Abstract

   A maternal low-protein (LP) diet during gestation and/or lactation
   results in metabolic syndrome in their offspring. Here, we investigated
   the effect of maternal LP diet during puberty and adulthood on the
   metabolic homeostasis of glucose and lipids in offspring. Female mice
   were fed with normal-protein (NP) diet or a LP diet for 11 weeks. Male
   offspring were then fed with a high-fat diet (NP-HFD and LP-HFD groups)
   or standard chow diet (NP-Chow and LP-Chow groups) for 4 months.
   Results showed that maternal LP diet during puberty and adulthood did
   not alter the insulin sensitivity and hepatic lipid homeostasis of
   their offspring under chow diet, but aggravated insulin resistance,
   hepatic steatosis, and hypercholesterolemia of offspring in response to
   a post-weaning HFD. Accordingly, transcriptomics study with offspring’s
   liver indicated that several genes related to glucose and lipid
   metabolism, including lipoprotein lipase (Lpl), long-chain acyl-CoA
   synthetase 1 (Acsl1), Apoprotein A1 (Apoa1), major urinary protein 19
   (Mup19), cholesterol 7α hydroxylase (Cyp7a1) and fibroblast growth
   factor 1 (Fgf1), were changed by maternal LP diet. Taken together,
   maternal LP diet during puberty and adulthood could disarrange the
   expression of metabolic genes in the liver of offspring and aggravate
   insulin resistance and hepatic steatosis in offspring fed a HFD.

   Keywords: maternal diet, offspring, low-protein diet, insulin
   sensitivity, hepatic steatosis, cholesterol

1. Introduction

   With alterations in eating patterns and sedentary habit, non-alcoholic
   fatty liver disease (NAFLD), type 2 diabetes mellitus (T2DM), obesity,
   and associated clinical features, such as hyperlipidemia and insulin
   resistance, are becoming more prevalent than ever
   [[50]1,[51]2,[52]3,[53]4]. Classically, the environment and genes are
   key factors associated with metabolic diseases [[54]4]. Recently,
   epidemiological studies have reported that maternal nutrition status,
   including over- and under-nutrition, rendered offspring vulnerable to
   metabolic diseases in adult life [[55]5,[56]6]. However, the mechanisms
   underlying the susceptibility in offspring from maternal exposure to
   malnutrition are far from clear.

   Dietary protein has extensive physiological and nutritional functions,
   including supplying amino acids for protein synthesis, and regulating
   food intake, lipid and glucose metabolism, immune functions, and bone
   metabolism [[57]7]. Therefore, investigating the consequences of
   dietary protein levels on human health is particularly important. In
   many low-income countries, the average dietary protein intake is below
   international recommendations [[58]8,[59]9]. Human studies have shown
   that dietary protein levels in the mother during pregnancy influence
   the health of their offspring [[60]10,[61]11]. Studies on mice
   indicated that maternal protein restriction during pregnancy alleviated
   systemic insulin resistance in offspring in response to a post-weaning
   high-fat diet (HFD) [[62]12,[63]13]. However, another study suggested
   that maternal protein restriction during gestation and lactation
   combined with a post-weaning HFD impaired insulin sensitivity and
   increased serum insulin levels in their offspring [[64]14].

   Most studies on maternal low-protein (LP) diet and offspring health
   have focused on gestation, as this period is the “key window” period
   for fetal development [[65]15], with maternal nutrition passed via the
   placenta to critical offspring organs, including the brain, liver, and
   adipose tissue [[66]16]. A recent review article summarized that
   maternal nutrition levels before gestation altered offspring phenotypes
   by changing oocytes maturity and quality [[67]17]. In a recent study,
   consuming a maternal LP diet one ovulatory cycle prior to mating led to
   cardiovascular abnormalities in offspring [[68]18]. Furthermore,
   another study showed that a maternal LP diet before pregnancy increased
   insulin sensitivity and reduced glucose concentration in their male
   offspring [[69]19]. Our previous study indicated that an LP diet during
   puberty and adulthood reduced primordial follicle activation in female
   mice [[70]20]. However, it is still unclear whether a maternal LP diet
   during puberty and adulthood affects the glucose and lipids metabolism
   of their offspring.

   In this study, F[0] female mice were fed with LP diet from 5- to
   16-week of age, followed by mating with normal male mice, and then were
   fed with a normal diet during pregnancy and lactation. The F[1] male
   offspring were fed a normal diet or a HFD. The results showed that a
   maternal LP diet during puberty and adulthood exerted no effect on
   glucose and lipids metabolism in offspring fed normal diets, but
   aggravated the insulin resistance and hepatic steatosis in offspring
   fed a HFD.

