fatty acids from group 1, and PAHPA, the palmitic acid metabolite.

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Linkage analysis revealed positional candidate genes on chromosome 4 (Olr1, Mgst1), and chromosome 5 (Acnat1, Acnat2, Baat; see Table 2 for the full gene names). The third group included QTLs associated with FAHFAs with one and two double bonds (PAHOA and PAHLA) and QTL linkage revealed Fads6, Ptgs1, and Gpx7 as the positional candidate genes. The fourth group of polyunsaturated FAHFAs included Cd36 as the candidate gene for the chromosome 4

QTL.

Role of positional candidate genes in PAHSA metabolism

To limit the extent of the investigation, we focused our attention mainly on the possible role of the candidate genes in PAHSA metabolism. Candidate genes from groups 1 and 2 are all target genes for Nrf2 (31; 32), a transcription factor that exerts a complex control over the cellular redox status and lipid metabolism. Prdx6 codes for a GSH while Mgst1 and Mgst3 code for GSH S (31) and the activity for all 3 enzymes is sensitive to GSH depletion caused by BSO, an inhibitor of GSH synthesis. We treated mice by adding BSO to their drinking water (20 mM) for 3 days. Induction of oxidative stress by GSH depletion (Figure 3A) caused an increase in the levels of all three gene products (Figure 3B), increase of the markers for lipid peroxidation (Figure 3C) as well as an increase of 12/13, 11, 10, 9PAHSA (Figure 3D) suggesting that redox status and reactive oxygen species (ROS) scavenging are involved in

FAHFA biosynthesis.

Next, we focused on the involvement of Prdx6, which represents a strong candidate for

PAHSA biosynthesis as it possesses multiple lipidrelated enzymatic activities (33), is a Nrf2 targeted gene (32), and its role in the pathophysiology of type 2 diabetes has been reported (34).

The loss of Prdx6 did not affect gene expression of either Nfe2l2, Mlxipl, Mgst1,Mgst3, Cat,

Sod1-3, Prdx1-5 (Figure 4A) in agreement with previous data showing no compensatory

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expression of antioxidant enzymes (25) and no increase in lipid peroxidation (Figure S4). On the

contrary, levels of 11, 10 and 9PAHSA were significantly lower in WAT that had been

dissected from Prdx6 null mice as compared to wild type controls (Figure 4B), suggesting a

direct role of Prdx6 in the synthesis of the regioisomers.

To test directly the role of Nrf2 in PAHSA synthesis, we have used SHR and SHRNrf2

transgenic rats (Figure 5A). As expected, expression of Prdx6, Mgst1 and Mgst3 in epididymal

WAT of fasted rats was significantly higher in the SHRNrf2 animals, showing that chronic

activation of Nrf2 pathway leads to activation of antioxidant defense system in this model

(Figure 5B), but had no effect on 9 and 13hydroxyoctadecadienoic acids (9 and 13HODE),

the markers for lipid peroxidation (Figure 5C). Next, we aimed to characterize the effect of Nrf2

on FAHFA levels in WAT, depending also on the feeding status of the animals. Therefore, WAT

was dissected from SHR and SHRNrf2, either from fasted animals, or after refeeding the

animals chow diet. In the fasted state, levels of 13/12, 11, and 9PAHSA were reduced in

WAT from fasted SHRNrf2 as compared to SHR, while levels of 10 and 5PAHSA were not

different in the rats of the two genotypes. In accordance with the previous study in mice (6), in

the control SHR, levels of PAHSA decreased in response to the refeeding, however, no effect of

the refeeding was observed in SHRNrf2 (Figure 5D). Levels of 13PAHLA and 13LAHLA

showed that Nrf2 transgenic expression did not affect the synthesis of HLAderived FAHFAs,

while synthesis of HSAderived FAHFAs and response to refeeding was altered. These results

suggested involvement of mutual interactions between Nrf2 and feeding status in the modulation

of the PAHSAs levels in WAT.

The refeeding of rats chow diet should induce DNL in WAT, while glucose represents the most

common supply of carbon units for DNL and its availability might limit DNL in WAT.

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Quantification of the expression of the Glut4 (Slc2a4) gene at both transcript and protein level in

WAT indicated that Nrf2 transgenic expression counteracted chow dietmediated induction of the gene and, therefore, limited glucose availability during the refeeding period (Figure 5F). In fact, the refeeding response of all the genes critical for DNL in WAT that were in focus of our study (ChREBP, Acly, Acc1, Fasn) was dysregulated in SHRNrf2 (Figure 5G). Thus, while chow refeeding induced ChREBP alpha and beta expression in SHR, this effect was abrogated in SHRNrf2. The expression of the lipogenic genes (Acly, Acc1, Fasn) was significantly upregulated in SHR but not in SHRNrf2 in response to the chow refeeding. Levels of plasma glucose in the refeeding experiment (Figure 5H) and both glucose and insulin levels during

OGTT suggested that SHRNrf2 animal were insulinresistant.

Collectively, these results further document the complex interaction between Nrf2 and feeding status (see above), especially the negative influence of Nrf2 on lipogenesis and the paradoxical dissociation between the changes in activity of the DNL pathway and PAHSAs levels in WAT

(see also (6; 16), Fig. 6 and the Discussion).

DISCUSSION

The principal finding of this study was that biosynthesis of FAHFAs in WAT involved the adaptive Nrf2regulated antioxidant system. Therefore, our results further document that the defense against oxidative stress is interconnected, in a complex way, with DNL in WAT and suggest that FAHFAs may link activity of the adaptive antioxidant response in WAT with insulin sensitivity in peripheral tissues.

