Developmental Accretion of Docosahexaenoic Acid Is Independent of Fatty Acid Transporter Expression in Brain and Lung Tissues of C57BL/6 and Fat1 Mice

William Yakah; Pratibha Singh; George Perides; Joanne Brown; Steven D Freedman; Camilia R Martin

doi:10.1093/jn/nxz074

. 2019 Jun 10;149(10):1724–1731. doi: 10.1093/jn/nxz074

Developmental Accretion of Docosahexaenoic Acid Is Independent of Fatty Acid Transporter Expression in Brain and Lung Tissues of C57BL/6 and Fat1 Mice

William Yakah ¹, Pratibha Singh ², George Perides ², Joanne Brown ², Steven D Freedman ^2,³, Camilia R Martin ^3,^4,^✉

PMCID: PMC6768804 PMID: 31179494

ABSTRACT

Background

Developmental expression of fatty acid transporters and their role in polyunsaturated fatty acid concentrations in the postnatal period have not been evaluated.

Objective

We hypothesized that transporter expression is developmentally regulated, tissue-specific, and that expression can modulate fatty acid accretion independently of diet.

Methods

Brain and lung transporter expression were quantified in C57BL/6 wild-type (WT) and Fat1 mice. Pups were dam-fed until day 21. Dams were fed AIN-76A 10% corn oil to represent a typical North American/European diet. After weaning, mice were fed the same diet as dams. Gene expression of Fatp1, Fatp4, Fabp5, and Fat/cd36 was quantified by quantitative reverse transcriptase-polymerase chain reaction. Fatty acid concentrations were measured by GC–MS.

Results

Brain docosahexaenoic acid (DHA) concentrations increased from day 3 to day 28 in both genotypes, with higher concentrations at days 3 and 14 in Fat1 than in WT mice [median (IQR)]: 10.7 (10.6–11.2) mol% compared with 6.6 (6.4–7.2) mol% and 12.5 (12.4–12.9) mol% compared with 8.9 (8.7–9.1) mol%, respectively; P < 0.05). During DHA accrual, transporter expression decreased. Fold changes in brain Fatp4, Fabp5, and Fat/cd36 were inversely correlated with fold changes in brain DHA concentrations in Fat1 relative to WT mice (ρ = −0.85, −0.75, and −0.78, respectively; P ≤ 0.001). Lung DHA concentrations were unchanged across the 3 time points for both genotypes. Despite unchanging DHA concentrations, there was increased expression of Fatp1 at days 14 and 28 (5-fold), Fatp4 at day 14 (2.3-fold), and Fabp5 at day 14 (3.8-fold) relative to day 3 in Fat1 mice. In WT mice, Fatp1 increased almost 5-fold at day 28 relative to day 3. There was no correlation between lung transporters and DHA concentrations in Fat1 relative to WT mice.

Conclusions

Development of fatty acid transporter expression in C57BL/6 WT and Fat1 mice is genotype and tissue specific. Further, postnatal accretion of brain DHA appears independent of transporter status, with tissue concentrations representing dietary contributions.

Keywords: fatty acid accretion, newborn development, fatty acid transporters, docosahexaenoic acid, arachidonic acid

Introduction

Fatty acids, especially long-chain PUFAs, are major sources of metabolic energy in the cell and are critical for fetal and newborn development (1). These include the 2 “essential” fatty acids, α-linolenic acid (18:3n–3) and linoleic acid (18:2n–6), which cannot be synthesized de novo, conferring the need to obtain these fatty acids from the diet (2). In contrast, omega-3 (n–3) PUFAs such as DHA can come from the diet or be synthesized from essential fatty acids and serve important structural and functional roles in infant development (2), improving cognitive function and brain myelination (3, 4). As such, the brain relies on optimal concentrations of n–3 PUFAs for development, and inadequate supplies in early gestation and infancy are harder to overcome than deficiencies occurring at later ages (5).

ω-6 (n–6) PUFAs, such as arachidonic acid (20:4n–6, AA), play critical roles in the modulation of inflammatory responses through the formation of eicosanoids (6). Also, higher concentrations of AA in the brain reflect its role in neurodevelopmental processes (7). Combinations of diets rich in both AA and DHA have been shown to improve brain development in mice as well as growth (8). Impaired postnatal metabolism and accretion of fatty acids lead to deficits in AA and DHA. These deficits are linked to an increased risk of developing chronic lung injury, nosocomial sepsis, and retinopathy of prematurity (9, 10).

With limited desaturase activity in infancy (11), the synthesis of AA and DHA from its essential fatty acid precursors, linoleic acid and α-linolenic acid, is insufficient to meet the body's high demands (8), thus supplementation with these lipid species is required (12). However, the mechanisms by which PUFAs are taken up in tissues, as well as transported across the blood–brain barrier into the brain, are poorly understood. Two mechanisms have been described to account for fatty acid transfer across cell membranes: passive diffusion, and protein-mediated fatty acid transport mechanisms (13). Fatty acid transporters not only facilitate, but also regulate, cellular fatty acid uptake in a manner similar to glucose transport by glucose transporters (14). It has also been proposed that fatty acid transporters can function not only as direct transporters of PUFAs, but also as enzymes that activate PUFAs through acyl-CoA synthetase activity, or both (15). Fatty acid transporters have also been implicated in the pathogenesis of diseases such as obesity and type 2 diabetes (14), becoming targets for therapeutic measures.

