Open Access

The effects of short-term high-fat feeding on exercise capacity: multi-tissue transcriptome changes by RNA sequencing analysis

  • Ya Xiao1, 2,
  • Wanshan Wang3,
  • Liguo Chen1,
  • Jieyu Chen2,
  • Pingping Jiang2,
  • Xiuqiong Fu4,
  • Xiaoli Nie2,
  • Hiuyee Kwan4,
  • Yanyan Liu2Email author and
  • Xiaoshan Zhao2Email author
Contributed equally
Lipids in Health and Disease201716:28

DOI: 10.1186/s12944-017-0424-7

Received: 14 July 2016

Accepted: 25 January 2017

Published: 2 February 2017

Abstract

Background

The effects of short-term high fat diets on physiology are elusive and the molecular changes following fat overconsumption remain largely unknown. In this study, we aimed to evaluate exercise capacity in mice fed with a high fat diet (HFD) for 3 days and investigate the molecular mechanisms in the early response to high-fat feeding.

Methods

Exercise capacity was assessed by weight-loaded swimming test in mice fed a control diet (10 kcal% fat) or a HFD (60 kcal% fat) for 3 days. Global gene expression of ten important tissues (brain, heart, liver, spleen, lung, kidney, stomach, duodenum, skeletal muscle and blood) was analyzed using RNA Sequencing.

Results

A HFD for just 3 days can induce 71% decrease of exercise performance prior to substantial weight gain (P <0.01). Principle component analysis revealed that differential gene expression patterns existed in the ten tissues. Out of which, the brain, spleen and lung were demonstrated to have more pronounced transcriptional changes than other tissues. Biological process analysis for differentially expressed genes in the brain, spleen and lung showed that dysregulation of peripheral and central immune response had been implicated in the early stage of HFD exposure. Neurotransmission related genes and circulatory system process related genes were significantly down-regulated in the brain and lung, respectively.

Conclusions

Our findings provide new insights for the deleterious effects of high-fat feeding, especially revealing that the lung maybe as a new important target attacked by short-term high-fat feeding.

Keywords

RNA Sequencing High-fat feeding Exercise capacity Multi-tissue Short-term

Background

High-fat and high-calorie diets along with a low physical activity lifestyle have contributed to the onset or development of type 2 diabetes, metabolic syndrome and cardiovascular disease [1]. There has been conflicting results on whether consumption of a high fat diet (HFD) is detrimental or beneficial for endurance performance. Studies in rats have demonstrated a beneficial effect of a fat-rich diet on exercise capacity via increasing the ability to oxidize fat and concomitantly sparing glycogen content [24]. In contrast, Murray et al. [5] reported that 9 days of high-fat feeding impaired energy production and physical performance associated with respiratory uncoupling in skeletal muscle mitochondria. In the present study, we aimed to evaluate exercise capacity in mice fed with a HFD for 3 days and investigate the molecular mechanisms in the early response to high-fat feeding.

Advances in genomic technologies may help to reveal the early molecular changes by enabling simultaneous analysis of thousands of genes in response to a HFD. The serial analysis of gene expression strategy identified 12 transcripts of hypothalamus which regulated by food intake in mice at 3 h after high-fat meal ingestion [6]. The transcriptomic analysis of duodenum mucosa after high-fat meal ingestion in C57BL/6 J mice found substantial changes of genes related to lipid metabolism [7]. Microarray analysis showed markedly changes of numerous genes involved in various biological processes including morphogenesis, fatty acid catabolism and amino acid metabolism following 3 days of high-fat feeding in the skeletal muscle of C57BL/6 J mice [8]. cDNA microarrays analysis of mRNA expression showed down-regulation of genes related to fatty acid biosynthesis in the liver of one week HFD-fed BALB/c mice [9].

However, no study to date has simultaneously analyzed the systemic gene expression profile of multi-tissues in response to short-term HFD and it remains unknown that which tissue has the most pronounced changes of gene expression profile in the early stage after high-fat feeding. Recently, RNA sequencing (RNA-seq), as an attractive alternative to microarrays for transcriptome analysis, provides major advances in robustness, comparability and richness of expression profiling data [10]. Thus we utilized RNA-seq to investigate gene expression profile of ten tissues (brain, heart, liver, spleen, lung, kidney, stomach, duodenum, skeletal muscle and blood) in C57BL/6 J mice with 3 days of high-fat feeding, which may contribute to the understanding of molecular mechanisms of changes in exercise performance induced by short-term HFD.

Methods

Animals and study protocol

Animal experiments were approved by the Animal Care and Use Committee of Southern Medical University (Approval No.2013027). The methods were carried out in accordance with the approved guidelines. Forty male C57BL/6 J mice at the age of 8 weeks were obtained from Laboratory Animal Center of Southern Medical University (Approval No. SCXK (Yue) 2011–0015). All the animals were maintained in a temperature-controlled room (22–25 °C; 35–55% humidity) with a twelve-hour light/dark cycle. Mice were randomly divided into two groups, where 20 mice were fed a control diet (CD, D12450B, 10 kcal% fat) and 20 mice were fed a high fat diet (HFD, D12492, 60 kcal% fat) for 3 days. Mice were allowed free access to food and water. The changes of body weight were observed after 3 days.

Assessment of exercise capacity

A weight-loaded swimming test has been commonly used for assessment of exercise capacity in murine [11, 12]. After 3 days, 10 mice were taken out from each group for swimming exercise performance test which was conducted as previously described with some modifications [13]. The mice were not fasted and were loaded the constant weight (1.5 g tin wire, attached to the tail). The mice were dropped individually into a swimming pool (30 cm high, 25 cm in diameter) filled with water at 25 ± 1 °C. It was considered that the mice were exhausted when they failed to return to the surface of water within a 10 s period. The swimming time to exhaustion was used as the index of exercise capacity.