The comprehensive LCMS analysis of FAHFAs revealed the complexity of this lipid class. We have identified ~160 regioisomers combined of 7 FAs and 7 hydroxy FAs. The distribution of

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the branching positions among the hydroxy FAs suggests that the carbons in the middle of the

molecule, and preferentially in the vicinity of a double bond, are the primary targets for

oxidation. The chromatography was optimized for separation of PAHSAs, thus the separation of

other FAHFAs was not optimal and there might be other regioisomers that coelute. In general,

there are common branching patterns for saturated HPA and HSA, and monounsaturated HPO

and HOA. The hydroxyl position on polyunsaturated HLA and HDHA matched the common

enzymatic products (11), while the HAA branching at carbon 11 was unexpected. Importantly,

since the analysis does not recognize cis/trans double bond isomers, R/S enantiomers, or unusual

FAs, there might be more than ~300 FAHFA species. To limit the extent of the investigation, we

focused our attention mainly on PAHSAs.

The correlation between 9PAHSA trait and the parameters of adipocyte metabolism already

characterized in the BXH/HXB RI strains confirmed beneficial effects of PAHSAs on the

essential metabolic functions of WAT (6). The QTL analysis highlighted a pathway of Nrf2

target genes involved in antioxidative defense. Nrf2 mediates the crosstalk between lipid

metabolism, DNL, and antioxidant defense mechanisms in the liver and WAT (35; 36),

demonstrating that defense against oxidative stress is interconnected with lipogenesis (3; 37; 38).

Reduced levels of Nrf2 were associated with the development of oxidative stress, redox status

disbalance and diabetic complications including cardiomyopathy, nephropathy, retinopathy, foot

ulceration and microangiopathy in patients and mice (35; 39). Transient activation of the Nrf2

system by naturally occurring compounds, such as plant polyphenols, results in raising

antioxidant levels and may explain the beneficial metabolic effects of these micronutrients (37;

39; 40). Moreover, there is synergistic induction of lipid catabolism and antiinflammatory

lipids in WAT and reduction of adiposity in mice with induced obesity, in response to the

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combined intervention using calorie restriction and n3 fatty acids that correlates with an

increase in WAT levels of 15dPGJ2, the lipid signaling mediator that stimulates the Nrf2 system

(41; 42). Therefore, the ChREBPNrf2FAHFAs axis may be involved in beneficial effects of

various (micro)nutrients on metabolic health and insulin sensitivity and contribute to

amelioration of diabetic complications. This important possibility should be explored in the

future.

The positional candidate genes related to lipid metabolism include the Fmo family linked to production of ROS (11; 43; 44), four enzymes with activity scavenging phospholipid hydroperoxides (4548) (different from seleniumcontaining phospholipid

hydroperoxidase Gpx4), and peroxisomal acyltransferases (49). Although the Fmo family

catalyzes preferentially oxygenation of heteroatoms (44), Fmo forms a stable 4ahydroperoxy

FAD intermediate, which can serve as a source of hydrogen peroxide for lipid peroxidation (43).

The four identified antioxidative enzymes (Prdx6, Gpx7, Mgst1, Mgst3) exert peroxidase

activity with phospholipid hydroperoxides as substrates (4548), while Prdx6 possesses also phospholipase A2, and lysophosphatidylcholine acyltransferase activities, respectively. These

enzymes can thus produce a phospholipid with a hydroxy FA or even cleave this hydroxy FA in

the case of Prdx6. The family of peroxisomal acyltransferases (Baat, Acnat1, Acnat2) conjugate

long and verylong chain saturated acylCoAs to taurine or glycine, but complete substrate

specificity has not yet been identified (49). Thus, it might be possible that they can esterify the

hydroxy FA with saturated acylCoA as the known acyltransferases are not involved (18). Of

note, FAHFAs were identified as the products of DNL in WAT, which relies on NADPH production to drive the lipogenesis. Therefore, the NADPH can serve for both fatty acid

elongation and glutathionedisulfide reductase reaction.

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We demonstrated in this study that the inhibition of GSH synthesis by BSO resulted in uniformly

elevated PAHSA levels and deletion of Prdx6 decreased PAHSA levels. This suggests that lipid

peroxidation under elevated oxidative stress conditions, glutathione and a reduction

of hydroperoxy phospholipids are involved in formation of HSA. Heterogeneous reduction or

elevation of PAHSA regioisomers might be related to either the incidence of peroxidation at

specific carbon sites (see below), substrate specificity of an acyltransferase, or to preferential

degradation of some regioisomers (e.g. 12 and 13PAHSA (19)). A previous report (34)

documented that Prdx6 null mice develop a phenotype similar to earlystage type 2 diabetes

manifested as increased insulin resistance of peripheral tissues, decreased insulin secretion, and

systemic inflammation. The present results with Prdx6 null mice indicating decreased levels of

9PAHSA complement the original description of PAHSAs (6) as lipids with potent antidiabetic

and antiinflammatory activities.

Unexpectedly, the overexpression of Nrf2 accompanied by the increased expression of cellular

antioxidant defense genes led to lower or unchanged PAHSA levels. This discrepancy could be

explained by the dysregulation of the ChREBPdependent DNL pathway. While chronic

stimulation of the Nrf2 pathway might supply more hydroxy FA, reduction of de novo

synthesized palmitate limits the rate of PAHSA synthesis. Therefore, it seems plausible that the

fine tuning of enzymatic and nonenzymatic cellular antioxidant defenses and coordination with

the DNL pathway is needed for FAHFA synthesis and that substrate specificity of peroxidases

might play a role in the synthesis of individual regioisomers. We have confirmed the observation

by the group of B. Kahn (6), that changes in the activity of DNL due to feeding status do not

correlate with the changes of PAHSA levels in WAT, in spite of the essential role of the

ChREBPDNL axis in the formation of PAHSA in WAT (16). Also, genetic activation of Nrf2 in

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mice led to a repression of both hepatic and WAT lipogenesis (38; 50). Therefore, we

hypothesize that formation of new FA due to DNL activity is essential for formation of PAHSA, but the rate of PAHSA formation is controlled by other mechanism that involves remodeling of

membrane phospholipid hydroperoxides, as described below (see also Fig. 6). Given the

diversity of the FAHFA class, it is plausible that other pathways are also involved in the

synthesis of various FA combinations, regioisomers and enantiomers. The critical step seems to be the synthesis of the parental hydroxy FA. In the case of unsaturated FAs, enzymatic and non

enzymatic oxygenation follows the known pathways (e.g. 13HLA, 12HOA as major

regioisomers). The (poly)unsaturated FAHFAs (13AAHLA, 13DHAHLA) are associated with

genes related to desaturation (Scd6) and to scavenging of oxidized lipids (Cd36) and might be

involved in the immunometabolic crosstalk within WAT (1; 12).