Several fatty acid transporters have been identified to be involved in fatty acid uptake, including plasma membrane fatty acid binding protein (FABP), fatty acid translocase (FAT/CD36), and a family of fatty acid transport proteins (FATPs). Increasing expression of the genes encoding fatty acid transporters has been shown to lead to increasing PUFA uptake (15–18), highlighting the important roles fatty acid transporters may play in fatty acid accretion during fetal and newborn development. However, the expression of fatty acid transporters and their role in maintaining fatty acid status in tissues, and especially in the brain, have not been evaluated from a developmental perspective.

We hypothesized that fatty acid transporter expression is developmentally regulated, is tissue specific, and that their expression can modulate DHA and AA accretion independently of diet in the newborn. Understanding the interplay between DHA and AA and specific fatty acid transporters across age may help identify age-specific nutritional strategies to optimize DHA and AA accretion in newborns.

Methods

Animals

All procedures were approved by the Institutional Animal Care and Use Committee at the Beth Israel Deaconess Medical Center, Boston, MA (#108–2014). C57BL/6 wild-type (WT) mice were purchased from Charles River Laboratories. Transgenic Fat1 mice on a C57BL/6 background were kindly provided by Dr. Jing Kang's laboratory at Massachusetts General Hospital, Boston, MA. The Fat1 mouse expresses the Caenorhabditis elegans Fat1 gene encoding an n–3 fatty acid desaturase that converts n–6 PUFAs to n–3 PUFAs (19). The animals were kept under standard laboratory conditions and maintained on a controlled 12-h dark-light diurnal cycle, with access to food and water ad libitum. The dam and postweaning diet used was based on the semisynthetic rat and mouse diet AIN-76A developed by the American Institute of Nutrition (20, 21). A modified version of the diet (AIN-76A with 10% corn oil) obtained from TestDiet was used as representative of a typical North American/European diet. This diet is enriched in SFAs and MUFAs which in the WT mouse leads to a dominant n–6 fatty acid profile. In contrast, Fat1 mice are capable of converting n–6 fatty acids and convert them down the n–3 pathway as a result of possessing the Fat1 gene from C. elegans. This unique metabolism leads to a dominant n–3 fatty acid profile in Fat1 mice (19). After birth, pups were dam-fed until killing or weaning at 21 d, whichever came first. After 21 d, mice were weaned to the same unpurified diet as the dams. Fat1 and WT mice at days 3 (baseline), 14, and 28 were killed by carbon dioxide asphyxiation. Brain and lung tissues were snap-frozen and stored at −80°C for later use.

There was a total of 31 mice in the study with 17 in the Fat1 group (n = 6, 6, and 5 for days 3, 14, and 28, respectively) and 14 in the WT group (n = 6, 3, and 5 for days 3, 14, and 28, respectively). Sex of the mice could not be determined at day 3. At day 14, 4 males and 2 females were Fat1 and 3 males were WT. At day 28, both groups had 4 males and 2 females.

RNA isolation

Total RNA was isolated from 50 mg of homogenized tissue using the guanidine thiocyanate method (22). The RNA concentration and purity were measured using a Nanodrop 2000 (Thermo Scientific).

Genotyping of Fat1 status

Mouse littermates were genotyped by PCR using mouse tail DNA. For DNA isolation, the mouse tail was incubated with 100 μL of 50 mM NaOH at 95°C for 1 h. After 1 h, 10 μL of 1 M Tris-HCl (pH = 8.0) was added. The samples were mixed on a vortex, centrifuged for 15 min at 14,000 × g at 4°C, and stored at 4°C until used. PCR was performed to determine the mouse genotype using the following primers: Fat1 forward, TGTTCATGCCTTCTTCTTTTTCC; Fat1 reverse, GCGACCATACC TCAAACTTGGA, and GoTaq Green Master Mix (Promega). PCR products and DNA ladders were subjected to electrophoresis on a 2% agarose gel. Pups who matched the genotype of their mothers were selected for final analysis (e.g., WT pups born to WT mothers and Fat1 pups born to Fat1 mothers) to maintain the gene-induced fatty acid phenotypes throughout the preweaning period.

Fatty acid analysis

Brain and lung tissues were isolated and methylated using a modified Folch method as described previously (23). Briefly, tissue samples were ground to powder in liquid nitrogen and total lipids were extracted using chloroform:methanol (2:1, vol:vol). After 10 min on ice, the samples were mixed on a vortex and centrifuged at 1080 × g for 10 min at room temperature. The lower phase was removed and completely dried under nitrogen gas vapors. Fatty acids were then methylated by addition of 0.5 mL 0.5 mol/L methanolic NaOH and incubated for 3 min at 100°C. FAME mass was determined by comparing areas of unknown FAMEs to that of a fixed concentration of 17:0 internal standard. Up to 31 FAMEs were identified per sample. Individual fatty acid concentrations are expressed as a percentage of the total fatty acid mass (mol%).

qRT-PCR

We used qRT-PCR to quantify the relative changes of gene expression in the brain and lung tissues of Fat1 and WT littermates. We used the Power SYBR Green RNA-to-C_T 1-Step Kit (Applied Biosystems) according to the manufacturer's instructions. We used 0.5 µg RNA from each sample to prepare a 25-µL total volume of master-mix. qRT-PCR analysis of murine Fatp1, Fatp4, Fabp5, Fat/cd36, and Gapdh was carried out using an ABI Prism 7000 Sequence Detector (Applied Biosystems) following the manufacturer's protocol. The set of primers for Fatp1 (sense: 5′-CGCTTTCTGCGTATCGTCTGCAAG-3′; antisense: 5′-AAGATGCACGGGATCGTGTCT-3′), Fatp4 (sense 5′- CAGCAACTGTGACCTGGAGA-3′; antisense: 5′- CCTTCCGCAACTCTGTCTTC-3′), Fabp5 (sense: 5′-CAAAACCGAGAGCACAGTGA-3′; antisense: 5′-AAGGTGCAGACCGTCTCAGT-3′z), Fat/cd36 (sense: 5′-CCTTAAAGGAATCCCCGTGT-3′; antisense: 5′-TGCATTTGCCAATGTCTAGC-3′), and Gapdh (housekeeping gene, sense: 5′-AGGTCGGTGTGAACGGATTTG-3′; antisense: 5′-TGTAGACCATGTAGTTGAGGTCA-3) were synthesized by Eurofins Genomics. C_T values were determined, and mRNA expression levels were calculated as fold changes using the ∆∆C_T method normalized to Gapdh.

