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Nrf2-mediated Antioxidant Defense and Peroxiredoxin 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
3Max Delbrück Center 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, E mail:
[email protected], Telephone: +420 296443707, Fax: +420 296442599
1
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 anti inflammatory properties that are formed in white adipose tissue (WAT) via de
novo lipogenesis, but their biosynthetic enzymes 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 2 like 2 (Nrf2) mediated antioxidant defense system (Prdx6, Mgst1, Mgst3), lipid handling proteins (Cd36, Scd6, Acnat1, Acnat2, Baat) and family of Flavin Containing
Monooxygenase (Fmo) as the positional candidate genes. Transgenic expression of Nrf2 and deletion of Prdx6 genes resulted in reduction of palmitic acid ester of 9 hydroxystearic acid (9
PAHSA) and 11 PAHSA levels, while oxidative stress induced by an inhibitor of glutathione synthesis increased PAHSA levels nonspecifically.
Our results indicate that the synthesis of FAHFAs via carbohydrate responsive element binding protein (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 energy dense neutral lipids both in the liver and WAT (1 4). Although DNL
in the liver is usually associated with systemic insulin resistance, DNL in WAT correlates
with insulin sensitivity (5 8) 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 ether lipids (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 glucose insulin homeostasis and inflammation as observed in
insulin resistant mice as well as humans, while their reduced levels may contribute to diabetes
risk (6; 10 12).
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. 9 PAHSA). There are several regioisomer
families derived from palmitic (PA), palmitoleic (PO), stearic (SA), oleic (OA), linoleic (LA),
and docosahexaenoic (DHA) acid with tissue specific distribution documented so far (6; 10; 11;
13 15). WAT represents a major site of carbohydrate responsive element binding protein
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dependent (ChREBP) FAHFA synthesis (6; 11; 16). Serine hydrolase carboxyl ester lipase (17;
18) and threonine hydrolases (19) were identified as FAHFA metabolizing 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 non enzymatic 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 gene expression
levels to investigate potential candidate genes involved in FAHFA biosynthesis.
MATERIALS AND METHODS
Materials and reagents
All chemicals were purchased from Sigma Aldrich (Czech Republic) unless stated otherwise.
13 FAHFA standards (5 ,9 ,10 ,12 ,13 PAHSA, OAHSA, SAHSA and C4 9 PAHSA) were purchased from Cayman Pharma (Neratovice, Czech Republic) and 5 ,7 ,9 ,OAHPA, 7 OAHSA,
5 ,7 ,9 PAHPA and 13 DHAHLA, 12 DHAHOA 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 BN Lx/Cub (referred to as the BN) progenitor strains (22). Nuclear factor
erythroid 2 related factor 2 (Nrf2) transgenic SHR (23) (referred to as the SHR Nrf2) 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:
mNrf2 413F: GCA ACT CCA GAA GGA ACA GG and mNrf2 573R: AGG CAT CTT GTT
TGG GAA TG (23). All rats were housed in an air conditioned animal facility at 22 °C and
allowed free access to food and water. Lipidomic, biochemical, and metabolic phenotypes were
assessed in 6 week old 14 hours 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, SHR Nrf2 and SHR males (n=7) were fasted for 24 hours (9 a.m. – 9.a.m.)
following or not by re feeding chow for 6 hours, and WAT was dissected and stored as described
above; eventually metabolipidomic, proteomic, gene expression 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/M H from Ssniff Spezialdiaten GmbH, Germany). Animals were killed in random fed 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 8 Isoprostane 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 50 70 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 C4 9 PAHSA was added to the homogenate (1 ng/sample). The organic phase was collected, dried in a Speed vac (Savant
SPD121P; Thermo), resuspended in dichloromethane and applied on HyperSep SPE columns
(500 mg/10 ml, 40 60µm, 70Å, Thermo). FAHFAs were eluted from the SPE columns with ethyl
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acetate, concentrated using a Speed vac, resuspended in methanol and immediately analyzed
using liquid chromatography mass spectrometry (LC MS) as follows.
Chromatographic separation was performed in a UPLC Ultimate 3000 RSLC (Thermo) equipped
with a YMC Triart 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 genome wide 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 two tailed Student’s t test was used to determine statistical significance among two groups and p < 0.05 was considered significant. Two way 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 co elution.
FAHFA profiles
We analyzed WAT levels of FAHFA regioisomers in 30 RI and two progenitor strains.
Distribution of 9 PAHSA, 12/13 PAHSA (6), and 13 DHAHLA (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 9 PAHSA was shown to be involved in enhanced glucose uptake and insulin
sensitivity of peripheral tissues (6). The correlation between 9 PAHSA trait and physiological
parameters of the BXH/HXB RI strains (30) confirmed that 9 PAHSA 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 9 PAHSA on glucose homeostasis. Interestingly, isoproterenol induced
lipolysis of isolated adipocytes (22) correlated with 9 PAHSA trait (Pearson r = 0.415; p =
0.0341) suggesting that 9 PAHSA augments also the capacity of lipid mobilization from WAT.