2. Materials and Methods

2.1. Animal Care and Experimental Design

   All animal procedures were reviewed and approved by the Animal Care and
   Use Committee of Sichuan Agricultural University. Four-week-old male
   and female mice (C57BL/6J) were obtained from Vital River laboratory
   Animal Technology Co. Ltd. (Beijing, China). Mice were kept in a
   pathogen-free room with 22 °C and 60% of stable temperature and
   humidity. After one-week adaptation, female mice were randomly grouped
   into two groups and were fed a low protein diet (LP, 8% Casein) or
   normal protein diet (NP, 20% Casein) until 16 weeks of age. Body weight
   and food intake were measured biweekly. These mice were then mated with
   normal male mice at 16-week of age. All mated female mice were fed a
   standard diet during gestation and lactation. F[1] male pups were
   weaned at 3 weeks of age and then were accessed to a standard chow diet
   (10% calorie from fat, Research Diet; NP-Chow and LP-Chow groups) or a
   high-fat diet (60% calorie from fat, Research Diet; NP-HFD and LP-HFD
   groups) from 4 weeks of age ([71]Figure 1A). Body weight was measured
   biweekly. Insulin tolerance test (ITT) was performed at 16 weeks of
   age. Blood glucose levels (Blood Glucose Strip, Yicheng, Beijing,
   China) were measured under fast condition at 20 weeks of age. Serum and
   tissues were then collected on the same day after blood glucose level
   measurement for further analysis.

Figure 1.

   [72]Figure 1
   [73]Open in a new tab

   Maternal low-protein diet during puberty and adulthood impaired insulin
   sensitivity of offspring under HFD condition. C57/BL6J female mice were
   fed with NP diet or a LP diet for 11 weeks until 16 weeks of age. These
   mice were then mated with normal-diet fed male mice. All female mice
   were fed with normal-diet during pregnancy and lactation. F1 male pups
   were weaned at 3 weeks of age and then were accessed to normal chow
   diet or high-fat diet from 4 weeks of age. (A) Breeding strategy to
   generate the first-generation offspring. (B) Body weight of the
   offspring (n = 10–14 for each group). (C) Blood glucose levels at
   harvest (n = 7–9 for each group). (D) Insulin tolerance test and (E)
   the area under curve (n = 7 for each group). (F) Insulin levels in the
   serum (n = 6 for each group). (G) Western blot bands of phosphorylation
   AKT in liver tissue. (H) The quantification of phosphorylation AKT
   levels. The mRNA levels of G6pc (I), Pepck (J), and Pgc1α (K) in the
   liver of offspring (n = 7–9 for each group). NP, normal protein diet;
   LP, low protein diet. Data were expressed as mean ± SE. * p < 0.05, **
   p < 0.01 LP vs. NP.

2.2. Serum Biochemical Analysis

   Serum levels of triglyceride (TAG) (Maccura biotechnology Co., Ltd.,
   Chengdu, China), total cholesterol (TC) (Maccura), high-density
   lipoprotein cholesterol (HDL-C) (Kehua Bio-Engineering, Shanghai,
   China), and low-density lipoprotein cholesterol (LDL-C) (Kehua) were
   analyzed on an automatic biochemical analyzer (7020, HITACHI, Tokyo,
   Japan) with their respective kits [[74]21]. Serum insulin level (ALPCO)
   and liver TAG content (Sigma, St. Louis, MO, USA) were analyzed with
   their respective commercial kits according to manufacturer’s
   instructions.

2.3. Liver Histological Analysis

   Liver tissue was fixed in paraffin or OCT embedding media for H&E
   staining and Oil-red O staining, respectively. The samples were then
   cut into 4 μm pieces (RM2016, Leica, Shanghai, China). For H&E
   staining, dehydrated sections were stained with hematoxylin, rinsed
   with double-distilled water (ddH[2]O), then stained with eosin. The
   slices were then dehydrated and put on slides using a neutral resin.
   For Oil-red O staining, the slices were dried on slides, fixed in 4%
   paraformaldehyde for 15 min, rinsed in PBS, and stained with Oil-red O
   staining solution. After that, the slides were washed in PBS again,
   stained with hematoxylin, rinsed in ddH[2]O, dried, and mounted with
   glycerogelatin. Images were obtained with imaging software on a
   microscope (TS100, Nikon, Tokyo, Japan) with a CCD (DS-U3, Nikon)
   (NIS-Elements F3.2, Nikon).

2.4. Insulin Tolerance Test

   Six-hour fasted mice were intraperitoneally injected with insulin (Novo
   Nordisk, Beijing, China) at the doses of 0.6 IU/kg (NP-Chow and LP-Chow
   groups) or 1.2 IU/kg (NP-HFD and LP-HFD groups) by intraperitoneal
   injection [[75]22]. Blood glucose levels were measured at 0, 15, 30,
   45, 60, and 90 min post insulin injection with a glucometer (Beijing
   Yicheng).