Statistical methods

All statistical analyses were tissue specific with comparisons across time to determine the role of developmental expression of fatty acid transporters on tissue n–3 and n–6 PUFA concentrations. Fatty acid concentrations are presented as median (IQR). Two-factor ANOVA using generalized linear modeling after rank normal transformation of the data was used to compare unbalanced, repeated measures of fatty acid concentrations across time and between experimental (Fat1) and control (WT) groups at each time point. If significant, Tukey's honestly significant difference test (HSD) post hoc analysis adjusting for multiple comparisons was performed.

The RT2 profiler Custom PCR Array (Qiagen) was used to quantify the relative changes in gene expression. Results of the mRNA quantification of Fatp1, Fatp4, Fabp5, and Fat/cd36 are reported as median (IQR) fold change. A median fold change >1 represents upregulation and a value <1 represents downregulation.

The analytical approach consisted of 2 steps to understand the relation between the developmental expression of fatty acid transporters and tissue accretion of the critical fatty acids DHA and AA. First, for each genotype, median fold changes of transporter gene expression at days 14 and 28 were calculated using day 3 as the referent time point. The Kruskal–Wallis test was performed to evaluate differences in gene expression across time for each genotype. If the result of the Kruskal–Wallis test was statistically significant, Dunn's multiple comparison test was used to compare different time points in a pairwise fashion (24). Second, we repeated these analyses using fold changes in Fat1 relative to WT at each time point, followed by correlation testing of these fold changes with fold changes in fatty acid concentration.

Data analyses were performed using R version 3.3.1 (R Foundation) and GraphPad Prism version 7.00 (GraphPad Software Inc.) software. P values < 0.05 were considered statistically significant.

Results

Effect of high n–6 PUFA diet on fatty acid concentrations

In order to use the same diet in all animal groups but enrich for n–3 PUFAs and n–6 PUFAs, we took advantage of Fat1 mice and their WT littermates. Median (IQR) fatty acid concentrations (mol%) of select PUFAs in the n–3 and n–6 pathway of Fat1 and WT mice in brain and lung tissues are shown in Tables 1 and 2, respectively. The complete fatty acid profiles for the brain and lung tissues are shown in Supplemental Tables 1 and 2, respectively. For both genotypes there was an accrual in the major n–3 fatty acids EPA (20:5n–3) and DHA from day 3 to day 28 in the brain (EPA: P < 0.0001 for Fat1; P < 0.007 for WT; DHA: P < 0.001 for Fat1; P < 0.0001 for WT), whereas these were unchanged across time in the lung [EPA: main effect of day: F(2,25) = 1.8, P = 0.2; DHA: main effect of day: F(2,25) = 0.8, P = 0.5]. There were no changes in the concentrations of the n–6 fatty acid AA over time for both genotypes in brain [main effect of day: F(2,25) = 3.1, P = 0.06] and lung [main effect of day: F(2,25) = 2.4, P = 0.1].

TABLE 1.

Fatty acid profiles in brain tissue of WT and Fat1 transgenic mice on postnatal days 3, 14, and 28¹

					P value²
Fatty acid	Genotype	Day 3	Day 14	Day 28	Day	Genotype	Day*Genotype
18:3n–3 ALA					0.2	0.1	0.2
	Fat1	0.0 (0.0–0.02)	ND	ND
	WT	ND	ND	ND
20:5n–3 EPA					0.02	<0.001	<0.001
	Fat1	0.6 (0.6–0.9)^b*	0.3 (0.2–0.3)^c*	0.08 (0.08–0.1)^a
	WT	ND^b	ND^b	0.06 (0.06–0.07)^a
22:6n–3 DHA					<0.001	<0.001	0.2
	Fat1	10.7 (10.6–11.2)^b*	12.5 (12.4–12.9)^a,b*	13.7 (13.4–13.9)^a
	WT	6.6 (6.4–7.2)^b	8.9 (8.7–9.1)^b	13.2 (12.2–13.4)^a
18:2n–6 LA					0.004	0.006	0.6
	Fat1	1.1 (1.1–1.2)	1.4 (1.3–1.6)	1.2 (1.2–1.2)
	WT	1.0 (0.8–1.1)	1.1 (1.1–1.1)	1.1 (1.0–1.1)
20:3n–6 DGLA					<0.001	<0.001	0.02
	Fat1	0.6 (0.6–0.6)^b*	1.0 (0.9–1.0)^a*	0.9 (0.7–0.9)^a
	WT	0.4 (0.4–0.4)^b	0.6 (0.6–0.6)^a	0.7 (0.7–0.7)^a
20:4n–6 AA					0.06	0.01	0.2
	Fat1	9.4 (9.3–9.6)	10.1 (9.5–10.4)	9.8 (9.5–10.1)
	WT	10.2 (9.8–10.6)	12.2 (12.1–12.5)	10.2 (9.8–10.8)
n–6:n–3 fatty acid ratio					0.01	<0.001	0.1
	Fat1	1.1 (1.1–1.1)*	1.1 (1.1–1.2)	1.1 (1.0–1.1)
	WT	2.4 (2.3–2.5)^a	2.2 (2.2–2.4)^a	1.1 (1.1–1.2)^b

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Values are medians (IQR) (n = 31; Fat1 n = 6, 6, and 5, and WT n = 6, 3, and 5, for days 3, 14, and 28, respectively). Values are mol% except for n–6:n–3 fatty acid ratio. Medians in a row (Day 3, 14, and 28) within each genotype without a common letter are significantly different, P < 0.05. *Different from the WT group at that time point, P < 0.05. AA, arachidonic acid; ALA, α-linolenic acid; DGLA, dihomo-γ-linolenic acid; LA, linoleic acid; ND, not detectable with fatty acid value < 0.001 mol%; n–6:n–3 fatty acid ratio, ratio of ω-6 to ω-3 fatty acid; WT, wild-type.