Biochemical assays

After 3 days of feeding, the remaining 10 mice in each group were anesthetized with sodium pentobarbital (75 mg/kg, ip) following a 6 h fasting period. The blood samples were collected by removing the left eyeball of the mice and rapidly centrifuged at 1000 g at 4 °C for 10 min. Plasma levels of glucose, triglycerides, total cholesterol, low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C), free fatty acids (FFAs), apolipoprotein E (ApoE), C-reactive protein (CRP), superoxide dismutase (SOD), homocysteine (HCY), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), total protein (TP), albumin (ALB), globulin (GLB), ALB/GLB, total bilirubin (TBIL), direct bilirubin (DBIL), indirect bilirubin (IBIL), total bile acid (TBA), uric acid (UA), Creatinine (Cr), urea, Cystatin C (CysC), creatine kinase (CK), lactate dehydrogenase (LDH), A-hydroxybutyric acid dehydrogenase (HBDH), potassium (K), sodium (Na), chlorine (Cl) and calcium (Ca) were measured using a multifunctional biochemistry analyzer (Olympus AU2700, Tokyo, Japan). Statistical analyses for biochemical assays and assessment of exercise capacity were conducted using SPSS (version 19.0) for Windows. The data are reported as mean ± standard error of the mean (SEM). Differences between the compared groups were analyzed by Student’s t test. A P value less than 0.05 was considered to be statistically significant.

Tissue Processing and RNA Isolation

Five mice of each group were selected randomly from the mice which did not perform weight-loaded swimming test for RNA sequencing. Tissue samples included the whole brain and heart, liver, spleen, lung, kidney, stomach, duodenum, skeletal muscle and blood. The samples were dissected and immediately immersed in RNA later solution (Ambion, California, USA). All samples were stored at – 80 °C before processing. Total RNA was extracted from all samples using Trizol reagent (Invitrogen, Carlsbad, CA). The RNA concentration was quantified using a spectrophotometer (NanoDrop echnologies, Wilmington, DE) and the integrity was evaluated by the Agilent Bioanalyzer 2100 (Agilent, Santa Clara, CA).

RNA sequencing and gene expression analysis

In the CD and HFD group, fixed quantities of RNA of five samples from the same kind of tissue were combined into a single sample. The cDNA library was conducted by Illumina Tru-Seq RNA Sample Prep Kits (Illumina, San Diego, CA) with Ribosomal RNA depletion following manufacturer’s instructions. Samples were sequenced for 50 bp single read using the HiSeq2000 platform. Before alignment, reads with a low quality and adapters were screened by FastQC and removed. The remaining reads were mapped to the mice reference genome (UCSC mm10) with TopHat v2.0.9. The maximum number allowed for mismatch mapping was 2. Reads Per Kilobase of exon model per Million mapped reads (RPKM) was calculated to express the mRNA abundances. Analysis of differential expression was performed using edgeR, which could be used even with the most minimal levels of replication [14]. The read counts per gene were normalized to counts per million (CPM). CPM values were utilized for differential expression analysis, whereas RPKM values were used for principle component analysis (PCA) with the GeneSpring Gx 12.0 software (Agilent Technologies, Palo Alto, CA).

Biological process analysis

Molecule annotation system (MAS) is a set of web tools for function annotation based on integration of various public resources such as Gene Ontology, KEGG, BioCarta, GenMapp, UniGene, OMIM and more [15]. Biological process analysis for differentially expressed genes (DEGs) was performed using the CapitalBio MAS 3.0 software (CapitalBio Corporation, Beijing, China). Absolute fold change >2 with P < 0.05 was considered statistically significant in the RNA-seq analysis.

Real-time quantitative RT-PCR verification of RNA-seq data

To further confirm the findings from the RNA-seq analysis, we selectively examined 22 genes expression (8 genes in the brain, 9 genes in the spleen and 5 genes in the lung) using real-time quantitative RT-PCR (qRT-PCR) method. Five samples from the same kind of tissue of purified RNA in each group were used for qRT-PCR. Total RNA from the samples was first reverse- transcribed into cDNA templates with the PrimeScriptTM RT reagent Kit (TaKaRa, Otsu, Japan) according to the manufacturer’s instruction. PCR was run on a ABI 7500 Real-Time PCR System (Applied Biosystems, Inc., Foster City, CA, USA) using the SYBR Premix Ex TaqTM II (Otsu-Shi, Shiga, Japan). The reaction volume was 20 μL and the PCR conditions were as follows: 30 s. at 95 °C, 40 cycles of 5 s. at 95 °C and 34 s. at 60 °C, followed by a melting curve analysis step. Every sample was measured in duplicate, and relative quantification was determined by the comparative Ct method (2-ΔΔCT). β-actin was used as a housekeeping gene to normalize the expression data. The primers used for gene validation are listed in Additional file 1: Table S1.