2.5. RNA Extraction and Real-Time PCR

   RNA extraction and real-time PCR were performed as previously reported
   [[76]23]. Briefly, liver powder was homogenized in TRizol reagent for
   RNA extraction (Invitrogen, Shanghai, China). The quality of RNA was
   analyzed by agarose gel and the concentration was measured with a
   spectrophotometer (NanoDrop 2000, Thermo Fisher Scientific, Waltham,
   MA, USA). 1 μg RNA was reverse-transcribed into cDNA with a
   reverse-transcription PCR kit according to the manufacturer’s
   instruction (Takara, Dalian, China). Real-time PCR was conducted on a
   quantitative-PCR machine (7500HT, ABI) with Power SYBR Green RT-PCR
   reagents (BioRad, Hercules, CA, USA). The conditions used for PCR were:
   95 °C for 10 min for 1 cycle, and then 40 cycles of 95 °C for 15 s
   followed by 60 °C for 1 min. The real-time PCR data was analyzed by the
   2^−ΔΔCt method with β-actin (Actb) as the reference. The sequences of
   the primers are listed in [77]Table S1.

2.6. Preparation of cDNA Libraries and Sequencing

   cDNA libraries were constructed using the Illumina NEBNext UltraTM RNA
   Library Prep Kit. Briefly, four liver samples of each group from NP-HFD
   and LP-HFD groups were used. mRNA was extracted and purified from total
   RNA using Poly-T oligo-attached magnetic beads and was fragmented by
   heating in NEBNext First Strand Synthesis Reaction Buffer. First and
   second strand cDNAs were then synthetized from the mRNA. For
   hybridization, DNA fragments were linked with NEBNext adaptors after
   end-reparation and single nucleotide A (adenine) addition. After this,
   an AMPure XP system (Beckman Coulter, Beverly, CA, USA) was used to
   select cDNA fragments of 250 base pairs (bp)-300 bp. Libraries
   quantification and qualification were tested using the Agilent
   Bioanalyzer 2100 and ABI StepOnePlus Real-Time PCR System. The Illumina
   platform was then used to sequence the cDNA library.

2.7. Quality Control and Reads Mapping

   To generate clean reads, low-quality reads in the raw data (more than
   20% bases quality was lower than 10) were filtered, and then reads with
   adaptors and unknown bases (n bases more than 5%) were removed. Clean
   reads were mapped onto a reference genome (mus musculus) using HISAT2
   (Hierarchical Indexing for Spliced Alignment of Transcripts, v2.0.5, UT
   Southwestern, Dallas, TX, USA).

2.8. Quantification and Analysis of Differentially Expressed Genes (DEGs)

   Read numbers mapped to genes were counted using featureCounts
   (v1.5.0-p3). Then, the FPKM (fragments per kilobase of exon model per
   million mapped fragments) of each gene was calculated to reflect gene
   expression level.

   DEGs between the two groups were analyzed using the DESeq2 R package
   (v1.16.1, European Molecular Biology Laboratory, Heidelberg, Germany).
   To control false discovery rates, p-values were adjusted using the
   Benjamini and Hochberg methods. Genes with corrected p-values less than
   0.05 were considered as differentially expressed.

2.9. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)
Enrichment Analysis of DEGs

   GO enrichment and KEGG pathways enrichment of the DEGs were analyzed
   using the clusterProfiler R package, and p-values of the GO terms less
   than 0.05 were considered significant.

2.10. Statistical Analysis

   SAS 9.3 software was used to analyze the data (SAS Institute Inc.,
   Cary, NC, USA). The data’s normality and homogeneity of variances were
   verified with a univariate test. An independent t-test was used to
   examine the differences between two groups with normal distribution
   data, whereas non-Gaussian and heterogeneous data were investigated
   using non-parametric analysis. The statistical difference of ITT was
   analyzed using repeated measures ANOVA. Results were presented as mean
   ± SE. p-value < 0.05 was considered significant.

3. Results

3.1. LP Diet Did Not Change the Food Intake and Body Weight in Female Mice

   Female mice were fed with LP diet or NP diet from 5- to 16-week of age
   ([78]Figure 1A). Results showed that the food intake was not changed by
   an LP diet, though the protein intake level was much lower in the LP
   group than that in the NP group ([79]Figure S1A,B). Moreover, the body
   weights were similar between the two groups ([80]Figure S1C).