Two-factor ANOVA using generalized linear modeling after rank normal transformation of the data was performed with Tukey's honestly significant difference test (HSD) post hoc analysis.

TABLE 2.

Fatty acid profiles in lung tissue of WT and Fat1 transgenic mice on postnatal days 3, 14, and 28¹

					P value²
Fatty acid	Genotype	Day 3	Day 14	Day 28	Day	Genotype	Day*Genotype
18:3n–3 ALA					0.005	<0.001	0.01
	Fat1	0.3 (0.2–0.3)^a*	0.1 (0.1–0.2)^b*	0.2 (0.2–0.2)^b
	WT	0.1 (0.08–0.1)	0.04 (0.02–0.05)	0.1 (0.06–0.2)
20:5n–3 EPA					0.2	<0.001	0.001
	Fat1	2.3 (2.0–2.4)*	0.6 (0.6–0.7)*	0.5 (0.4–0.5)
	WT	ND	ND	0.0 (0–0.01)
22:6n–3 DHA					0.5	<0.001	0.2
	Fat1	3.1 (2.9–3.3)	2.9 (2.5–3.0)	3.3 (3.2–3.7)*
	WT	1.7 (1.5–1.9)	1.3 (1.2–1.4)	1.9 (1.1–2.1)
18:2n–6 LA					<0.001	0.1	0.3
	Fat1	9.1 (8.7–9.4)	11.3 (10.7–11.9)	13.4 (13.0–14.0)
	WT	8.6 (8.4–8.9)^b	9.9 (8.6–10.1)^a,b	14.9 (11.3–16.2)^a
20:3n–6 DGLA					0.005	0.9	0.1
	Fat1	1.2 (1.1–1.2)	1.5 (1.4–1.5)	1.2 (1.1–1.2)
	WT	1.1 (0.9–1.1)^b	1.7 (1.5–1.7)^a	1.3 (1.3–1.4)^a,b
20:4n–6 AA					0.1	<0.001	0.004
	Fat1	5.3 (5.0–5.7)	6.0 (6.0–6.3)	7.1 (6.9–7.2)
	WT	10.5 (9.3–10.7)	10.2 (9.0–10.3)	9.2 (6.8–10.4)
n–6:n–3 fatty acid ratio					0.1	<0.001	0.6
	Fat1	2.1 (2.1–2.2)*	3.5 (3.4–3.7)*	4.1 (3.5–4.1)*
	WT	11.0 (10.7–12.0)	13.5 (12.9–13.9)	11.1 (8.8–16.5)

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Values are medians (IQR) (n = 31; Fat1 n = 6, 6, and 5, and WT n = 6, 3, and 5, for days 3, 14, and 28, respectively). All values expressed as mol% except for n–6:n–3 fatty acid ratio. Medians in a row (Day 3, 14, 28) within each genotype without a common letter are significantly different, P < 0.05. *Different from the WT group at that time point, P < 0.05. AA, arachidonic acid; ALA, α-linolenic acid; DGLA, dihomo-γ-linolenic acid; LA, linoleic acid; ND, not detectable with fatty acid value <0.001 mol%; n–6:n–3 fatty acid ratio, ratio of ω-6 to ω-3 fatty acid; WT, wild-type.

Two-factor ANOVA using generalized linear modeling after rank normal transformation of the data was performed with Tukey's honestly significant difference test (HSD) post hoc analysis.

As anticipated, the brain and lungs from Fat1 mice had higher n–3 PUFA concentrations than those of WT mice. In the preweaning period, marked by postnatal days 3 and 14, EPA and DHA concentrations were significantly higher in brain tissue from Fat1 mice than from their WT littermates, but showed no significant difference between both groups at postnatal day 28 (P = 0.6 for EPA, P = 0.6 for DHA). In the lung, EPA concentrations were significantly higher in Fat1 than in WT mice on days 3 and 14 (P < 0.0001 for both time points). DHA concentrations were significantly higher in Fat1 than in WT mice on day 28 (P = 0.001). Median AA concentrations were lower in the lungs from Fat1 mice than in those of their WT littermates on days 3 and 14 (P < 0.0001 and P = 0.03, respectively).