Results

Body weight and blood plasma metabolites

As shown in Table 1, initial and final body weights showed no significantly differences among the groups. HFD feeding tended to increase weight gain, but this effect failed to reach statistical significance (P = 0.094). Plasma glucose levels were 67% higher in HFD-fed mice than CD-fed mice (P < 0.001). Although no differences were seen in plasma LDL-C, FFA and ApoE, the cholesterol level was significantly greater in the HFD-fed mice (P < 0.001). The increase in HDL-C (P < 0.001) and decrease in plasma triglycerides (P = 0.005) were also observed in HFD-fed mice. Plasma levels of CRP, SOD, HCY, ALT, AST, ALP, TP, ALB, GLB, ALB/GLB, TBIL, DBIL, IBIL, TBA, UA, Cr, Urea, CysC, LDH, HBDH, K and Ca were unchanged between the CD and HFD groups except for the CK, Na and Cl (Additional file 2: Table S2).
Table 1

Body weight and plasma biochemical parameters of CD-fed and HFD-fed mice

Parameter

CD

HFD

P value

Initial body weight (g)

22.81 ± 0.29

22.84 ± 0.31

0.950

Final body weight (g)

22.64 ± 0.40

23.45 ± 0.26

0.094

Plasma glucose (mmol/L)

4.71 ± 0.42

7.89 ± 0.31

<.001

Plasma triglycerides (mmol/L)

0.46 ± 0.03

0.36 ± 0.01

0.005

Plasma cholesterol (mmol/L)

2.16 ± 0.08

3.25 ± 0.08

<.001

Plasma LDL-C (mmol/L)

0.13 ± 0.02

0.19 ± 0.04

0.233

Plasma HDL-C (mmol/L)

1.55 ± 0.05

2.30 ± 0.04

<.001

Plasma FFA (mmol/L)

0.85 ± 0.04

0.88 ± 0.04

0.611

Plasma ApoE (mg/L)

16.34 ± 3.24

21.30 ± 2.57

0.254

Values are expressed as means ± SEM. CD, control diet; HFD high fat diet

Exercise capacity in a weight-loaded swimming test

The swimming time indicated the exercise capacity. Both groups of mice swam the same mean time at baseline (CD = 687.3 ± 93.9 s, HFD = 669.0 ± 87.8 s). After 3 days of feeding, CD-fed mice maintained a similar swimming time of 748.9 ± 77.4 s, whereas HFD-fed mice swam 213.7 ± 44.4 s on average, 71% less far than the CD-fed mice (P <0.001) (Fig. 1).
https://static-content.springer.com/image/art%3A10.1186%2Fs12944-017-0424-7/MediaObjects/12944_2017_424_Fig1_HTML.gif
Fig. 1

Effects of high-fat diet feeding on exercise capacity in C57BL/6 J mice (CD, control diet; HFD, high fat diet; *P < 0.01 vs. CD-fed mice). Values are expressed as means ± SEM

Summary of sequencing data and global gene expression profiles

A range of 28.1 to 67.4 million raw reads were generated among samples. After removing reads with a low quality, an average of 32.3 million clean reads per sample was obtained (range, 21.3 to 51.5 million reads). Approximately 98.64% of clean reads per sample were mapped to the mice reference genome among samples (Table 2). Totally 33151 unique genes among all samples was detected. To assess the effect of sequencing depth on RNA-seq data, we conducted sequencing saturation analysis. In the beginning of the RNA-seq, with increase of the counts of reads, the number of identified genes in each tissue was increasing. However, when the counts of reads rose to approximately 30 million, the growth rate of identified genes flattened which indicated that the number of identified genes tended to saturation.
Table 2

Summary of sequence statistics

Sample

Total number of raw reads

Total number of clean reads

Mapped reads

Mapping ratio (%)

C-blood

38,700,424

30,614,380

30,228,909

98.74%

C-brain

52,264,883

40,188,570

39,152,260

97.42%

C-duodenum

59,741,001

45,938,467

45,365,742

98.75%

C-heart

30,948,992

23,609,651

23,392,762

99.08%

C-kidney

52,803,870

40,421,377

40,024,878

99.02%

C-liver

36,944,726

28,422,843

28,121,458

98.94%

C-lung

28,118,618

21,811,801

21,603,740

99.05%

C-muscle

38,907,555

29,713,640

29,393,124

98.92%

C-spleen

46,764,891

36,109,723

34,944,640

96.77%

C-stomach

45,416,694

34,795,951

34,206,646

98.31%

H-blood

58,119,027

46,530,915

46,004,745

98.87%

H-brain

29,603,099

22,773,050

22,369,746

98.23%

H-duodenum

49,387,591

37,878,983

37,445,186

98.85%

H-heart

38,642,015

29,564,572

29,298,974

99.10%

H-liver

67,430,163

51,556,269

51,032,926

98.98%

H-lung

32,460,683

25,169,611

24,916,857

99.00%

H-muscle

30,898,190

23,377,884

23,142,897

98.99%

H-spleen

31,165,867

24,237,199

23,688,869

97.74%

H-stomach

27,849,155

21,301,788

21,072,130

98.92%

H-kidney

43,190,796

33,268,647

32,945,285

99.03%

C control diet group, H high fat diet group

To investigate the global gene expression profiles of ten tissues and identify the tissue with the most pronounced transcriptional changes after short-term high-fat feeding, we performed PCA on all samples (Fig. 2). The results showed differential gene expression patterns in the ten tissues. Each sphere represented an individual sample. The sphere representing liver, heart, kidney, skeletal muscle and blood in CD and HFD group overlapped, indicating that gene expression patterns of HFD-fed mice in the five tissues were almost not changed. The sphere representing stomach and duodenum in CD and HFD group were closely to each other, indicating that gene expression patterns of CD-fed and HFD-fed mice in the two tissues were nearly similar. Gene expression patterns of brain, spleen and lung in HFD group showed substantial differences as compared with CD group.
https://static-content.springer.com/image/art%3A10.1186%2Fs12944-017-0424-7/MediaObjects/12944_2017_424_Fig2_HTML.gif
Fig. 2