3.2. Maternal LP Diet during Puberty and Adulthood Impaired Insulin
Sensitivity in Offspring Fed High-Fat Diet

   To investigate the effects of maternal protein restriction during
   puberty and adulthood on offspring metabolism, male F1 mice were fed a
   normal chow diet (NP-Chow and LP-Chow groups) or a high-fat diet
   (NP-HFD and LP-HFD groups) from 4 weeks old. Results showed that a
   maternal LP diet did not change the body weight and blood glucose
   levels of offspring under normal chow-diet or HFD ([81]Figure 1B,C).
   However, systemic insulin sensitivity in offspring was impaired by the
   maternal LP diet under offspring HFD condition, whereas no difference
   was observed under normal chow-diet condition when compared with the
   maternal NP diet ([82]Figure 1D,E). Moreover, the serum insulin level
   of the offspring from the LP group was higher than that of the
   offspring from the NP group under HFD conditions, whereas no difference
   was observed between the offspring from the LP and NP groups under
   normal chow-diet conditions ([83]Figure 1F). Furthermore, the exogenous
   insulin-induced AKT phosphorylation level in the offspring’s liver was
   impaired by the maternal LP diet compared with the NP group under
   offspring HFD condition ([84]Figure 1G,H). However, the expression of
   glucogenic genes G6pc, Pepck1, and Pgc1α in the liver were not changed
   by maternal protein restriction under neither normal chow-diet nor HFD
   ([85]Figure 1I). These results indicated that the maternal LP diet
   potentially aggravated insulin resistance in HFD-fed offspring.

3.3. Maternal Low-Protein Diet during Puberty and Adulthood Aggravated Lipids
Profiles in HFD-Fed Offspring

   The homeostasis of lipids is important for animal health. The weight of
   liver and fat tissues in offspring were not changed by the maternal LP
   diet ([86]Figure S2). However, liver triglycerides (TAG) content in
   offspring was increased by the maternal LP diet under HFD condition, as
   compared to the maternal NP diet ([87]Figure 2A,B). Moreover, serum
   contents of TC, LDL-C, and HDL-C were higher, whereas TAG content was
   lower, in the offspring of the LP-HFD group than those of the NP-HFD
   group. However, no differences in serum lipids profiles were observed
   between the LP-Chow and NP-Chow groups ([88]Figure 2C–F).

Figure 2.

   [89]Figure 2
   [90]Open in a new tab

   Maternal low-protein diet during puberty and adulthood aggravated
   hepatic steatosis of offspring under HFD condition. (A) Oil-red O
   staining and H&E staining with the liver of offspring. Bars equal to
   100 μm. (B) TAG content in the liver. (C) TAG content in the serum. (D)
   TC content in the serum. (E) LDL-C content in the serum. (F) HDL-C
   content in the serum. n = 7–9 for each group. Data were expressed as
   mean ± SE. NP, normal protein diet; LP, low protein diet. * p < 0.05,
   ** p < 0.01 LP vs. NP.

3.4. Transcriptome Profiling in Offspring’s Liver

   To identify the potential mechanism involved in the regulation of
   offspring’s lipid metabolism by a maternal LP diet during puberty and
   adulthood, we performed transcriptome analysis to screen for
   differentially expressed genes (DEGs) in liver from HFD-fed offspring.
   In total, 24,800 genes were detected ([91]Supplementary Table S2). With
   |log2 (fold changes)| > 0 and associated p-values < 0.05, a total of
   388 DEGs were identified, including 200 up-regulated genes and 188
   down-regulated genes, between the LP-HFD and NP-HFD groups ([92]Figure
   3A and [93]Supplementary Table S3). Of these, 62 DEGs were very
   significantly different between the two groups (p < 0.01)
   ([94]Supplementary Table S3). A heat map cluster analysis showed the
   distribution of DEGs ([95]Figure 3B).

Figure 3.

   [96]Figure 3
   [97]Open in a new tab

   Analysis of DEGs in the liver between LP-HFD and NP-HFD groups.
   Transcriptome analysis was performed with the liver of LP-HFD and
   NP-HFD offspring. RNA-seq libraries were prepared with total RNAs
   extracted from liver tissues, and sequencing was carried out on
   Illumina Hiseq platform. The final data were analyzed by the DEseq2 R
   software. (A) Heatmap clustering was analyzed with differentially
   expressed genes between the LP-HFD and NP-HFD groups. (B) The threshold
   for differential expression genes (cut-off = |log2 Fold Change| > 0 and
   p-value < 0.05) is indicated by dashed black lines. Solid red and green
   dots represent the up-regulated and down-regulated genes, respectively.
   n = 4 for each group.

3.5. Functional and Pathway Enrichment Analysis of DEGs

   GO functional and KEGG pathway enrichment analyses were performed with
   the DEGs between the LP-HFD and NP-HFD groups. Results showed that the
   DEGs were categorized into three groups (biological process (BP),
   cellular component (CC), and molecular function (MF)) based on GO
   enrichment analysis, and many of them were associated with lipids
   metabolism, such as long-chain fatty acid metabolic process, positive
   regulation of steroid metabolic process, regulation of lipid
   biosynthetic process, acetyl-CoA metabolic process, and cholesterol
   biosynthetic process in BP, lipid particle in CC, and steroid
   hydroxylase activity, cholesterol binding, long-chain fatty acid-CoA
   ligase activity, sterol transporter activity, lipid transporter
   activity, and lipoprotein particle receptor binding in MF ([98]Figure
   4A). Other high enriched GOs were positive regulation of vasculature
   development, cellular amino acid metabolic process, and bile acid
   biosynthetic process in BP, blood microparticle, melanosome, ruffle,
   cell leading edge, and pigment granule in CC, and carbohydrate binding,
   GTPase binding and carbohydrate transmembrane transporter activity in
   MF ([99]Figure 4A and [100]Supplementary Table S4).