Based on the current knowledge, we propose a pathway for 9PAHSA biosynthesis (Figure 6).

Glucose is converted to citrate and further to palmitate in WAT via the DNL pathway, which

might be controlled by a cascade of: (i) target of rapamycin complex 2 (mTORC2) (3); (ii)

ChREBPβ (3; 5); (iii) Nrf2; and (iv) Nrf2targets like Prdx6. Membrane phospholipids can be

randomly oxidized by ROS or phospholipid precursors can be synthesized via DNL (9) and

enzymatically oxidized. Although the spontaneous (per)oxidation of saturated stearic acid is less

likely compared to polyunsaturated FAs, the Fmo family is linked to ROS production and the

family substrate specificity has not yet been completely identified (43; 44). Also, the peroxidation of palmitate was located preferentially at the center of the molecule (20), similar to

PAHSA regioisomer distribution. Phospholipid hydroperoxide can form various types of lipid peroxidation products (malondialdehyde, 4hydroxynonenal, glyoxal, etc.) or can be reduced by

enzymes with GSH peroxidase or activity (Prdx6, Mgst1, Mgst3) to a phospholipid

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with hydroxy acyl chain. This reaction is dependent on cellular redox state and probably

controlled via an Nrf2 master regulator. The hydroxy FA is usually cleaved through an oxidized

phospholipid membrane remodeling process (e.g. Prdx6 PLA2 activity) and the free hydroxy FA

can be esterified with acylCoA by acyltransferase (probably via Baat, Acnat1, Acnat2; (18)) as

was shown in HEK293T cells (21). The final esters are eventually degraded by serine and

threonine hydrolases (17; 19).

The future challenge will be to validate the identified positional candidate genes to delineate the

role for individual FAHFAs in lipid and glucose metabolism, and to establish the role of these

novel lipokines in the defense against diabetesinduced oxidative stress and associated

complications such as diabetic cardiomyopathy and nephropathy. Also the identification of

potential phospholipid intermediates in FAHFA synthesis and detailed structural characterization

of FAHFA regioisomers will be needed in order to identify specific receptors and signaling

pathways. Elucidation of the involvement of the ChREBPNrf2FAHFAs axis in the beneficial

health effects of various micronutrients could help in prevention and treatment of obesity

associated diseases.

Acknowledgments

This work was supported by grants from the Czech Science Foundation (GA1604859S and

GJ1710088Y) and Ministry of Education, Youth and Sports of the Czech Republic

(LTAUSA17173). This publication is supported by the project „BIOCEV – Biotechnology and

Biomedicine Centre of the Academy of Sciences and Charles University“

(CZ.1.05/1.1.00/02.0109), from the European Regional Development Fund.“ The Proteomic core

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facility, BIOCEV, Charles University in Prague is acknowledged for the proteomic measurements.

Conflict of interest: The authors declare no conflicts of interest.

Author contributions

OK, MB, CD, VL, VZ and JS performed the animal studies, OK and MB performed the lipid analysis, OK, FK and NH performed the statistical evaluation, MP, FK and JK performed the genetic analysis, OK and MV performed the proteomic study, LB and TD prepared FAHFA standards, JK, ABF, MP contributed to the discussion, OK designed the studies and wrote the manuscript. OK and MP are the guarantors of all data. ABF and CD thank Drs. Patrick Seale and

Jeff Ishibashi (University of Pennsylvania) for assistance with isolation of WAT from mice.

References

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Tables

Table 1: The number of regioisomers in the corresponding FAHFA family

HPA HPO HSA HOA HLA HAA HDHA

PA 6 4 7 4 2 1 2

PO 6 4 8 4 2 1 2

SA 4 4 6 4 2 1 2

OA 6 4 6 4 2 1 2

LA 6 4 8 4 2 1 2

AA 6 4 5 4 2 1 2

DHA 4 2 3 4 2 1 2

Table 2: Positional candidate genes in FAHFA metabolism Trait QTL range (Mb) p value FDR RGD ID Symbol Group 1 9PAHSA 4: 161.8 161.8 < 0.00003 < 0.047 70927 Mgst1 12/13 PAHSA 13: 78.9 85.4 < 0.00017 < 0.058 71005 Prdx6 Fmo family 1306373 Mgst3

Group 2 8PAHPA 4: 159.9 167.2 < 0.00014 < 0.081 620515 Olr1

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70927 Mgst1 11/12 SAHPA 4: 181.5 181.5 < 0.00049 < 0.083 11/12 SAHPA 5: 25.8 66.5 < 0.00074 < 0.089 1584701 Acnat1 1359532 Acnat2 2190 Baat 11/12 SAHPA 15: 25.8 26.3 < 0.00068 < 0.089

Group 3 12SAHOA 3: 136.4 155.3 < 0.00025 < 0.086 3439 Ptgs1 8OAHOA 5: 130.6 130.6 < 0.00002 < 0.034 1306999 Gpx7 9PAHOA 10: 104.7 107.7 < 0.00003 < 0.012 1311950 Fads6 13PAHLA 10: 104.7 107.7 < 0.00008 < 0.028 1311950 Fads6

Group 4 13AAHLA 4: 0.1 14.6 < 0.00022 < 0.092 2301 Cd36

Acnat1, acylcoenzyme A amino acid Nacyltransferase 1; Acnat2, acylcoenzyme A amino acid

Nacyltransferase 2; Baat, bile acid CoA:amino acid Nacyltransferase; Cd36, CD36 molecule;

Fads6, fatty acid desaturase 6; Fads6, fatty acid desaturase 6; Fmo family, flavin containing monooxygenases; Gpx7, glutathione peroxidase 7; Mgst1, microsomal glutathione Stransferase

1; Mgst1, microsomal glutathione Stransferase 1; Mgst3, microsomal glutathione Stransferase

3; Olr1, oxidized low density lipoprotein receptor 1; Prdx6, peroxiredoxin 6; Ptgs1, prostaglandinendoperoxide synthase 1.