Principle component analysis of ten tissues in CD-fed and HFD-fed mice (CD, control diet; HFD, high fat diet). PCA analysis was conducted using the GeneSpring Gx 12.0 software. Each sphere represents an individual sample. The sphere representing liver, heart, kidney, skeletal muscle and blood in the two groups overlapped

Genes and the related biological processes altered in the brain of HFD-fed mice

According to the results of PCA, we found that the brain, spleen and lung had more pronounced transcriptional changes than other tissues following 3 days of HFD intervention. Consequently, we focused on the analysis of the genes and related biological processes altered in the brain, spleen and lung of HFD-fed mice. We found 145 DEGs in the brain, of which less than half of the genes were annotated with known function from the Ensembl database (Table 3). To gain insight into the possible biologic functions of the genes affected by high-fat feeding, enrichment analysis of Gene Ontology for the DEGs was conducted. After 3 days of HFD exposure, the overrepresented biological processes in the brain were mainly enriched in neurological system process and immune response (Fig. 3). In the neurological system process related group, LIM homeobox transcription factor 1 beta (Lmx1b), and NK2 homeobox 1(Nkx2-1), which involved in neuron migration and development, were down-regulated to 8.11-fold and 10.56-fold respectively in the HFD-fed mice. Genes related to central nervous system morphogenesis were significantly down-regulated, such as homeobox D11 (Hoxd11) (12.21-fold) and UNC homeobox (Uncx) (5.39-fold). Inflammatory/immune related processes were altered as well. The mRNA levels of chemokine (C-C motif) receptor 1(Ccr1) was up-regulated to 13.18-fold. The rest immune-related genes including chemokine (C-C motif) receptor 4 (Ccr4), CD200 receptor 3 (Cd200r3), CD274 molecule (Cd274), CD300 antigen like family member G (Cd300lg) and transcription factor AP-2, alpha (Tfap2a) were down-regulated to 8.28-,3.92-, 3.48-, 11.96- and 4.79-fold respectively.
Table 3