QTL mapping
Genome wide linkage analysis revealed several significant QTLs associated with FAHFA
regioisomers on chromosomes 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 /13 PAHSA with the peak of QTL linkage in the immediate vicinity of the Prdx6 as a
positional candidate gene on chromosome 13 (Figure 2). Other positional candidate genes
relevant to FAHFA metabolism were the Fmo family and Mgst3, and Mgst1 in case of 9 PAHSA
trait. Additional potential QTL for group 1 was found on chromosome 12 near the marker
D12Rat10 in the proximity of the ChREBP coding 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 peroxidase while Mgst1 and Mgst3 code for GSH S transferases (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 , 9 PAHSA (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 enzyme for
PAHSA biosynthesis as it possesses multiple lipid related 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 9 PAHSA 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 SHR Nrf2
transgenic rats (Figure 5A). As expected, expression of Prdx6, Mgst1 and Mgst3 in epididymal
WAT of fasted rats was significantly higher in the SHR Nrf2 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 13 hydroxy octadecadienoic acids (9 and 13 HODE),
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 SHR Nrf2, either from fasted animals, or after re feeding the
animals chow diet. In the fasted state, levels of 13 /12 , 11 , and 9 PAHSA were reduced in
WAT from fasted SHR Nrf2 as compared to SHR, while levels of 10 and 5 PAHSA 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 re feeding, however, no effect of
the re feeding was observed in SHR Nrf2 (Figure 5D). Levels of 13 PAHLA and 13 LAHLA
showed that Nrf2 transgenic expression did not affect the synthesis of HLA derived FAHFAs,
while synthesis of HSA derived FAHFAs and response to re feeding was altered. These results
suggested involvement of mutual interactions between Nrf2 and feeding status in the modulation
of the PAHSAs levels in WAT.
The re feeding 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 diet mediated induction of the gene and, therefore, limited glucose availability during the re feeding period (Figure 5F). In fact, the re feeding response of all the genes critical for DNL in WAT that were in focus of our study (ChREBP, Acly, Acc1, Fasn) was dysregulated in SHR Nrf2 (Figure 5G). Thus, while chow re feeding induced ChREBP alpha and beta expression in SHR, this effect was abrogated in SHR Nrf2. The expression of the lipogenic genes (Acly, Acc1, Fasn) was significantly upregulated in SHR but not in SHR Nrf2 in response to the chow re feeding. Levels of plasma glucose in the re feeding experiment (Figure 5H) and both glucose and insulin levels during
OGTT suggested that SHR Nrf2 animal were insulin resistant.
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 Nrf2 regulated 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 LC MS 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 co elute. 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 9 PAHSA 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 anti oxidative 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 anti inflammatory
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 n 3 fatty acids that correlates with an
increase in WAT levels of 15d PGJ2, the lipid signaling mediator that stimulates the Nrf2 system
(41; 42). Therefore, the ChREBP Nrf2 FAHFAs 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 glutathione peroxidase activity scavenging phospholipid hydroperoxides (45 48) (different from selenium containing phospholipid
hydroperoxidase Gpx4), and peroxisomal acyltransferases (49). Although the Fmo family
catalyzes preferentially oxygenation of heteroatoms (44), Fmo forms a stable 4a hydroperoxy
FAD intermediate, which can serve as a source of hydrogen peroxide for lipid peroxidation (43).
The four identified anti oxidative enzymes (Prdx6, Gpx7, Mgst1, Mgst3) exert peroxidase
activity with phospholipid hydroperoxides as substrates (45 48), 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 very long chain saturated acyl CoAs 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 acyl CoA 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 glutathione disulfide 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 peroxidases 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 13 PAHSA (19)). A previous report (34)
documented that Prdx6 null mice develop a phenotype similar to early stage 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
9 PAHSA complement the original description of PAHSAs (6) as lipids with potent anti diabetic
and anti inflammatory 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 ChREBP dependent 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 non enzymatic 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
ChREBP DNL 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. 13 HLA, 12 HOA as major
regioisomers). The (poly)unsaturated FAHFAs (13 AAHLA, 13 DHAHLA) 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 9 PAHSA 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)
ChREBP β (3; 5); (iii) Nrf2; and (iv) Nrf2 targets 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, 4 hydroxynonenal, glyoxal, etc.) or can be reduced by
enzymes with GSH peroxidase or transferase 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 acyl CoA 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 diabetes induced 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 ChREBP Nrf2 FAHFAs 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 (GA16 04859S and
GJ17 10088Y) 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.
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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 9 PAHSA 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 8 PAHPA 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 12 SAHOA 3: 136.4 155.3 < 0.00025 < 0.086 3439 Ptgs1 8 OAHOA 5: 130.6 130.6 < 0.00002 < 0.034 1306999 Gpx7 9 PAHOA 10: 104.7 107.7 < 0.00003 < 0.012 1311950 Fads6 13 PAHLA 10: 104.7 107.7 < 0.00008 < 0.028 1311950 Fads6
Group 4 13 AAHLA 4: 0.1 14.6 < 0.00022 < 0.092 2301 Cd36
Acnat1, acyl coenzyme A amino acid N acyltransferase 1; Acnat2, acyl coenzyme A amino acid
N acyltransferase 2; Baat, bile acid CoA:amino acid N acyltransferase; 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 S transferase
1; Mgst1, microsomal glutathione S transferase 1; Mgst3, microsomal glutathione S transferase
3; Olr1, oxidized low density lipoprotein receptor 1; Prdx6, peroxiredoxin 6; Ptgs1, prostaglandin endoperoxide synthase 1.
Figure legends
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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.
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.
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.
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.
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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 glycaemia 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.
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
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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.
180x220mm (300 x 300 DPI) Page 35 of 44 Diabetes
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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
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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 isomerase 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