Figure legends

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Figure 1 – Distribution of FAHFAs among RI strains. A: structure of 9PAHSA; B: Levels of

9PAHSA, 12/13PAHSA, and 13DHAHLA in epididymal WAT of RI strains. 12 and 13

PAHSA levels are reported together due to separation issues (6). Values are expressed as

medians and progenitor strains highlighted as empty bars, n=56.

Figure 2 – Linkage analysis of 12-/13-PAHSA on chromosome 13. Manhattan plot of 12/13

PAHSA trait. Mapping of 12/13PAHSA trait on chromosome 13. FDR, false discovery rate.

Positional candidate genes Prdx6 and Fmo family are highlighted in red.

Figure 3 – Effect of glutathione synthesis inhibition on PAHSAs. C57BL6/J control mice and

mice treated with BSO. A: GSH levels in epididymal WAT; B: Gene expression in epididymal

WAT; C: Levels of 9 and 13hydroxyoctadecenoid acids (HODE, HLA) in WAT. D:

Epididymal WAT levels of PAHSA regioisomers. Data are expressed as means ± standard error,

n=8, * significantly different at p<0.05.

Figure 4 – Effect of Prdx6 knockout on PAHSAs in WAT. C57BL6/J WT mice and Prdx6 null

mice. A: Expression of relevant genes in WAT. Nfe2l2, Nuclear factor (erythroidderived 2)like

2 [Nrf2]; Mlxipl, MLXinteracting proteinlike [ChREBP]; Mgst, Microsomal glutathione S

transferase; Cat, ; Sod, superoxide dismutase; Prdx, Peroxiredoxin. B: Levels of PAHSA

in WAT. 5PAHSA levels were not determined. Data are expressed as means ± standard error,

n=5, * significantly different at p<0.05.

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Figure 5 – Effect of Nrf2 overexpression on DNL in WAT. SHR WT and SHRNfr2 transgenic

rats were fasted for 24 hours and either sacrificed or refed chow for 6 hours. A: Transgenic

expression of murine Nrf2 in WAT; B: Expression of positional candidate genes; C: Levels of 9 and 13hydroxyoctadecenoid acids (HODE, HLA) in WAT; D: Levels of PAHSA regioisomers;

E: Levels of HLAderived FAHFAs; F: Gene expression and protein levels (MS label free quantitation) of Glut4 (Slc2a4); G: Gene expression of DNL pathway, Acly, ATP citrate ;

Acc1. AcetylCoA carboxylase; Fasn, fatty acid synthase; H: Plasma glucose levels. Data are expressed as means ± standard error, n=7, fold change over SHR fasted group. I: Oral glucose tolerance test (OGTT). Blood glycaemia and insulin levels during the OGTT. Data are expressed as means ± standard error, n=1011. * ttest: significantly different at p<0.05. 2way ANOVA /

HolmSidak test: (i) statistically significant interaction between genotype and nutritional state at p < 0.05; f, significantly different nutritional state p < 0.05; g, significantly different genotype p

< 0.05.

Figure 6 – Proposed scheme for PAHSA synthesis. DNL from glucose to palmitate is controlled by ChREBP. Membrane phospholipids (PhL) are oxidized to phospholipid hydroperoxide (PhLOOH), which is further converted to a phospholipid with the hydroxy fatty acid (PhLOH) via glutathionedependent peroxidases. Hydroxy FA (hydroxy stearic acid) is liberated from the PhLOH and subsequently coupled to acylCoA coming from DNL pathway, yielding a PAHSA, which can be later degraded by specific hydrolases. While DNL from glucose is an essential prerequisite for PAHSA synthesis, Nrf2 overexpression limits the DNL pathway. Therefore, it seems plausible that fine tuning of enzymatic and nonenzymatic cellular antioxidant defenses and coordination with the DNL pathway is needed for PAHSA synthesis

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and that substrate specificity of peroxidases/phospholipases might play a role in the synthesis of

individual regioisomers.

Additional information

Supplementary Material accompanies this paper at …

Competing financial interests:

The authors declare no competing financial interests.

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Figure 1 – Distribution of FAHFAs among RI strains. A: structure of 9-PAHSA; B: Levels of 9-PAHSA, 12-/13- PAHSA, and 13-DHAHLA in epididymal WAT of RI strains. 12- and 13-PAHSA levels are reported together due to separation issues (6). Values are expressed as medians and progenitor strains highlighted as empty bars, n=5-6.

89x141mm (300 x 300 DPI)

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Figure 2 – Linkage analysis of 12-/13-PAHSA on chromosome 13. Manhattan plot of 12-/13-PAHSA trait. Mapping of 12-/13-PAHSA trait on chromosome 13. FDR, false discovery rate. Positional candidate genes Prdx6 and Fmo family are highlighted in red.

180x134mm (300 x 300 DPI)

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Figure 3 – Effect of glutathione synthesis inhibition on PAHSAs. C57BL6/J control mice and mice treated with BSO. A: GSH levels in epididymal WAT; B: Gene expression in epididymal WAT; C: Levels of 9- and 13- hydroxyoctadecenoid acids (HODE, HLA) in WAT. D: Epididymal WAT levels of PAHSA regioisomers. Data are expressed as means ± standard error, n=8, * significantly different at p<0.05.

179x51mm (300 x 300 DPI)

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Figure 4 – Effect of Prdx6 knockout on PAHSAs in WAT. C57BL6/J WT mice and Prdx6 null mice. A: Expression of relevant genes in WAT. Nfe2l2, Nuclear factor (erythroid-derived 2)-like 2 [Nrf2]; Mlxipl, MLX- interacting protein-like [ChREBP]; Mgst, Microsomal glutathione S-transferase; Cat, catalase; Sod, superoxide dismutase; Prdx. Peroxiredoxin. B: Levels of PAHSA in WAT. 5-PAHSA levels were not determined. Data are expressed as means ± standard error, n=5, * significantly different at p<0.05.