Figure 4.

   [101]Figure 4
   [102]Open in a new tab

   GO and KEGG pathway enrichment analysis of DEGs. (A) GO annotation and
   classification based on biological process (BP), cellular component
   (CC), and molecular function (MF). (B) KEGG enrichment bubble chart.
   The color of the point indicates the q-value of the hypergeometric
   test, and the size represents their corresponding number of genes in
   their pathway.

   KEGG pathway enrichment analysis showed that the major enriched
   pathways of the DEGs were metabolic pathways, including PPAR signaling
   pathway, steroid hormone biosynthesis, primary bile acid biosynthesis,
   cholesterol metabolism, fatty acid biosynthesis, and insulin resistance
   ([103]Figure 4B). Other enriched pathways were complement and
   coagulation cascades, chemical carcinogenesis, prion diseases, protein
   processing in endoplasmic reticulum, cytokine-cytokine receptor
   interaction, and so on ([104]Figure 4B and [105]Supplementary Table
   S5).

3.6. Validation of the DEGs Linked to Lipid and Glucose Metabolism

   Transcriptome analysis identified several DEGs that were previously
   linked to lipid and glucose metabolism ([106]Table 1). These DEGs were
   interesting, as offspring mice in the LP-HFD group exhibited more liver
   fat accumulation and lower hepatic insulin sensitivity than the mice in
   the NP-HFD group ([107]Figure 1G,H and [108]Figure 2A,B). Therefore, we
   validated some of these DEGs using RT-qPCR. The selected genes were the
   regulator of glucose metabolism fibroblast growth factor 1 (Fgf1), the
   regulators of lipid and cholesterol metabolism including lipoprotein
   lipase (Lpl), long-chain acyl-CoA synthetase 1 (Acsl1), cholesterol 7α
   hydroxylase (Cyp7a1) and cell death inducing DFEA like effector A
   (Cidea), and an important regulator of both glucose and lipid
   metabolism major urinary protein 19 (Mup19). Interestingly, the
   expression of Lpl, Cyp7a1, and Cidea was upregulated, whereas the
   expression of Mup19, Fgf1, and Acsl1 were downregulated in the liver of
   the LP-HFD group compared to those in the NP-HFD group ([109]Figure 5).
   Additionally, the mRNA levels of other lipid metabolism genes were
   significantly upregulated by the maternal LP diet, including selectin P
   (Selp), StAR-related lipid transfer protein 6 (Stard6), and FMS-like
   tyrosine kinase 1 (Flt1) ([110]Figure 5). The expression patterns of
   these genes were consistent with the result of the transcriptome data.

Table 1.