Differentially expressed genes in the brain of HFD-fed mice

Gene symbol

Log2FC

P- value

Gene symbol

Log2FC

P- value

Gene symbol

Log2FC

P- value

Alpi

−3.65

0.022

Slc22a19

−3.40

0.008

Gm13986

−2.48

0.019

Alpk3

−6.59

0.009

Sly

−6.59

0.009

Gm14302

−6.28

0.016

Bhlha15

−3.52

0.027

Smim24

−3.65

0.022

Gm14673

−2.43

0.018

Bmp8b

−1.82

0.039

Spata18

−5.87

0.048

Gm14886

−6.02

0.033

Brs3

2.80

0.034

Tfap2a

−2.26

0.033

Gm15174

−2.49

0.036

C6

−6.15

0.023

Tnfsf15

−5.87

0.048

Gm15302

−5.87

0.048

C87414

−5.87

0.048

Uncx

−2.43

0.041

Gm15839

−1.96

0.047

Capn11

−2.98

0.010

Usp17la

−1.86

0.039

Gm16028

−6.15

0.023

Ccr1

3.72

0.046

Vax2os

−2.15

0.017

Gm16060

−5.87

0.048

Ccr4

−3.05

0.008

Zfp345

−2.89

0.032

Gm16513

−5.87

0.048

Cd200r3

−1.97

0.040

1700007P06Rik

−6.02

0.033

Gm17085

−3.94

0.011

Cd274

−1.80

0.037

1700021A07Rik

−3.38

0.042

Gm17535

−7.89

5.53E-09

Cd300lg

−3.58

0.005

1700128F08Rik

−2.23

0.012

Gm20505

−2.04

0.046

Ces5a

−1.83

0.034

1810019N24Rik

−6.02

0.033

Gm20663

−1.98

0.044

Cpa4

−5.87

0.048

2810404F17Rik

−4.30

4.67E-04

Gm20831

−6.69

0.006

Csprs

−3.38

0.042

3110067C02Rik

−5.87

0.048

Gm21292

−3.39

0.003

Dsg3

−2.23

0.022

4931406B18Rik

−1.69

0.050

Gm2165

−2.71

0.020

Egfros

−6.39

0.016

9530056K15Rik

−5.87

0.048

Gm21719

−6.15

0.023

Esp6

−6.86

0.005

C230088H06Rik

−4.17

0.005

Gm21738

−6.61

2.23E-09

Ffar2

−3.38

0.042

C430042M11Rik

−3.06

0.002

Gm21776

−6.69

0.006

Gcm1

−2.38

0.013

G430049J08Rik

−2.29

0.025

Gm21784

−3.77

0.015

Hopxos

−5.87

0.048

CH36-246D16.4

−3.02

0.009

Gm21989

6.03

0.048

Hoxd11

−3.61

3.48E-04

CH36-35H7.2

−7.54

0.001

Gm23897

−2.55

0.009

Insrr

−2.45

0.010

CH36-399D20.1

−7.93

1.73E-04

Gm26573

−7.72

3.41E-04

Itgb6

−3.28

0.001

Gm10038

−2.16

0.026

Gm26583

−6.15

0.023

Klk14

−3.48

0.002

Gm10132

−6.02

0.033

Gm26648

−6.28

0.016

Lmx1b

−3.02

0.003

Gm10134

−1.96

0.036

Gm26704

−5.05

9.17E-06

Lypd8

−4.17

0.005

Gm10172

−2.31

0.013

Gm26705

−2.22

0.017

Mep1b

−2.76

0.020

Gm10715

−6.88

1.29E-09

Gm26719

−2.84

0.015

Mid1

−1.78

0.045

Gm10717

−6.11

3.59E-09

Gm26763

−6.15

0.023

Mpz

−5.87

0.048

Gm10718

−6.15

2.98E-09

Gm26804

−7.01

0.003

Ms4a4b

−7.01

0.003

Gm10719

−6.56

5.50E-10

Gm26857

−2.14

0.022

Muc19

−2.46

0.011

Gm10720

−4.94

1.06E-06

Gm26870

−6.03

4.96E-09

Muc6

−5.87

0.048

Gm10721

−8.04

1.26E-04

Gm27956

−6.39

0.016

Mylk4

−2.85

0.002

Gm10722

−5.19

7.91E-07

Gm3755

−1.96

0.036

Nkapl

−2.72

0.046

Gm10800

−6.03

4.95E-09

RP23-184B11.4

−6.28

0.016

Nkx2-1

−3.40

2.13E-04

Gm10801

−5.91

8.73E-09

RP23-315H12.7

−5.87

0.048

Orly

−6.69

0.006

Gm11168

−5.67

3.66E-08

RP23-458B6.16

−6.86

0.005

Otc

2.70

0.032

Gm11231

−2.18

0.032

RP23-91 L14.2

−6.59

0.009

Patl2

−5.87

0.048

Gm11398

−5.87

0.048

RP24-112B7.3

−3.24

0.012

Pcdh12

2.83

0.046

Gm11883

−5.87

0.048

RP24-209E1.3

−6.02

0.033

Pou1f1

−2.62

0.003

Gm11948

−5.87

0.048

RP24-228I22.1

−6.69

0.006

Pou2f2

−1.83

0.043

Gm12177

−2.43

0.021

RP24-319B23.2

−4.68

0.001

Pou2f3-rs1

−6.02

0.033

Gm12496

−2.91

0.013

RP24-369 J17.1

−6.39

0.016

Psg28

−1.83

0.042

Gm12652

−6.28

0.016

RP24-446E18.2

−6.02

0.033

Rbp2

−3.72

0.018

Gm13086

−2.34

0.023

RP24-482E11.1

−5.87

0.048

Rdh19

−6.28

0.016

Gm13465

−2.54

0.033

RP24-72B9.10

−6.02

0.033

Rhox8

−6.15

0.023

Gm13691

−6.28

0.016

   

Serpina10

−4.52

0.002

Gm13961

−5.87

0.048

   

FC fold change

https://static-content.springer.com/image/art%3A10.1186%2Fs12944-017-0424-7/MediaObjects/12944_2017_424_Fig3_HTML.gif
Fig. 3

Enriched biological process significantly altered in HFD-fed mice compared to CD-fed mice in the brain, spleen and lung (CD, control diet; HFD, high fat diet)

Genes and the related biological processes altered in the spleen of HFD-fed mice

61 genes were markedly changed in the spleen, however, half of which were largely unknown. The overrepresented biological processes in the spleen were mainly related to acute-phase response and immune system, with a significant change in the expression of immune-related genes (Fig. 3). As shown in Table 4, immunoglobulin kappa joining 4 (Igkj4) and T cell receptor alpha joining 37(Traj37) were increased to 8.34- and 70.52-fold respectively, while Fc receptor-like S, scavenger receptor (Fcrls), immunoglobulin heavy variable 1–84 (Ighv1-84), immunoglobulin kappa joining 1(Igkj1), immunoglobulin kappa variable 5–39 (Igkv5-39), regenerating islet-derived 3 alpha (Reg3a) and regenerating islet-derived 3 beta (Reg3b) in various immunological pathways were decreased to 74.54-, 11.63-, 54.57-, 3.60-, 16.34- and 8.11- fold respectively. Other overrepresented biological processes included carbohydrate metabolism, ubiquitin-dependent protein catabolism, G2/M transition of mitotic cell cycle and neurotransmitter uptake.
Table 4