180x54mm (300 x 300 DPI)

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Figure 5 – Effect of Nrf2 overexpression on DNL in WAT. SHR WT and SHR-Nfr2 transgenic rats were fasted for 24 hours and either sacrificed or re-fed chow for 6 hours. A: Transgenic expression of murine Nrf2 in WAT; B: Expression of positional candidate genes; C: Levels of 9- and 13-hydroxyoctadecenoid acids (HODE, HLA) in WAT; D: Levels of PAHSA regioisomers; E: Levels of HLA-derived FAHFAs; F: Gene expression and protein levels (MS label free quantitation) of Glut4 (Slc2a4); G: Gene expression of DNL pathway, Acly, ATP citrate lyase; Acc1. Acetyl-CoA carboxylase; Fasn, fatty acid synthase; H: Plasma glucose levels. Data are expressed as means ± standard error, n=7, fold change over SHR fasted group. I: Oral glucose tolerance test (OGTT). Blood glycemia and insulin levels during the OGTT. Data are expressed as means ± standard error, n=10-11. * t-test: significantly different at p<0.05. 2-way ANOVA / Holm-Sidak test: (i) statistically significant interaction between genotype and nutritional state at p < 0.05; f, significantly different nutritional state p < 0.05; g, significantly different genotype p < 0.05.

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Figure 6 – Proposed scheme for PAHSA synthesis. DNL from glucose to palmitate is controlled by ChREBP. Membrane phospholipids (PhL) are oxidized to phospholipid hydroperoxide (PhL-OOH), which is further converted to a phospholipid with the hydroxy fatty acid (PhL-OH) via glutathione-dependent peroxidases. Hydroxy FA (hydroxy stearic acid) is liberated from the PhL-OH and subsequently coupled to acyl-CoA coming from DNL pathway, yielding a PAHSA, which can be later degraded by specific hydrolases. While DNL from glucose is an essential prerequisite for PAHSA synthesis, Nrf2 overexpression limits the DNL pathway. Therefore, it seems plausible that fine tuning of enzymatic and non-enzymatic cellular antioxidant defenses and coordination with the DNL pathway is needed for PAHSA synthesis and that substrate specificity of peroxidases/phospholipases might play a role in the synthesis of individual regioisomers.

180x60mm (300 x 300 DPI)

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Nrf2-mediated Antioxidant Defense and Peroxiredoxin 6 are Linked to Biosynthesis of Palmitic Acid Ester of 9-Hydroxystearic Acid

Content:

Figure S1 - Chromatographic profiles of FAHFAs

Figure S2 - Correlations between 9-PAHSA trait and physiological parameters of the BXH/HXB RI strains

Figure S3 - Manhattan plots of FAHFA traits

Figure S4 – Lipid peroxidation in WT and Prdx6 null WAT

Table S1 – Optimized MS parameters for FAHFA measurement

Table S2: QTL associated with FAHFA traits

Figure S1 - Chromatographic profiles of FAHFAs. Epididymal adipose tissue samples were extracted and separated on YMC-Triart C18 ExRS 1.9 µm 2.1x150 mm column. Illustrative profiles for HAA and HDHA regioisomers were acquired from mice fed omega-3 PUFA rich diet (1; 2). PA, palmitic acid; PO, palmitoleic acid; SA, stearic acid; OA, oleic acid; LA, linoleic acid; AA, arachidonic acid; DHA, docosahexaenoic acid; H- prefix denotes hydroxy fatty acid.

In case of HPO and HOA, limited information on the position of double bond was acquired based on the MS/MS/MS spectra. Supposed configuration: 9-HPO and 9-HOA: Δ10; 10-HPO and 10-HOA: Δ8; 11-, 12-HPO and 11-, 12-HOA: Δ9;

Diabetes Page 38 of 44 Figure S1- chromatographic profiles of FAHFAs HPA HPO HSA HOA HLA HAA HDHA

PAHPA PAHPO PAHSA PAHOA PAHLA PAHAA PAHDHA 9- 9- 11/10- 11- 11-13/12- 13- 17- 10- 9- 13/12- 5- 11- 10- 14- 8- 7- 12- 5- 9- 8- 12- 9- Intensity (cps) 13 14 15 16 17 9 10 11 12 13 14 15 16 16 17 18 19 20 21 12 13 14 15 16 17 10 11 12 13 14 15 10 11 12 13 14 15 9 10 11 12 13 14

POHPA POHPO POHSA POHOA POHLA POHAA POHDHA 9- 7- 11- 10- 9- 11/10- 13- 11- 13/12- 13/12- 7- 17- 8- 9- 11- 9- 5- 10- 8- 5- 12- 14-

Intensity (cps) 12- 11 12 13 14 15 16 9 10 11 12 13 14 15 16 13 14 15 16 17 18 11 12 13 14 15 16 10 11 12 13 14 15 10 11 12 13 14 15 8 9 10 11 12 13

SAHPA SAHPO SAHSA SAHOA SAHLA SAHAA SAHDHA 10- 13- 11- 9- 13/12- 11/10- 17- 9- 12/11- 10- 13/12- 11- 8- 9- 8- 12- 14-

Intensity (cps) 9- 9- 15 16 17 18 19 20 14 15 16 17 18 20 21 22 23 24 25 15 16 17 18 19 20 13 14 15 16 17 18 13 14 15 16 17 18 9 10 11 12 13 14

OAHPA OAHPO OAHSA OAHOA OAHLA OAHAA OAHDHA 11/10- 7- 10- 13- 11- 12/11- 17- 10 13/12- 11- 9- 13/12- 9- 14- 5- 9- 9- 8- 12- 9- Intensity (cps) 8-

13 14 15 16 17 9 10 11 12 13 14 15 16 15 16 17 18 19 20 12 13 14 15 16 17 10 11 12 13 14 15 10 11 12 13 14 15 9 10 11 12 13 14