   DEGs related to lipid and glucose metabolism.
   Ensembl ID Gene Description Log[2]FC p Value
   ENSMUSG00000078673 Mup19 major urinary protein 19 −4.46 0.0001
   ENSMUSG00000036585 Fgf1 fibroblast growth factor 1 −0.35 0.0068
   ENSMUSG00000028240 Cyp7a1 cytochrome P450, family 7, subfamily a,
   polypeptide 1 0.55 0.0131
   ENSMUSG00000024378 Stard4 StAR-related lipid transfer (START) domain
   containing 4 −0.32 0.0157
   ENSMUSG00000028195 Cyr61 cysteine rich protein 61 0.36 0.0265
   ENSMUSG00000032083 Apoa1 apolipoprotein A-I −0.24 0.0373
   ENSMUSG00000005514 Por P450 (cytochrome) oxidoreductase −0.28 0.0426
   ENSMUSG00000095320 Ccl21a chemokine (C-C motif) ligand 21A (serine)
   1.53 0.0059
   ENSMUSG00000029648 Flt1 FMS-like tyrosine kinase 1 −0.30 0.0295
   ENSMUSG00000024526 Cidea cell death-inducing DNA fragmentation factor,
   alpha subunit-like effector A 0.91 0.000
   ENSMUSG00000020644 Id2 inhibitor of DNA binding 2 −0.38 0.0305
   ENSMUSG00000015568 Lpl lipoprotein lipase 0.47 0.0201
   ENSMUSG00000031767 Nudt7 nudix (nucleoside diphosphate linked moiety
   X)-type motif 7 −0.53 0.0119
   ENSMUSG00000006517 Mvd mevalonate (diphospho) decarboxylase −0.46
   0.0135
   ENSMUSG00000057228 Aadat aminoadipate aminotransferase −0.29 0.0359
   ENSMUSG00000028011 Tdo2 tryptophan 2,3-dioxygenase −0.24 0.0407
   ENSMUSG00000034593 Myo5a myosin VA 0.76 0.0092
   ENSMUSG00000043461 Sptssb serine palmitoyltransferase, small subunit B
   3.34 0.0122
   ENSMUSG00000032231 Anxa2 annexin A2 −0.41 0.0134
   ENSMUSG00000021135 Slc10a1 solute carrier family 10 (sodium/bile acid
   cotransporter family), member 1 −0.25 0.0162
   ENSMUSG00000030382 Slc27a5 solute carrier family 27 (fatty acid
   transporter), member 5 −0.21 0.0252
   ENSMUSG00000041828 Abca8a ATP-binding cassette, sub-family A (ABC1),
   member 8a −0.34 0.0343
   ENSMUSG00000018796 Acsl1 acyl-CoA synthetase long-chain family member 1
   −0.21 0.0366
   ENSMUSG00000079608 Stard6 StAR-related lipid transfer (START) domain
   containing 6 −2.86 0.0378
   ENSMUSG00000020484 Xbp1 X-box binding protein 1 −0.41 0.0120
   ENSMUSG00000024292 Cyp4f14 cytochrome P450, family 4, subfamily f,
   polypeptide 14 −0.30 0.0039
   ENSMUSG00000042248 Cyp2c37 cytochrome P450, family 2. Subfamily c,
   polypeptide 37 −0.41 0.0073
   ENSMUSG00000092008 Cyp2c69 cytochrome P450, family 2, subfamily c,
   polypeptide 69 −2.07 0.0075
   ENSMUSG00000019768 Esr1 estrogen receptor 1 (alpha) −0.48 0.0276
   ENSMUSG00000054827 Cyp2c50 cytochrome P450, family 2, subfamily c,
   polypeptide 50 −0.41 0.0179
   ENSMUSG00000020258 Glyctk glycerate kinase −0.20 0.0437
   ENSMUSG00000002831 Plin4 perilipin 4 0.42 0.0030
   ENSMUSG00000028427 Aqp7 aquaporin 7 1.16 0.0238
   ENSMUSG00000025006 Sorbs1 sorbin and SH3 domain containing 1 0.27
   0.0285
   ENSMUSG00000016194 Hsd11b1 hydroxysteroid 11-beta dehydrogenase 1 −0.28
   0.0073
   ENSMUSG00000035780 Ugt2a3 UDP glucuronosyltransferase 2 family,
   polypeptide A3 −0.31 0.0139
   ENSMUSG00000039648 Kyat1 kynurenine aminotransferase 1 −0.29 0.0244
   ENSMUSG00000030711 Sult1a1 sulfotransferase family 1A,
   phenol-preferring, member 1 −0.30 0.0262
   ENSMUSG00000057425 Ugt2b37 UDP glucuronosyltransferase 2 family,
   polypeptide B37 −0.57 0.0362
   ENSMUSG00000039519 Cyp7b1 cytochrome P450, family 7, subfamily b,
   polypeptide 1 −0.80 0.0422
   ENSMUSG00000067144 Slc22a7 solute carrier family 22 (organic anion
   transporter), member 7 −0.91 0.0230
   ENSMUSG00000041698 Slco1a1 solute carrier organic anion transporter
   family, member 1a1 −1.64 0.0419
   ENSMUSG00000027938 Creb3l4 cAMP responsive element binding protein
   3-like 4 1.58 0.0128
   ENSMUSG00000038648 Creb3l2 cAMP responsive element binding protein
   3-like 2 −0.36 0.0444
   ENSMUSG00000078683 Mup1 major urinary protein 1 −1.96 0.0414
   ENSMUSG00000078687 Mup8 major urinary protein 8 −2.80 0.0039
   ENSMUSG00000096674 Mup15 major urinary protein 15 −2.03 0.0087
   ENSMUSG00000082644 Mup-ps19 major urinary protein, pseudogene 19 −1.24
   0.0280
   ENSMUSG00000020053 Igf1 insulin-like growth factor 1 −0.29 0.0461
   ENSMUSG00000024378 Stard4 StAR-related lipid transfer (START) domain
   containing 4 −0.32 0.0157
   [111]Open in a new tab

Figure 5.

   [112]Figure 5
   [113]Open in a new tab

   Validation of DEGs involved in lipid and glucose metabolism in the
   liver of NP-HFD and LP-HFD offspring. RT-qPCR was used to validate the
   RNA-seq data. The relative expression of Lpl (A), Cyp7a1 (B), Cidea
   (C), Mup19 (D), Fgf1 (E), Acsl1 (F), Selp (G), Stard6 (H), and Flt1
   (I). n = 7–9 for each group. Data were expressed as mean ± SE. * p <
   0.05; ** p < 0.01 LP-HFD vs. NP-HFD.