Postnatal changes in fatty acid transporters

mRNA expression of Fatp1, Fatp4, Fabp5, and Fat/cd36 in brain and lung tissues from Fat1 and WT mice is shown in Figure 1. For each genotype, median (IQR) fold changes are reported for brain (Figure 1A–C) and lung tissues (Figure 1D–F) compared with the baseline at postnatal day 3. In addition, transporter expression in Fat1 mice relative to their WT littermates for each postnatal day was evaluated (Figure 1C, F). In the brain, the expression of Fatp1, Fabp5, and Fat/cd36 decreased at day 28 relative to day 3 in Fat1 mice (Figure 1A). In WT mice (Figure 1B), all measured transporters significantly decreased at day 28 relative to day 3. Comparatively, in Fat1 relative to WT mice (Figure 1C), the fold change in the expression of Fatp4, Fabp5, and Fat/cd36 was higher at day 28 than at day 3 for Fatp4 or at day 14 for Fabp5 and Fat/cd36.

mRNA expression of fatty acid transport proteins in *Fat1* and WT mice for brain (A–C) and lung (D–F) tissues on postnatal days 3, 14, and 28. (A, D) transporter expression in *Fat1* mice on days 14 and 28 relative to day 3; (B, E) transporter expression in WT mice on days 14 and 28 relative to day 3; (C, F) transporter expression in *Fat1* relative to WT mice at each postnatal day. Fold changes are reported as median (IQR) fold changes (n = 31; *Fat1 n* = 6, 6, 5, and WT n = 6, 3, and 5, for days 3, 14, and 28, respectively). Statistical significance of the change in transporter expression across time for each genotype was determined by Kruskal–Wallis test followed by pairwise comparisons adjusted by Dunn's multiple comparison test. Labeled points without a common letter are significantly different, P ˂ 0.05. *Fabp5*, fatty acid binding protein 5; *Fat/cd36*, fatty acid translocase/cluster domain 36; *Fatp1*, fatty acid transport protein 1; *Fatp4*, fatty acid transport protein 4; WT, wild-type.

In contrast, in the lungs of Fat1 mice, expression of Fatp1, Fatp4, and Fabp5 demonstrated an increase at the preweaning time point of day 14 relative to day 3 (Figure 1D). Of these transporters only Fatp1 showed an increase in expression at day 28 relative to day 3. In the lungs of WT mice, an increase in expression of Fatp1 was seen at day 28 relative to day 3. For Fatp1 and Fatp4, the fold change at day 28 relative to day 3 was greater than the fold change at day 14 relative to day 3. Fat/cd36 declined at day 14 relative to day 3. No changes in expression of Fabp5 were observed (Figure 1E). Relative to WT mice, Fat1 mice had an increase in fold expression in the preweaning period for Fatp1 (fold change at day 14 compared with day 3) and a decrease in expression in the postweaning period (fold change at day 28 compared with day 14) for Fatp1 and Fatp4 (Figure 1F).

Dietary effects on transporter expression and DHA and AA accretion

To investigate the effect of transporter expression on DHA and AA concentrations, Spearman rank correlation coefficients were plotted and calculated between the mRNA expression of the fatty acid transporters Fatp1, Fatp4, Fabp5, and Fat/cd36 and the fatty acids DHA and AA in the brain (Figure 2) and lung (Figure 3) tissues of Fat1 mice relative to WT littermates. In the brain, higher fold changes in DHA concentrations significantly correlated with lower expression of Fatp4 (ρ = −0.85, P < 0.001), Fabp5 (ρ = −0.75, P = 0.001), and Fat/cd36 (ρ = −0.78, P < 0.001) in Fat1 mice (Figure 2B–D). There was no correlation between the expression of Fatp1 and DHA accrual in Fat1 relative to WT brain (Figure 2A). In contrast to brain, there were no significant correlations between transporter expression and DHA accretion in the lung tissue (Figure 3A–D).

Spearman rank correlation coefficients of mRNA expression of fatty acid transporters and DHA (A–D) and AA (E–H) in brain tissue. mRNA expression and fatty acid values are summarized as fold changes in *Fat1* mice relative to WT littermates (n = 17). AA, arachidonic acid; *Fabp5*, fatty acid binding protein 5; *Fat/cd36*, fatty acid translocase/cluster domain 36; *Fatp1*, fatty acid transport protein 1; *Fatp4*, fatty acid transport protein 4; WT, wild-type.

Spearman rank correlation coefficients of mRNA expression of fatty acid transporters and DHA (A–D) and AA (E–H) in lung tissue. mRNA expression and fatty acid values are summarized as fold changes in *Fat1* mice relative to WT littermates (n = 17). AA, arachidonic acid; *Fabp5*, fatty acid binding protein 5; *Fat/cd36*, fatty acid translocase/cluster domain 36; *Fatp1*, fatty acid transport protein 1; *Fatp4*, fatty acid transport protein 4; WT, wild-type.

Similar procedures were conducted to evaluate the effect of transporter expression on AA concentrations. The AA fold change in Fat1 relative to WT mice was <1.0 for both brain and lung tissues because AA concentrations are lower in Fat1 than in WT mice. In the brain (Figure 2E–H), increased fold changes of AA in Fat1 relative to WT were positively correlated with expression of Fabp5 (ρ = 0.57, P = 0.02) and Fat/cd36 (ρ = 0.69, P = 0.003), but inversely correlated with Fatp1 (ρ = −0.60, P = 0.01). In the lung, Fabp5 was positively correlated with AA fold change, whereas there were no other significant correlations with the other transporters (Figure 3E–H).

Discussion

The objective of this study was to investigate developmental and tissue-specific changes in fatty acid transporters and to identify how PUFA accretion is or is not related to transporter expression. The study was carried out at 3 developmental stages: postnatal days 3, 14, and 28, which are developmentally equivalent to humans at 23–32 wk preterm, 2–8 mo, and 4–8 y of age, respectively (25). The use of transgenic Fat1 mice in this study is a first step in understanding the overarching mechanisms involved in fatty acid uptake in metabolically relevant tissues in humans. Although the direct transferability of mouse to human nutrition studies is not fully understood, the basic aspects of metabolism are the same in both mammals and differences, where they exist, are quantitative on a per-kilocalorie basis, not qualitative (26). Given the well-established functions of n–3 PUFAs such as DHA, we can compare fatty acid transporter differences in the Fat1 model, which has higher n–3 PUFAs, with their higher n–6 PUFA WT littermates fed a North American/European diet. In the brain, we found that the developmental changes in expression levels of fatty acid transporters were not directly related to DHA accretion. For both WT and Fat1 mice, transporter expression decreased across advancing age despite increasing DHA accrual. In the lung within each genotype, we found increasing transporter expression levels across time despite no changes to DHA concentrations.