LAHPA LAHPO LAHSA LAHOA LAHLA LAHAA LAHDHA 10- 9- 7- 9- 11/10- 13- 11- 17- 11- 7- 14- 8- 11- 8- 13/12- 9- 13/12- 10- 5- 9- 5- 12- 12- Intensity (cps)

11 12 13 14 15 16 9 10 11 12 13 14 15 16 13 14 15 16 17 18 11 12 13 14 15 16 10 11 12 13 14 15 10 11 12 13 14 15 9 10 11 12 13 14

AAHPA AAHPO AAHSA AAHOA AAHLA AAHAA AAHDHA 7- 9- 13- 10- 11/10- 11- 13/12- 17- 9- 12/11- 13/12- 8- 5- 9- 9- 14- 8- 12- 9- Intensity (cps) 10-

11 12 13 14 15 9 10 11 12 13 14 15 16 12 13 14 15 16 17 10 11 12 13 14 15 10 11 12 13 14 15 10 11 12 13 14 15 8 9 10 11 12 13

DHAHPA DHAHPO DHAHSA DHAHOA DHAHLA DHAHAA DHAHDHA 10- 11- 9- 11/10- 13- 17/14- 13/12- 9- 8- 9- 10- 8- 9-

Intensity (cps) 12- 9-

9 10 11 12 13 14 9 10 11 12 13 14 9 10 11 12 13 14 9 10 11 12 13 14 9 10 11 12 13 14 9 10 11 12 13 14 8 9 10 11 12 13 Time (min) Time (min) Time (min) Time (min) Time (min) Time (min) Time (min)

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Figure S2 – Correlations between 9-PAHSA trait and physiological parameters of the BXH/HXB RI strains. Difference between maximal and basal glucose uptake into collagenase-liberated adipocytes and isoproterenol-induced lipolysis of isolated adipocytes plotted versus 9-PAHSA trait levels. Physiological data acquired from GeneNetwork (3).

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Figure S3 – Manhattan plots of FAHFA traits

Dash line defines FDR threshold.

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Figure S4 - Lipid peroxidation in wild type and Prdx6 null WAT. Levels of thiobarbituric acid reactive substances (TBARS) and 8-isoprostanes in WAT dissected from wild type and Prdx6 null mice. Data are expressed as means ± standard error, n=3.

Table S1 – Optimized MS parameters for FAHFA measurement

Q1, precursor ion; Q3 product ion; DP, declustering potential; CE, collision energy.

- ID Q1 [M-H] Q3 FA Q3 HFA Q3 HFA-H2O DP CE PAHPO 507.4 255.2 269.2 251.2 -130 -35 PAHPA 509.4 255.2 271.2 253.2 -130 -35 PAHLA 533.4 255.2 295.2 277.2 -130 -35 PAHOA 535.4 255.2 297.2 279.2 -130 -35 PAHSA 537.5 255.2 299.3 281.3 -130 -35 PAHAA 557.4 255.2 319.2 301.2 -130 -35 PAHDHA 581.4 255.2 343.2 325.2 -130 -35 POHPO 505.4 253.2 269.2 251.2 -130 -35 POHPA 507.4 253.2 271.2 253.2 -130 -35 POHLA 531.4 253.2 295.2 277.2 -130 -35 POHOA 533.4 253.2 297.2 279.2 -130 -35 POHSA 535.5 253.2 299.3 281.3 -130 -35 POHAA 555.4 253.2 319.2 301.2 -130 -35 POHDHA 579.4 253.2 343.2 325.2 -130 -35 LAHPO 531.4 279.2 269.2 251.2 -130 -35 LAHPA 533.4 279.2 271.2 253.2 -130 -35 LAHLA 557.4 279.2 295.2 277.2 -130 -35 LAHOA 559.4 279.2 297.2 279.2 -130 -35 LAHSA 561.5 279.2 299.3 281.3 -130 -35 LAHAA 581.4 279.2 319.2 301.2 -130 -35 LAHDHA 605.4 279.2 343.2 325.2 -130 -35 OAHPO 533.4 281.2 269.2 251.2 -130 -35 OAHPA 535.4 281.2 271.2 253.2 -130 -35 OAHLA 559.4 281.2 295.2 277.2 -130 -35 OAHOA 561.4 281.2 297.2 279.2 -130 -35 OAHSA 563.5 281.2 299.3 281.3 -130 -35 OAHAA 583.4 281.2 319.2 301.2 -130 -35 OAHDHA 607.4 281.2 343.2 325.2 -130 -35 Diabetes Page 42 of 44

SAHPO 535.5 283.3 269.2 251.2 -130 -35 SAHPA 537.5 283.3 271.2 253.2 -130 -35 SAHLA 561.5 283.3 295.2 277.2 -130 -35 SAHOA 563.5 283.3 297.2 279.2 -130 -35 SAHSA 565.6 283.3 299.3 281.3 -130 -35 SAHAA 585.5 283.3 319.2 301.2 -130 -35 SAHDHA 609.5 283.3 343.2 325.2 -130 -35 AAHPO 555.4 303.2 269.2 251.2 -130 -35 AAHPA 557.4 303.2 271.2 253.2 -130 -35 AAHLA 581.4 303.2 295.2 277.2 -130 -35 AAHOA 583.5 303.2 297.2 279.2 -130 -35 AAHSA 585.5 303.2 299.3 281.3 -130 -35 AAHAA 605.4 303.2 319.2 301.2 -130 -35 AAHDHA 629.4 303.2 343.2 325.2 -130 -35 DHAHPO 579.4 327.2 269.2 251.2 -130 -35 DHAHPA 581.4 327.2 271.2 253.2 -130 -35 DHAHLA 605.4 327.2 295.2 277.2 -130 -35 DHAHOA 607.5 327.2 297.2 279.2 -130 -35 DHAHSA 609.5 327.2 299.3 281.3 -130 -35 DHAHAA 629.4 327.2 319.2 301.2 -130 -35 DHAHDHA 653.4 327.2 343.2 325.2 -130 -35

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Table S2: QTL associated with FAHFA traits