4. Discussion

   Many studies have explored the effects of a maternal LP diet during
   gestation and/or lactation on the development and metabolism of their
   offspring. In this study, we investigated the effect of a maternal LP
   diet during puberty and adulthood, but not during gestation or
   lactation, on hepatic insulin sensitivity and lipids metabolism in
   their offspring. Results showed that offspring from the LP group
   exhibited hypercholesterolemia, impaired hepatic insulin sensitivity,
   increased serum insulin level, and liver fat accumulation, as compared
   to NP group, in response to HFD. In addition, our transcriptome
   analysis identified several DEGs that were previously reported to
   regulate lipid and glucose metabolism.

   We observed that maternal LP consumption did not alter the body weight,
   or liver or white adipose tissue weight of offspring. A previous study
   also reported that maternal protein restriction before pregnancy did
   not change body mass, organ mass, glucose tolerance test, and glucose
   level in female offspring [[114]19]. In another study with Wistar rats,
   maternal protein restriction (80 g protein/kg) for 8 weeks before
   pregnancy increased plasma glucose and TC levels in offspring under
   postnatal normal diet conditions [[115]24]. Besides, when C57BL/6JBom
   female mice (8-week-old) were fed with a LP (8.4% protein) diet for 8
   weeks, their male offspring had more fat deposit than the control mice
   under postnatal normal diet conditions [[116]25]. The inconsistent
   results between different studies might be due to different animal
   models and/or feeding periods.

   Liver is one of the main target tissues for insulin action. Hepatic
   insulin resistance decreases liver response to insulin signaling by
   interrupting the insulin-induced inhibition of hepatic glucose
   production, which leads to hyperlipidemia, hyperglycemia, liver
   disease, and type 2 diabetes [[117]26,[118]27]. Here, we observed that
   LP-HFD offspring exhibited lower insulin sensitivity and higher insulin
   levels when compared with NP-HFD offspring, even though body weight,
   liver and white adipose tissue weight, or blood glucose level were not
   significantly different between the two groups. The reason why the
   LP-HFD offspring had similar blood glucose levels compared to the
   NP-HFD offspring might be that the LP-HFD offspring exhibited reduced
   hepatic insulin sensitivity but higher serum insulin level. The reason
   why serum insulin levels increased in LP-HFD mice will be investigated
   in a future study. Moreover, we showed that a maternal LP diet during
   puberty and adulthood decreased Fgf1 expression in the liver of
   post-weaning HFD-diet fed offspring. FGF1 is a hormone that functions
   as an insulin sensitizer. Previous studies reported that Fgf1-deficient
   mice developed insulin resistance under HFD conditions
   [[119]28,[120]29]. Critically, recombinant Fgf1 markedly reduced blood
   glucose levels in diabetic mice [[121]30]. Therefore, a maternal LP
   diet during puberty and adulthood exerted a potential reprogramming
   effect on hepatic insulin sensitivity in the offspring by regulating
   the expression of Fgf1.

   The liver is also an important hub for maintaining the balance of lipid
   metabolism. Lipids’ over-accumulation in the liver results in NAFLD
   pathogenesis [[122]31]. We observed that the hepatic TAG content was
   higher, whereas the serum TAG level was lower in LP-HFD mice than those
   in the NP-HFD mice. This result suggested that the livers of the LP-HFD
   offspring might have had stronger lipids synthesis, lower lipids
   secretion, or higher TAG uptake than the livers of the HFD-NP
   offspring. Furthermore, RNA-sequencing data from the livers of LP-HFD
   and NP-HFD mice revealed several DEGs related to lipid synthesis and
   glucose metabolism, such as Lpl, Acsl1, Cyp7a1, and Cidea. The changes
   of several DEGs were confirmed by RT-qPCR. In particular, LP-HFD
   offspring had significantly reduced hepatic Acsl1 mRNA level compared
   with NP-HFD offspring. ACSL1 is a major acyl-CoA synthetase in hepatic
   long-chain fatty acid processing and has a critical role in regulating
   fatty acid oxidation and uptake, triglyceride synthesis, and
   cholesterol metabolism [[123]32,[124]33]. Liver Acsl1 deficiency
   induced severely hepatic triglyceride accumulation and
   hypercholesterolemia, particularly accompanied with hyperlipidemia
   [[125]34]. Therefore, the change of Acsl1 expression might be a reason
   for the accumulation of TAG in the liver of LP-HFD mice.