DHA accretion in the brain is a critical step in infant neurodevelopment as there is an increased need for DHA to be incorporated into neuronal membranes (27). Our study showed increased concentrations of DHA in both Fat1 and WT groups across postnatal ages, with higher concentrations in Fat1 than in WT mice in the preweaning period. Higher DHA concentrations in Fat1 than in WT mice at postnatal day 3 suggest that maternal DHA during pregnancy may have contributed to higher fetal brain DHA which was sustained after birth (28). This is supported by studies in rats where early supplementation with DHA during the preweaning period maintained high DHA concentrations in the brain even after pups were switched to a low-DHA diet (29). Increased postweaning desaturase activity in the liver (30) and further increased DHA synthesis may increase DHA incorporation into brain tissue to compensate for low dietary DHA concentrations as seen in the WT mice.

Specific mechanisms involving PUFA uptake have been a source of debate and are still relatively unclear. Previous studies support either passive diffusion through a “flip-flop” mechanism independent of transport proteins (31, 32), or protein-mediated transport (13, 33, 34). A few support both mechanisms to be involved in PUFA uptake across membranes (35). FATPs are members of the solute carrier family (SLC27A1–6). They are involved in fatty acid uptake and show variable expression owing to tissue-specific preferences for various isoforms of the transporters (36). The expression of FATPs in humans has strong homology to mice and other vertebrates and thus mouse studies to investigate mechanisms of fatty acid transport across membranes are likely relevant to humans (37). Fatp1 is highly expressed in adipose tissue but also in the brain and lung (38). Fatp4, in addition to being expressed in the brain, is also expressed by enterocytes of the intestinal epithelial cells and has been implicated in lipid absorption (15, 39). Fatty acid binding proteins consist of a family of cytosolic or plasma membrane binding proteins involved in fatty acid transport by increasing the concentration gradient of unbound fatty acids or docking with the plasma membrane (40). Of the subtypes expressed in various tissues, Fabp5 is expressed by neurons and glial cells in the prenatal and perinatal brain (41). We observed decreased expression of Fabp5 at late postnatal age in brain tissue, as was reported by Owada et al. (42). The scavenger receptor FAT/CD36 is also implicated in the transport of PUFAs in the microvascular endothelial cells of the brain (43). Some studies involving Fat/cd36-null mice show no change in DHA or AA concentrations (44, 45).

In agreement with previous work, we observed differences in the expression profiles of all fatty acid transporters between the developing and mature brain as also reported in a rat study (42). However, our results showed an inverse correlation between transporter expression profile and DHA accretion across age. This inverse correlation may be due to a regulatory mechanism to modulate DHA uptake into cells to avoid possible harmful effects of excess DHA accretion (14). Similarly, the higher expression profiles of transporters observed in lung tissue across the time points studied may also be a regulatory mechanism to increase DHA concentrations to meet metabolic demands of the lung.

Recent studies support both passive diffusion and protein-mediated transport as contributors to fatty acid uptake, suggesting that 1 sole mechanism is not enough for cellular fatty acid uptake in vivo (46, 47). At physiologic levels, most fatty acids are bound to the high-affinity sites on albumin. As such, low concentrations of free fatty acids cannot pass through membranes by passive diffusion, consequentially relying on protein-mediated transport. This suggests that the flip-flop mechanism on its own may not be sufficient to meet the cell's metabolic fatty acid demands. Other studies have demonstrated that most PUFA uptake in tissues is carried out by a saturable mechanism, which occurs rapidly at high concentrations of nonesterified fatty acids, thus suggesting that transporter expression may change to modulate PUFA uptake (47–49). Saturation of protein-mediated transporters slows down fatty acid transport, and the build-up of free fatty acids at the extracellular matrix then creates a diffusion gradient that may favor passive diffusion of fatty acids across the lipid bilayer. This saturable mechanism may suggest that protein-mediated uptake takes precedence when free fatty acids are at physiologic levels, whereas passive diffusion becomes predominant at higher, presumably nonphysiologic fatty acid levels (33). The roles played by both mechanisms of fatty acid uptake explain how dietary supplementation of fatty acids, such as DHA, leads to tissue accretion of the fatty acid of interest, irrespective of transporter status.

Successful accretion of DHA independent of transporter status has several potential implications when translating to human infants. First, acquired postnatal deficits in critical fatty acids especially in the preterm infant can be overcome by dietary supplementation and are not limited by developmental changes in fatty acid transporter status. Second, and closely related to the first, deficiencies in systemic fatty acid status should raise the concern of inadequate dietary delivery. Third, if insufficient fatty acid status persists despite nutritional intervention, other non–transporter-related issues should be considered such as the developmental and genetic capability of adequate digestion, absorption, and downstream conversion. Our data inform the above framework and highlight the physiological issues that need to be considered to optimize fatty acid delivery during infancy.

In conclusion, we hypothesized that the expression of fatty acid transporters is developmentally regulated, is tissue specific, and that their expression can modulate fatty acid accretion independently of diet. Our results demonstrate that transporter expression is tissue-specific; however, in contrast to our original hypothesis, we also show that fatty acid profiles can be altered by diet alone independently of transporter status, indicating that diet is a major driver of fatty acid status. Thus, diet can significantly alter tissue concentrations of PUFAs across a wide developmental spectrum from prematurity to infancy, independently of transporter status. This identifies diet as an important modifiable factor for fatty acid accretion regardless of the developmental transporter status of the host.