SDP Trait Genomic Range p.value FDR beta t.stat beta_se ci_upper ci_lower SDPG_04161793548 X9.PAHSA 4-161793548-161793548 2.79E-05 0.046932635 -0.183081616 -5.07118007 0.036102369 -0.112320972 -0.25384226 SDPG_13071646655 X12.13.PAHSA 13-71646655-72510384 7.86E-05 0.044160896 0.25459247 4.678066316 0.054422587 0.36126074 0.1479242 SDPG_13078909101 X12.13.PAHSA 13-78909101-78909101 2.27E-05 0.019103329 0.257097403 5.149244016 0.049929155 0.354958547 0.159236259 SDPG_13080093944 X12.13.PAHSA 13-80093944-81219060 2.27E-05 0.019103329 0.257097403 5.149244016 0.049929155 0.354958547 0.159236259 SDPG_13081943244 X12.13.PAHSA 13-81943244-83733914 1.16E-04 0.048985049 0.242172951 4.529814791 0.053461998 0.346958468 0.137387434 SDPG_13083744138 X12.13.PAHSA 13-83744138-85418436 1.72E-04 0.057951633 0.24095815 4.381403448 0.054995654 0.348749632 0.133166667 SDPG_04159937580 X8.PAHPA 4-159937580-160514422 1.44E-04 0.081157675 0.387286553 4.447458398 0.087080422 0.557964179 0.216608926 SDPG_04161793548 X8.PAHPA 4-161793548-161793548 1.28E-04 0.081157675 0.30195506 4.49200988 0.06722048 0.4337072 0.170202919 SDPG_04166069314 X8.PAHPA 4-166069314-167152491 1.21E-04 0.081157675 0.40117426 4.515841485 0.0888371 0.575294975 0.227053545 SDPG_10104672318 X9.PAHOA 10-104672318-104732023 3.46E-05 0.011661292 0.244878086 4.988902974 0.049084556 0.341083816 0.148672357 SDPG_10105504952 X9.PAHOA 10-105504952-105761650 1.42E-06 0.000797405 0.281542166 6.214339228 0.045305246 0.370340448 0.192743885 SDPG_10105769352 X9.PAHOA 10-105769352-105964319 4.28E-07 0.000360233 0.289369192 6.688007016 0.043266879 0.374172276 0.204566109 SDPG_10105969527 X9.PAHOA 10-105969527-106177758 1.92E-05 0.008071153 0.274516729 5.213220194 0.052657804 0.377726025 0.171307432 SDPG_10106181521 X9.PAHOA 10-106181521-107689156 1.09E-07 0.000184418 0.336331521 7.238509846 0.046464193 0.42740134 0.245261702 SDPG_10104672318 X13.PAHLA 10-104672318-104732023 4.93E-05 0.020777125 -0.227127602 -4.854631121 0.046785759 -0.135427514 -0.318827689 SDPG_10105504952 X13.PAHLA 10-105504952-105761650 3.35E-06 0.001880199 -0.258848927 -5.881068008 0.044013932 -0.17258162 -0.345116233 SDPG_10105769352 X13.PAHLA 10-105769352-105964319 1.35E-06 0.001752817 -0.264971881 -6.234736055 0.042499294 -0.181673265 -0.348270498 SDPG_10105969527 X13.PAHLA 10-105969527-106177758 8.42E-05 0.028374352 -0.243465606 -4.652136987 0.052334144 -0.140890684 -0.346040527 SDPG_10106181521 X13.PAHLA 10-106181521-107689156 2.08E-06 0.001752817 -0.296235071 -6.065372674 0.048840374 -0.200507937 -0.391962204 SDPG_05130556071 X8.OAHOA 5-130556071-130556071 2.01E-05 0.033818481 -0.35202829 -5.195582126 0.067755312 -0.219227878 -0.484828703 SDPG_04181531098 X11.12.SAHPA 4-181531098-181531098 4.95E-04 0.083348954 0.255805118 3.978345573 0.064299371 0.381831885 0.129778351 SDPG_05049742388 X11.12.SAHPA 5-49742388-50644238 1.42E-04 0.059882138 -0.324853563 -4.453654472 0.0729409 -0.1818894 -0.467817726 SDPG_05050656645 X11.12.SAHPA 5-50656645-52311164 4.62E-05 0.059882138 -0.345957452 -4.879582271 0.070898989 -0.206995433 -0.484919471 SDPG_05052356181 X11.12.SAHPA 5-52356181-54231285 1.42E-04 0.059882138 -0.324853563 -4.453654472 0.0729409 -0.1818894 -0.467817726 SDPG_05054244647 X11.12.SAHPA 5-54244647-54612807 6.90E-04 0.088995984 -0.294528395 -3.850330577 0.076494314 -0.14459954 -0.44445725 SDPG_05054633806 X11.12.SAHPA 5-54633806-54986141 3.42E-04 0.072021144 -0.307947307 -4.119700264 0.07474993 -0.161437444 -0.45445717 SDPG_05055867111 X11.12.SAHPA 5-55867111-57175062 3.42E-04 0.072021144 -0.307947307 -4.119700264 0.07474993 -0.161437444 -0.45445717 SDPG_05057202014 X11.12.SAHPA 5-57202014-60139253 6.90E-04 0.088995984 -0.294528395 -3.850330577 0.076494314 -0.14459954 -0.44445725 SDPG_05060214465 X11.12.SAHPA 5-60214465-60938429 3.42E-04 0.072021144 -0.307947307 -4.119700264 0.07474993 -0.161437444 -0.45445717 SDPG_05060988192 X11.12.SAHPA 5-60988192-62843226 7.39E-04 0.088995984 -0.29625819 -3.823565808 0.077482174 -0.144393129 -0.44812325 Diabetes Page 44 of 44