   LPL is important for the clearance of blood TAG. In our study, the Lpl
   mRNA level was significantly increased in the liver of LP-HFD mice
   compared to the NP-HFD mice. This was consistent with the decreased
   level of TAG in the circulation of LP-HFD offspring. It was reported
   that Lpl gene mutations caused severe hypertriglyceridemia in humans
   [[126]35], whereas liver Lpl deletion elevated plasma TAG level in mice
   [[127]36]. Another study reported that Lpl overexpression in the liver
   exacerbated hepatic TAG accumulation and induced liver insulin
   resistance [[128]37]. Thus, the decrease in blood TAG might due to the
   increased expression of hepatic Lpl in the offspring of LP diet fed
   dams.

   Blood cholesterol level is important for health. Our study revealed
   that serum TC, LDL-C, and HDL-C levels were significantly increased in
   the LP-HFD offspring when compared with the NP-HFD offspring.
   Similarly, a previous study reported that a maternal LP diet during
   gestation resulted in hypercholesterolemia in offspring fed a high-fat
   and high-sucrose diet [[129]38]. It was reported that CYP7a1 was
   involved in cholesterol metabolism by converting cholesterol into bile
   acids [[130]39]. We observed that the expression of Cyp7a1 was
   upregulated in the liver of LP-HFD offspring compared to the control
   mice. This might be due to the feedback of higher hepatic cholesterol
   level in LP-HFD offspring. CIDEa is a cell death-inducing DNA
   fragmentation factor alpha-like effector (CIDE) family member and was
   shown to be an important regulator of lipid storage and lipid droplet
   formation in hepatocytes. Previous studies reported that Cidea
   deficiency reduced TAG and TC levels in HFD-induced obese mouse and
   ob/ob genetic obese mouse liver via suppressing de novo lipid synthesis
   genes expression [[131]40,[132]41]. Furthermore, hepatic Cidea
   overexpression enhanced hepatic lipid accumulation [[133]42]. When
   compared with our NP-HFD offspring, hepatic Cidea mRNA level was
   significantly increased in LP-HFD offspring. This could partly explain
   why the LP-HFD mice had higher lipid storage levels in the liver and
   serum cholesterol than the NP-HFD mice.

   Mup19 has a critical role in glucose and lipid metabolism and is a
   liver-specific protein belonging to the Mup proteins family [[134]43].
   A previous study reported that Mup19 was putatively associated with
   lipid deposition in the liver [[135]44], similar to Mup1, which reduced
   fat accumulation and insulin resistance in db/db mouse liver [[136]45].
   In our study, Mup19 expression was significantly down-regulated in the
   liver of LP-HFD offspring when compared with the NP-HFD group. Thus,
   MUP19 might also play a role in the regulation of offspring’s glucose
   and lipids metabolism in LP-HFD offspring. Further studies are required
   to explore the epigenetic mechanisms of how maternal protein
   restriction during puberty and adulthood affects offspring metabolism.
   In particular, the common transcription factors of the Fgf1, Acsl1,
   Lpl, Cidea, and Mup19 genes will be the main targets.

5. Conclusions

   A maternal low-protein diet during puberty and adulthood could
   aggravate hepatic steatosis and insulin resistance in HFD-fed
   offspring, and this might be mediated by the alteration of
   metabolism-related genes. This study is of interest and shows that a
   maternal low-protein diet during puberty and adulthood is harmful to
   the health of their offspring.

Supplementary Materials

   The following supporting information can be downloaded at:
   [137]https://www.mdpi.com/article/10.3390/nu14194057/s1, Figure S1:
   Effect of low protein diet on food intake, protein intake, and body
   weight in mothers; Figure S2: Effect of maternal low-protein diet on
   liver and white adipose tissue weight in the offspring; Table S1: The
   primers for RT-PCR; Table S2: The gene expression identified by
   transcriptome analysis; Table S3: The DEGs identified by transcriptome
   analysis; Table S4: GO analysis of the DEGs; Table S5: KEGG analysis of
   the DEGs.
   [138]Click here for additional data file.^ (4.2MB, zip)

Author Contributions

   B.F., D.W. and X.H. conceived and designed the experiments; X.H., Y.Z.
   (Yong Zhuo), D.J., Y.Z. (Yingguo Zhu), Z.F., L.C., Y.L., S.X., L.H.,
   Y.Z. (Yuanfeng Zou) and L.L. performed the experiments; B.F., X.H. and
   C.H. analyzed the data; X.H. wrote the paper; B.F. and D.W. revised the
   manuscript. All authors have read and agreed to the published version
   of the manuscript.

Institutional Review Board Statement

   The animal study protocol was approved by the Animal Care and Use
   Committee of Sichuan Agricultural University (protocol code
   MICE20160026, 16 March 2016).

Data Availability Statement

   The data presented in this study are available on request from the
   corresponding author.

Conflicts of Interest

   The authors declare that they have no conflict of interest with the
   contents of this article.

Funding Statement

   This study was supported by Fok Ying-Tong Education for Young Teachers
   in the Higher Education Institutions of China (171019) and Young
   Scientist Project of National Key R&D Program (SQ2022YFD1300010).

Footnotes

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References