Differentially expressed genes in the spleen of HFD-fed mice

Gene symbol

Log2FC

P- value

Gene symbol

Log2FC

P- value

Acr

−6.09

0.033

5330434G04Rik

−5.77

0.048

Ccdc38

−6.09

0.033

5730596B20Rik

−5.77

0.048

Cngb3

−5.77

0.048

AY036118

−6.09

0.033

Fau-ps2

2.73

0.027

BC061212

−3.01

0.046

Fcrls

−6.22

0.023

BC068157

5.92

0.048

Folr2

−6.22

0.023

D830025C05Rik

−5.94

0.033

Frmpd4

−6.35

0.016

Gm10071

−5.77

0.048

Hs3st5

−5.77

0.048

Gm11455

2.26

0.047

Ighv1-84

−3.54

2.38E-04

Gm11800

−3.62

0.010

Igkj1

−5.77

0.048

Gm11957

6.33

0.023

Igkj4

3.06

0.021

Gm12763

−2.40

0.034

Igkv5-39

−1.85

0.034

Gm13483

−3.01

0.046

Lnx1

−5.94

0.033

Gm14444

−6.09

0.033

Lrrc7

−2.83

0.046

Gm15302

−6.22

0.023

Mcpt4

−3.01

0.046

Gm15785

−5.94

0.033

mt-Tm

−5.77

0.048

Gm17305

−5.94

0.033

Nek10

−5.94

0.033

Gm20544

−3.01

0.046

Palm2Akap2

−3.21

0.027

Gm21719

−3.30

0.027

Pcdhb10

−6.09

0.033

Gm2237

−5.94

0.033

Reg2

−3.33

2.65E-04

Gm24436

6.33

0.023

Reg3a

−4.03

1.50E-04

Gm25153

2.80

0.035

Reg3b

−3.02

0.001

Gm25931

2.65

0.046

Rpl9-ps3

−5.94

0.033

Gm26619

−2.95

0.008

Slc17a6

−5.77

0.048

Gm26807

−6.09

0.033

St6gal2

−5.77

0.048

Gm26825

−2.37

0.029

Tceal3

−3.01

0.046

Gm6136

−6.22

0.023

Tpd52l1

−5.77

0.048

Gm6612

2.65

0.046

Traj37

6.14

0.033

RP23-446G23.1

2.80

0.035

Vat1l

−3.01

0.046

RP24-369 J17.1

−2.89

0.039

Zfp42

−5.77

0.048

RP24-44H8.4

−2.86

0.011

1700095A21Rik

−5.94

0.033

   

FC fold change

Genes and the related biological processes altered in the lung of HFD-fed mice

In the lung, 83 genes were significantly altered. The overrepresented biological processes were mainly enriched in immune-related processes, including T cell and B cell mediated immune response (Fig. 3). As shown in Table 5, Immunoglobulin heavy constant epsilon (Ighe) and immunoglobulin heavy constant gamma 1 (G1m marker) (Ighg1) were increased to 52.71- and 6.02-fold respectively, while the mRNA levels of chemokine (C-C motif) receptor 9 (Ccr9), CD8 antigen, alpha chain (Cd8a), recombination activating gene 1(Rag1), recombination activating gene 2 (Rag2) and suppression inducing transmembrane adaptor 1 (Sit1) were decreased to 6.32-, 3.94-, 512-, 19.70- and 5.10- fold respectively. Circulatory system process was also significantly changed in the lung of HFD-fed mice, with the down-regulation of natriuretic peptide precursor A (Nppa) (7.78-fold) and natriuretic peptide precursor B (Nppb) (21.26-fold). Leptin (Lep) involved in the regulation of cholesterol absorption were increased to 5.70-fold and CART prepropeptide (Cartpt) related to cell glucose homeostasis were decreased to 62.25-fold. Other overrepresented biological processes included circadian regulation of gene expression and positive regulation of transmission of nerve impulse.
Table 5

Differentially expressed genes in the lung of HFD-fed mice

Gene symbol

Log2FC

P- value

Gene symbol

Log2FC

P- value

Abcc6

5.72

0.048

Satb1

−1.99

0.022

Arpp21

−5.29

7.83E-07

Scn1a

−2.97

0.042

Arsi

−2.28

0.034

Sit1

−2.35

0.023

Bmp10

−4.72

4.94E-06

Skint10

−5.96

0.033

Cartpt

−5.96

0.033

Spo11

−3.46

0.001

Casp14

−5.96

0.033

St18

5.72

0.048

Ccr9

−2.66

0.004

Syt13

−2.12

0.039

Cd8a

−1.98

0.025

Syt2

−3.54

0.035

Cdca5

−2.28

0.036

Tdrd5

−2.93

0.006

Chrna9

−4.53

0.003

Tgm5

−2.78

0.039

Crisp1

−1.87

0.040

Themis

−2.26

0.010

Dntt

−7.36

2.18E-09

Tnni1

6.36

0.016

Elovl3

−1.96

0.036

Trbc1

−1.97

0.025

Epyc

−6.15

0.023

Trbv17

−6.32

0.016

Gucy2g

5.91

0.048

Trbv4

−3.66

0.027

Hist1h1a

−1.88

0.034

Trim10

1.90

0.040

Ighe

5.72

0.048

Tube1

−1.96

0.050

Ighg1

2.59

0.011

Ubd

−3.06

0.017

Ighv11-1

−2.90

0.002

Vmn2r96

−3.54

0.035

Ighv11-2

−3.20

0.001

Xkrx

−2.35

0.008

Ighv12-3

−3.46

0.001

Xlr5a

5.72

0.048

Ighv1-53

1.92

0.046

Zan

3.20

0.046

Ighv1-54

2.42

0.031

1600029O15Rik

5.91

0.048

Ighv1-84

−2.28

0.036

4930455G09Rik

−3.66

0.027

Ighv7-3

−2.04

0.041

9330132A10Rik

6.07

0.033

Ighv7-4

−6.47

0.012

BB031773

−7.46

0.001

Igkv14-126

−2.80

0.002

BC028471

−2.85

0.027

Igkv1-99

6.89

0.004

BC065403

−5.96

0.033

Igkv3-2

1.95

0.039

Gm10489

5.72

0.048

Igkv4-91

−2.95

0.002

Gm10715

5.91

0.048

Insc

5.91

0.048

Gm10717

1.74

0.045

Lctl

2.40

0.031

Gm10785

5.91

0.048

Lep

2.51

0.008

Gm13855

5.72

0.048

Lin28a

5.72

0.048

Gm15340

−6.47

0.012

Ltb4r1

2.93

0.022

Gm15405

−2.16

0.045

mt-Tt

6.22

0.023

Gm15576

−5.96

0.033

Nppa

−2.96

0.001

Gm20438

5.91

0.048

Nppb

−4.41

4.38E-05

Gm26202

6.07

0.033

Prom2

−2.66

0.031

Gm26316

5.72

0.048

Prss16

−9.54

4.44E-07

Gm26870

2.00

0.021

Rag1

−9.00

2.01E-12

RP23-230A14.1

5.72

0.048

Rag2

−4.30

3.9E-04

   