SDPG_05063114762 X11.12.SAHPA 5-63114762-63162152 1.32E-04 0.059882138 -0.323527813 -4.482585576 0.072174375 -0.182066038 -0.464989589 SDPG_05063164285 X11.12.SAHPA 5-63164285-63706439 2.89E-04 0.072021144 -0.310029409 -4.183880452 0.074100924 -0.164791597 -0.455267221 SDPG_05065239187 X11.12.SAHPA 5-65239187-66480071 4.80E-04 0.083348954 -0.3019751 -3.990091407 0.075681249 -0.153639853 -0.450310347 SDPG_15025754773 X11.12.SAHPA 15-25754773-26250248 6.84E-04 0.088995984 0.315493383 3.853577938 0.081870248 0.475959069 0.155027696 SDPG_03136383584 X12.SAHOA 3-136383584-136578961 2.54E-04 0.085539159 -0.220889599 -4.233348851 0.052178454 -0.118619829 -0.323159369 SDPG_03137777747 X12.SAHOA 3-137777747-139087656 5.88E-05 0.037890575 -0.232240547 -4.788105941 0.048503636 -0.137173421 -0.327307674 SDPG_03139108660 X12.SAHOA 3-139108660-150071378 1.43E-05 0.024072631 -0.249758886 -5.324873544 0.046904191 -0.157826672 -0.341691101 SDPG_03150844988 X12.SAHOA 3-150844988-151580802 6.75E-05 0.037890575 -0.241448801 -4.73605112 0.050981038 -0.141525967 -0.341371636 SDPG_03154833237 X12.SAHOA 3-154833237-155286618 1.41E-04 0.059311448 -0.22758677 -4.457286849 0.051059485 -0.12751018 -0.32766336 SDPG_04000102881 X13.AAHLA 4-102881-7774756 5.59E-05 0.046549713 0.547352104 4.807520437 0.113853308 0.770504587 0.324199621 SDPG_04007780467 X13.AAHLA 4-7780467-8821996 8.29E-05 0.046549713 0.524520465 4.658116847 0.112603544 0.745223411 0.303817519 SDPG_04008906412 X13.AAHLA 4-8906412-8940940 5.59E-05 0.046549713 0.547352104 4.807520437 0.113853308 0.770504587 0.324199621 SDPG_04013806614 X13.AAHLA 4-13806614-14635595 2.17E-04 0.091502059 0.50084549 4.292626971 0.116675754 0.729529969 0.272161012

FDR < 0.1 Upper Confidence Interval 95% = beta + 1.96 * beta_standard_error Lower Confidence interval 95% = beta - 1.96 * beta_standard_error

Page 45 of 44 Diabetes

Table S3: Gene names, symbols, abbreviations and qPCR primer sequences.

Rat

Gene Name Gene Symbol Forward primer Reverse primer Peroxiredoxin 6 Prdx6 GCTGGGCGAGCAGTTGCAG CAGTTGACTGGAAGAAGGGAGAGAG Microsomal Glutathione S-Transferase 1 Mgst 1 GCCAATGAAACCCAGGCTTCACAC CCATCCACAGGCTCTACCCTTTTGT Microsomal glutathione S-transferase 3 Mgst 3 TCCCGTTCCTCAGTGGCAGGA GGCTACTACACGGGAGACCCTAGC Solute carrier family 2 member 4 Glut 4 GGGTTTCCAGTATGTTGCGGATGC CCGGCCTCTGGTTTCAGGCA MLX interacting protein-like ChREBP total CTTGGAAACCTTCACCAGG TACTGTTCCCTGCCTGCTC ChREBP alpha AGGCTCAAGCATTCGAAGAG TGCATCGATCACAGGTCATT

ChREBP beta CTTGTCCCGGCATAGCAAC TCTGCAGATCGCGCGGAG

ATP citrate lyase Acly CCAGGCCCAGCCCATAACGG GGAGTATGGGCTTCATCGGGCA Acetyl-CoA carboxylase alpha Acc1 TGCCCAGTCGCTCAGCCAAG CGGGAAAGCAGGGGATCCGT Fatty acid synthase Fasn TCCCATCACACACCTGGGACA CTGGACCGCCGTGACCTGAG Peptidylprolyl A (cyclophilin A) Ppia AGCATACAGGTCCTGGCAT TCACCTTCCCAAAGACCAC

Murine

Gene Name Gene Symbol Forward primer Reverse primer Peroxiredoxin 6 Prdx6 TCGGAGAGGGTGGGAACTACC CAGTTGACTGGAAGAAGGGAGAGAG Microsomal Glutathione S-Transferase 1 Mgst 1 CCTGTTTGGCTGAGGAAGGGGA TGCGCAGAGCCCACCTGAATGA Microsomal glutathione S-transferase 3 Mgst 3 ACACGGTGGTGCCCATCAGG GGCTACTACACAGGAGACCCTAGCA Nuclear factor, erythroid derived 2, like 2 Nfe2l2 AAGGCTCCATCCTCCCGAACC CTGAAAAGGCGGCTCAGCACC MLX interacting protein-like Mlxipl ATCTTGGTCTTAGGGTCTTCAGG CACTCAGGGAATACAGCGCTAC Actin, beta Actb GAACCCTAAGGCCAACCGTGAAAAGAT ACCGCTCGTTGCCAATAGTGATG

Methods

References:

1. Kuda O, Brezinova M, Rombaldova M, Slavikova B, Posta M, Beier P, Janovska P, Veleba J, Kopecky J, Jr., Kudova E, Pelikanova T, Kopecky J: Docosahexaenoic Acid-Derived Fatty Acid Esters of Hydroxy Fatty Acids (FAHFAs) With Anti-inflammatory Properties. Diabetes 2016;65:2580-2590 2. Brezinova M, Kuda O, Hansikova J, Rombaldova M, Balas L, Bardova K, Durand T, Rossmeisl M, Cerna M, Stranak Z, Kopecky J: Levels of palmitic acid ester of hydroxystearic acid (PAHSA) are reduced in the breast milk of obese mothers. Biochim Biophys Acta 2017;1863:126-131 3. Aitman TJ, Gotoda T, Evans AL, Imrie H, Heath KE, Trembling PM, Truman H, Wallace CA, Rahman A, Dore C, Flint J, Kren V, Zidek V, Kurtz TW, Pravenec M, Scott J: Quantitative trait loci for cellular defects in glucose and fatty acid metabolism in hypertensive rats. Nat Genet 1997;16:197-201