Supplementary Material

nxz074_Supplement_Tables

Click here for additional data file.^{(373.2KB, zip)}

Acknowledgments

The authors’ responsibilities were as follows—WY, CRM, and SDF: designed the research; WY, PS, GP, and JB: conducted the research; WY, PS, CRM, and SDF: analyzed the data and wrote and revised the manuscript; CM: has primary responsibility for the final content; and all authors: read and approved the final manuscript.

Notes

Supported by Charles H and Judy Hood Family Infant Health Research Program (to CRM) and National Institute of Diabetes and Digestive and Kidney Diseases grant NIH R01 DK104346 (to CRM).

Author disclosures: WY, PS, GP, JB, SDF, and CRM, no conflicts of interest.

Supplemental Tables 1 and 2 are available from the “Supplementary data” link in the online posting of the article and from the same link in the online table of contents at https://academic.oup.com/jn/.

WY and PS contributed equally to this work.

Abbreviations used: AA, arachidonic acid; Fabp5, fatty acid binding protein 5; Fat/cd36, fatty acid translocase/cluster domain 36; FATP, fatty acid transport protein; Fatp1, fatty acid transport protein 1; Fatp4, fatty acid transport protein 4; WT, wild type.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

nxz074_Supplement_Tables

Click here for additional data file.^{(373.2KB, zip)}

[bib1] 1. Dourlen P, Sujkowski A, Wessells R, Mollereau B. Fatty acid transport proteins in disease: new insights from invertebrate models. Prog Lipid Res. 2015;60:30–40. [DOI] [PubMed] [Google Scholar]

[bib2] 2. Agostoni C. Role of long-chain polyunsaturated fatty acids in the first year of life. J Pediatr Gastroenterol Nutr. 2008;47(Suppl 2):S41–4. [DOI] [PubMed] [Google Scholar]

[bib3] 3. Yurko-Mauro K, Alexander DD, Van Elswyk ME. Docosahexaenoic acid and adult memory: a systematic review and meta-analysis. PLoS One. 2015;10(3):e0120391. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib4] 4. Larque E, Krauss-Etschmann S, Campoy C, Hartl D, Linde J, Klingler M, Demmelmair H, Cano A, Gil A, Bondy B et al.. Docosahexaenoic acid supply in pregnancy affects placental expression of fatty acid transport proteins. Am J Clin Nutr. 2006;84(4):853–61. [DOI] [PubMed] [Google Scholar]

[bib5] 5. Innis SM. Dietary (n-3) fatty acids and brain development. J Nutr. 2007;137(4):855–9. [DOI] [PubMed] [Google Scholar]

[bib6] 6. Higgins AJ, Lees P. The acute inflammatory process, arachidonic acid metabolism and the mode of action of anti-inflammatory drugs. Equine Vet J. 1984;16(3):163–75. [DOI] [PubMed] [Google Scholar]

[bib7] 7. Martin CR. Fatty acid requirements in preterm infants and their role in health and disease. Clin Perinatol. 2014;41(2):363–82. [DOI] [PubMed] [Google Scholar]

[bib8] 8. Harauma A, Yasuda H, Hatanaka E, Nakamura MT, Salem N Jr, Moriguchi T. The essentiality of arachidonic acid in addition to docosahexaenoic acid for brain growth and function. Prostaglandins Leukot Essent Fatty Acids. 2017;116:9–18. [DOI] [PubMed] [Google Scholar]

[bib9] 9. Robinson DT, Martin CR. Fatty acid requirements for the preterm infant. Semin Fetal Neonatal Med. 2017;22(1):8–14. [DOI] [PubMed] [Google Scholar]

[bib10] 10. Löfqvist CA, Najm S, Hellgren G, Engström E, Sävman K, Nilsson AK, Andersson MX, Hård AL, Smith LEH, Hellström A. Association of retinopathy of prematurity with low levels of arachidonic acid: a secondary analysis of a randomized clinical trial. JAMA Ophthalmol. 2018;136(3):271–7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib11] 11. Szitanyi P, Koletzko B, Mydlilova A, Demmelmair H. Metabolism of ¹³C-labeled linoleic acid in newborn infants during the first week of life. Pediatr Res. 1999;45(5 Pt 1):669–73. [DOI] [PubMed] [Google Scholar]

[bib12] 12. Brenna JT. Arachidonic acid needed in infant formula when docosahexaenoic acid is present. Nutr Rev. 2016;74(5):329–36. [DOI] [PubMed] [Google Scholar]

[bib13] 13. Schwenk RW, Holloway GP, Luiken JJ, Bonen A, Glatz JF. Fatty acid transport across the cell membrane: regulation by fatty acid transporters. Prostaglandins Leukot Essent Fatty Acids. 2010;82(4–6):149–54. [DOI] [PubMed] [Google Scholar]

[bib14] 14. Glatz JF, Luiken JJ, Bonen A. Membrane fatty acid transporters as regulators of lipid metabolism: implications for metabolic disease. Physiol Rev. 2010;90(1):367–417. [DOI] [PubMed] [Google Scholar]

[bib15] 15. Anderson CM, Stahl A. SLC27 fatty acid transport proteins. Mol Aspects Med. 2013;34(2–3):516–28. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib16] 16. Chiu HC, Kovacs A, Blanton RM, Han X, Courtois M, Weinheimer CJ, Yamada KA, Brunet S, Xu H, Nerbonne JM et al.. Transgenic expression of fatty acid transport protein 1 in the heart causes lipotoxic cardiomyopathy. Circ Res. 2005;96(2):225–33. [DOI] [PubMed] [Google Scholar]