FC fold change

Verification of RNA-seq data

qRT-PCR was used to validate the expression levels measured by RNA-seq for 22 selected genes (8 genes in the brain, 9 genes in the spleen and 5 genes in the lung) from the list of differently expressed genes. As demonstrated in Fig. 4, qRT-PCR showed significant alterations in the expression of the 17 genes in correspondence with the findings from the RNA-sequencing analysis, while no obvious differential expression was detected for the 5 genes of Trap2a, Cd274, Ighv1-84, Igkv5-39 and Traj37 by qRT-PCR.
https://static-content.springer.com/image/art%3A10.1186%2Fs12944-017-0424-7/MediaObjects/12944_2017_424_Fig4_HTML.gif
Fig. 4

Confirmation of differential gene expression via qRT-PCR analysis (CD, control diet; HFD, high fat diet; *P < 0.05 vs. CD group). The expression value was normalized to the β-actin expression level. Values are expressed as average mRNA expression ± SEM bars

Discussion

Consistent with previous reports [6, 16], our results showed that the consumption of a high-fat diet for 3 days significantly increased plasma glucose level. The high-fat diet also increased plasma cholesterol and HDL cholesterol concentrations. Plasma triglycerides concentration decreased significantly after short-term high-fat feeding. Indeed, decreased triglycerides level was previously reported as early as 3 days after beginning a high-fat diet in a study that involved mice fed a chronic high-fat diet [17]. A randomized, double-blind, crossover study in 12 healthy subjects reported that plasma triglycerides concentration was significantly lower after a 3-d high-fat diet [18]. The low plasma triglycerides could be due to increased liver triglyceride content, possibly resulting in triglycerides being stored in the liver [19].

To our knowledge, we first reported that 3 days of high-fat feeding can induce exercise performance decrease in mice prior to substantial weight gain. In contrast to previous studies which conducted microarray analysis in a single tissue [69], we used RNA-seq to investigate the global gene expression profiles of ten tissues in the early response to fat intake. Interestingly, our study showed that differential gene expression patterns existed in the ten tissues. Previous researches on the effect of HFD mainly focused on the liver, skeletal muscle, intestine and heart, which were thought to have significant responses to consumption of high fat diets. However, in our results, the brain, spleen and lung were demonstrated to have more pronounced transcriptional changes than other tissues following 3 days of high-fat feeding. The simultaneous analysis of multi-tissues by RNA sequencing yielded information which had not been revealed by previous analyses of a single tissue.

In the brain of HFD-fed mice, dopamine neurons differentiation related genes including Lmx1b, Nkx2-1 and Uncx were found to be significantly down-regulated. Lmx1b, a key transcription factor for the specification of dopaminergic cell fate, has been reported to increase midbrain size and allocation of dopamine progenitors by promoting Wnt1/Wnt signaling [20]. Deficiency of Nkx2-1 in mice would lead to a remarkable abnormality in the trajectory of the ascending dopamine pathway [21]. Uncx, also known as Uncx4.1, is involved in the development of midbrain dopaminergic neurons [22]. Therefore, the down-regulation of these genes may contribute to impaired exercise capacity, which is supported by the observation of a link between dopamine and levels of physical exercise [23]. Moreover, Lmx1b and Nkx2-1 were demonstrated to regulate the migration of the superficial dorsal horn neurons and interneurons to the striatum or cortex, respectively [24, 25]. The decreased expression of the two genes suggested disturbed neuronal migration in HFD-fed mice, which may result in abnormal development of the nervous system. Inflammation is considered to be one of the important factors for deterioration of physical performance [26]. Similarly, our results also suggested that many immune-related genes were significantly altered in the brain of HFD-fed mice. Ccr1, which involved in the host response to pathogens and several inflammatory conditions [27], were significantly up-regulated. On the other hand, Ccr4 and Cd200r3 showed decreased expression in HFD-fed mice. Ccr4 were found to be functionally expressed on peripheral blood CD4+CD25+ regulatory T (Treg) cells [28]. CD200 imparts an immunoregulatory signal through the receptor for CD200, leading to the suppression of T-cell–mediated immune responses [29]. The up-regulation of Ccr1, coupled with the down-regulation of Ccr4 and Cd200r3, suggested the up-regulation of an inflammatory response toward the high fat diet in the brain. Consistently, it was reported that consumption of a HFD with 1 to 3 days induced hypothalamic inflammatory in both rats and mice [30]. However, the genes related to hypothalamic inflammatory signaling in the above study were not found to be significantly altered in our results. This discrepancy may reflect a difference between specific brain region and the whole brain.

The immune system has been considered to be affected by HFD exposure over a period of several weeks [31]. However, in the present study, we found that 3 days of HFD feeding had induced disturbed immune response in spleen, which is a major organ involved in B-cell maturation. Fcrls, which belongs to Fc receptor-like family possessing inhibitory and/or activating signaling motifs in B cell differentiation [32], were significantly down-regulated in response to HFD feeding. Similarly, microarray profiling carried out by Cui et al. in the spleen of C57BL/6 mice fed on a HFD also showed a decreased expression of Fc receptor [33]. Meanwhile, we observed abnormal expression of a few genes involved in immunoglobulin/B cell receptor signaling. Igkj4 showed significant up-regulation in HFD-fed mice, whereas the expression of Igkj1 were significantly decreased. Additionally, Reg3a and Reg3b, which play critical roles in acute-phase response [34, 35], were significantly down-regulated. The findings suggested that immune dysfunction was implicated in the spleen in response to 3 days of HFD feeding. Interestingly, neurotransmitter uptake related genes were significantly changed, such as solute carrier family 17 (sodium-dependent inorganic phosphate cotransporter), member 6(Slc17a6) which plays a key role in the transport of glutamate into synaptic vesicles before exocytotic release and the regulation of glutamate signaling [36].

Evidence has increasingly shown that a HFD regarded as a primary cause for numerous diseases including diabetes, hypertension, and steatohepatitis. However, few studies have been carried out to examine the effect of a HFD on the lung. To our surprise, the PCA results showed pronounced transcriptional changes in the lung and this is the first report to investigate the lung transcriptome profile after 3 days of HFD feeding. As the lung is a major site of immune regulation, our results revealed that many immune-related genes were significantly altered. Chemokine receptor Ccr9, which have proved to be important in the Treg cells mediated self-tolerance [37], was markedly down-regulated in HFD-fed mice. Sit1, a critical negative regulator of TCR-mediated signaling [38], showed significant down-regulation as well. The decreased expression of Ccr9 and Sit1 suggested an activated inflammatory response affected by HFD in the lung, which was in agreement with the previous study of the involvement of a HFD on lung inflammation [39]. In addition, we discovered decreased expression of CD8a in HFD-fed mice, which is important in cell-mediated immune defense and T-cell development [40]. Moreover, genes involved in T cell receptor signaling and immunoglobulin/ B cell receptor signaling were found to be significant altered. This study also revealed that circulatory system related genes were down-regulated by HFD in the lung. Nppa and Nppb are the precursor of atrial natriuretic peptide (ANP) and b-type natriuretic peptide (BNP), which have important physiological functions in the regulation of vascular tone and plasma volume [41]. ANP exhibits a protective role in the lung function in acute lung injury apart from its vasodilatory and natriuretic effects [42]. Intake of a HFD had been proved to make a slower pulmonary O2 uptake kinetics and attenuate microvascular blood flow and O2 delivery during the transition to moderate intensity exercise [43]. Therefore, we speculated that the decreased expression of Nppa and Nppb may contribute to the impaired exercise capacity in HFD-fed mice.

Conclusions

The simultaneous analysis of ten tissues following 3 days of high-fat feeding by RNA-seq technology revealed that the brain, spleen and lung had more pronounced transcriptional changes than other tissues. Dysregulation of peripheral and central immune response had been implicated in the early stage of the response to HFD exposure. Neurotransmission-related genes and circulatory system process related genes were markedly down-regulated in the brain and lung, respectively. These findings provide new insights for the deleterious effects of a HFD and contribute to the understanding of molecular mechanisms of exercise performance decrease induced by short-term high-fat feeding.

Abbreviations

ALB: 

Albumin

ALP: 

Alkaline phosphatase

ALT: 

Alanine aminotransferase

ANP: 

Atrial natriuretic peptide

ApoE: 

Apolipoprotein E

AST: 

Aspartate aminotransferase

BNP: 

b-type natriuretic peptide

Ca: 

Calcium

CD: 

Control diet

CK: 

Creatine kinase

Cl: 

Chlorine

CPM: 

Counts per million

Cr: 

Creatinine

CRP: 

C-reactive protein

CysC: 

Cystatin C

DBIL: 

Direct bilirubin

DEGs: 

Differentially expressed genes

HBDH: 

A-hydroxybutyric acid dehydrogenase

HCY: 

Homocysteine

HDL-C: 

High-density lipoprotein-cholesterol

HFD: 

High fat diet

IBIL: 

Indirect bilirubin

K: 

Potassium

LDH: 

Lactate dehydrogenas

LDL-C: 

Low-density lipoprotein-cholesterol

MAS: 

Molecule annotation system

Na: 

Sodium

PCA: 

Principle component analysis

RNA-seq: 

RNA sequencing

RPKM: 

Reads Per Kilobase of exon model per Million mapped reads

SOD: 

Superoxide dismutase

TBA: 

Total bile acid

TBIL: 

Total bilirubin

TP: 

Total protein

Treg: 

Regulatory T

UA: 

Uric acid

Declarations

Acknowledgements

Not applicable.

Funding

This work was supported by the National Science Foundation of China (Nos. 81373707, 81403447 and 81603520), the Natural Science Foundation of Guangdong Province, China (Nos. 2014A030313292, 2014A030310072 and 2016A030310084), the Science & Technical Plan of Guangzhou, Guangdong, China (No. 2014Y2-00504), the Administration of Traditional Medicine of Guangdong province (No. 20161063), the Fundamental Research Funds for the Central Universities (No. 21616315) and the Special Funds for the Cultivation of Guangdong College Students Scientific and Technological Innovation (No. pdjh2016b0093).

Availability of data and materials

All data generated or analysed during this study are included in this published article and its Additional file 1: Table S1 and Additional file 2: Table S2.

Authors’ contributions

XZ and YL conceived and designed the experiments. YX, WW, JC and PJ acquired the data. XF, XN and LC analyzed and interpreted the data. YX, WW and LC drafted the manuscript. XZ and HK revised the manuscript for important intellectual content. XZ and YL supervised the study. All authors were involved in the formulation of the research questions. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval

Animal experiments were approved by the Animal Care and Use Committee of Southern Medical University (Approval No.2013027).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Traditional Chinese Medicine, School of Medicine, Jinan University
(2)
School of Traditional Chinese Medicine, Southern Medical University
(3)
Experimental Animal Center, Southern Medical University
(4)
School of Chinese Medicine, Hong Kong Baptist University

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