[bib17] 17. Moulson CL, Lin MH, White JM, Newberry EP, Davidson NO, Miner JH. Keratinocyte-specific expression of fatty acid transport protein 4 rescues the wrinkle-free phenotype in Slc27a4/Fatp4 mutant mice. J Biol Chem. 2007;282(21):15912–20. [DOI] [PubMed] [Google Scholar]

[bib18] 18. Nickerson JG, Alkhateeb H, Benton CR, Lally J, Nickerson J, Han XX, Wilson MH, Jain SS, Snook LA, Glatz JF et al.. Greater transport efficiencies of the membrane fatty acid transporters FAT/CD36 and FATP4 compared with FABPpm and FATP1 and differential effects on fatty acid esterification and oxidation in rat skeletal muscle. J Biol Chem. 2009;284(24):16522–30. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib19] 19. Kang JX. Fat-1 transgenic mice: a new model for omega-3 research. Prostaglandins Leukot Essent Fatty Acids. 2007;77(5–6):263–7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib20] 20. Report of the American Institute of Nutrition ad hoc Committee on Standards for Nutritional Studies. J Nutr. 1977;107(7):1340–8. [DOI] [PubMed] [Google Scholar]

[bib21] 21. Newmark HL, Lipkin M, Maheshwari N. Colonic hyperproliferation induced in rats and mice by nutritional-stress diets containing four components of a human Western-style diet (series 2). Am J Clin Nutr. 1991;54(1 Suppl):209S–14S. [DOI] [PubMed] [Google Scholar]

[bib22] 22. Chomczynski P, Sacchi N. Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction. Anal Biochem. 1987;162(1):156–9. [DOI] [PubMed] [Google Scholar]

[bib23] 23. Freedman SD, Katz MH, Parker EM, Laposata M, Urman MY, Alvarez JG. A membrane lipid imbalance plays a role in the phenotypic expression of cystic fibrosis in cftr⁻^/⁻ mice. Proc Natl Acad Sci U S A. 1999;96(24):13995–4000. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib24] 24. Yuan JS, Reed A, Chen F, Stewart CN Jr. Statistical analysis of real-time PCR data. BMC Bioinformatics. 2006;7:85. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib25] 25. Semple BD, Blomgren K, Gimlin K, Ferriero DM, Noble-Haeusslein LJ. Brain development in rodents and humans: identifying benchmarks of maturation and vulnerability to injury across species. Prog Neurobiol. 2013;106–7:1–16. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib26] 26. Gallaher DD. Animal models in human nutrition research. Nutr Clin Pract. 1992;7(1):37–9. [DOI] [PubMed] [Google Scholar]

[bib27] 27. Kim HY. Novel metabolism of docosahexaenoic acid in neural cells. J Biol Chem. 2007;282(26):18661–5. [DOI] [PubMed] [Google Scholar]

[bib28] 28. Davis-Bruno K, Tassinari MS. Essential fatty acid supplementation of DHA and ARA and effects on neurodevelopment across animal species: a review of the literature. Birth Defects Res B Dev Reprod Toxicol. 2011;92(3):240–50. [DOI] [PubMed] [Google Scholar]

[bib29] 29. Elsherbiny ME, Goruk S, Monckton EA, Richard C, Brun M, Emara M, Field CJ, Godbout R. Long-term effect of docosahexaenoic acid feeding on lipid composition and brain fatty acid-binding protein expression in rats. Nutrients. 2015;7(10):8802–17. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib30] 30. Cook HW. In vitro formation of polyunsaturated fatty acids by desaturation in rat brain: some properties of the enzymes in developing brain and comparisons with liver. J Neurochem. 1978;30(6):1327–34. [DOI] [PubMed] [Google Scholar]

[bib31] 31. Hamilton JA, Guo W, Kamp F. Mechanism of cellular uptake of long-chain fatty acids: do we need cellular proteins?. Mol Cell Biochem. 2002;239(1–2):17–23. [PubMed] [Google Scholar]

[bib32] 32. Hamilton JA, Johnson RA, Corkey B, Kamp F. Fatty acid transport: the diffusion mechanism in model and biological membranes. J Mol Neurosci. 2001;16(2–3):99–108. [DOI] [PubMed] [Google Scholar]

[bib33] 33. Abumrad N, Coburn C, Ibrahimi A. Membrane proteins implicated in long-chain fatty acid uptake by mammalian cells: CD36, FATP and FABPm. Biochim Biophys Acta. 1999;1441(1):4–13. [DOI] [PubMed] [Google Scholar]

[bib34] 34. Abumrad N, Harmon C, Ibrahimi A. Membrane transport of long-chain fatty acids: evidence for a facilitated process. J Lipid Res. 1998;39(12):2309–18. [PubMed] [Google Scholar]

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PERMALINK

Developmental Accretion of Docosahexaenoic Acid Is Independent of Fatty Acid Transporter Expression in Brain and Lung Tissues of C57BL/6 and Fat1 Mice

William Yakah

Pratibha Singh

George Perides

Joanne Brown

Steven D Freedman

Camilia R Martin

ABSTRACT

Background

Objective

Methods

Results

Conclusions

Introduction

Methods

Animals

RNA isolation

Genotyping of Fat1 status

Fatty acid analysis

qRT-PCR

Statistical methods

Results

Effect of high n–6 PUFA diet on fatty acid concentrations

TABLE 1.

TABLE 2.

Postnatal changes in fatty acid transporters

FIGURE 1.

Dietary effects on transporter expression and DHA and AA accretion

FIGURE 2.

FIGURE 3.

Discussion

Supplementary Material

Acknowledgments

Notes

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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