https://orcid.org/0000-0001-6940-5581
Figures
Abstract
Background
Kidney developmental studies have demonstrated molecular pathway changes that may be related to decreased nephron numbers in the male 17 gestational days (17GD) low protein (LP) intake offspring compared to normal protein intake (NP) progeny. Here, we evaluated the HIF-1 and components of its pathway in the kidneys of 17-GD LP offspring to elucidate the molecular modulations during nephrogenesis.
Methods
Pregnant Wistar rats were allocated into two groups: NP (regular protein diet—17%) or LP (Low protein diet-6%). Taking into account miRNA transcriptome sequencing previous study (miRNA-Seq) in 17GD male offspring kidneys investigated predicted target genes and proteins related to the HIF-1 pathway by RT-qPCR and immunohistochemistry.
Results
In the present study, in male 17-GD LP offspring, an increased elF4, HSP90, p53, p300, NFκβ, and AT2 gene encoding compared to the NP progeny. Higher labeling of HIF-1α CAP cells in 17-DG LP offspring was associated with reduced elF4 and phosphorylated elF4 immunoreactivity in LP progeny CAP cells. In 17DG LP, the NFκβ and HSP90 immunoreactivity was enhanced, particularly in the CAP area.
Discussion and conclusion
The current study supported that the programmed reduced nephron number in the 17-DG LP offspring may be related to changes in the HIF-1α signaling pathway. Factors that facilitate the transposition of HIF-1α to progenitor renal cell nuclei, such as increased NOS, Ep300, and HSP90 expression, may have a crucial role in this regulatory system. Also, HIF-1α changes could be associated with reduced transcription of elF-4 and its respective signaling path.
Citation: Gomes JS, Sene LB, Lamana GL, Boer PA, Gontijo JAR (2023) Impact of maternal protein restriction on Hypoxia-Inducible Factor (HIF) expression in male fetal kidney development. PLoS ONE 18(5): e0266293. https://doi.org/10.1371/journal.pone.0266293
Editor: Christopher Torrens, Royal College of Surgeons in Ireland, IRELAND
Received: March 16, 2022; Accepted: April 13, 2023; Published: May 4, 2023
Copyright: © 2023 Gomes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Data Availability Statement: The miRNA sequencing data have been deposited into the Sequence Read Archive repository (accession: PRJNA694197) and Table S1 (Supplemental Information), and http://repositorio.unicamp.br/acervo/detalhe/1166350?guid=1641498025205&returnUrl=%2fresultado%2flistar%3fguid%3d1641498025205%26quantidadePaginas%3d1%26codigoRegistro%3d1166350%231166350&i=1.
Funding: This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, 05/54362-4, 12/18492-4, 13/12486-5 and 14/50938-8), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, 465699/2014-6).
Competing interests: The authors declare no conflicts of interest, financial or otherwise.
List of abbreviations: Ang II, Angiotensin II; AT1 and AT2 receptors, Type 1 and Type 2-angiotensin receptor; BSA, Bovine serum albumin; cDNA, complementary deoxyribonucleic acid; CEUA/UNESP, Institutional Ethics Committee; DAB—3,3’, diaminobenzidine tetrahydrochloride; DNA, deoxyribonucleic acid; elF4, E74-like factor; pelF4, phosphorylated E74-like factor; EP300, E1A binding protein p300; PCR, Polymerase chain reaction; GD, gestational days; GAPDH, Glyceraldehyde 3-phosphate dehydrogenase; HIF, Hypoxia-inducible factor; HSP90, heat shock protein 90; IDT, Integrated DNA Technologies; IGF, Insulin-like growth factor; LP, gestational low-protein intake; MC, mesenchymal cap; MM, Metanephros mesenchyme; Map2k2, mitogen-activated protein kinase kinase 2; miRNA (miR), a small non-coding RNA molecule; miRNA-Seq, miRNA transcriptome sequencing; mRNA, messenger ribonucleic acid; mTOR, mammalian target of rapamycin; NFκβ, nuclear factor kappa-light-chain-enhancer; NGS, Next Generation Sequencing; NO, Nitric oxide; NOS, nitric oxide synthetase; NOTCH1, single-pass transmembrane receptor protein; NP, normal protein intake; PHD, Prolyl-hydroxylase 3 enzyme; RIN, RNA Integrity Number; RT-qPCR, reverse transcription-polymerase chain reaction quantitative real-time; TGFα and TGFβ, α and Beta transformer growth factor; TGFβ-1, transforming growth factor-beta 1; TNF, Tumor necrosis factor; UB, ureter bud; U6 and U87, internal reference gene; VEGF, endothelial vascular growth factor; VHL E3, Von Hippel Lindau ubiquitin E3 ligase; 17-GD, 17th gestational day
Introduction
The adverse maternal intrauterine environment commitment, particularly maternal nutritional restriction, and psychological and placental ischemia, result in critical changes in the embryo/fetal organ structure and function disorders during developmental stages. Barker et al. (1989) were one of the first researchers to observe the relationship between birth weight and adult cardiovascular disease prevalence, interpreting the embryonic and fetal environments as a new component in the etiology of these diseases [1, 2]. From Barker’s hypothesis, Alan Lucas grounded fetal programming in 1991 [1–3]. So, epidemiological and experimental studies showed that insults during fetal/embryonic developmental stages led to long-term irreversible phenomena associated with an increasing predictive chance of developing chronic diseases in adulthood [3–10], including increased renal, cardiovascular, and metabolic risk disorders [11–15].
Rodent fetal programming studies confirm low birthweight prevalence is associated with an increased risk of arterial hypertension, heart disorders, chronic renal failure, and neuropsychological disorder in adulthood [5–10, 16, 17].
In response to a hostile intrauterine environment, it has been demonstrated that the fetus undergoes adaptations that accelerate the maturation and differentiation of tissues and organs to the detriment of cell proliferation, restricting fetus growth [18]. In this context, studies, including from our Laboratory, have shown evidence that disturbance in fetal programming results in low birth weight, fewer nephrons, and increased risk of renal disorders and hypertension in adulthood [1, 2, 5–10, 16].
Experimental studies from our lab and other authors have demonstrated lower birthweight, about 30% fewer nephrons from 17-GD (gestational day) to 16 weeks old offspring, associated with reduced renal salt excretion, chronic renal failure, and enhanced systolic pressure in 16 weeks of life or older, in gestational low-protein (LP) intake compared to standard protein intake (NP) offspring in adulthood [5–9, 19]. Huang and col (2020) also confirmed epigenetic control on embryo/fetal renal development suggesting a strict handle on gene expression, protein synthesis, tissue remodeling, and cell fates of the different kidney progenitor cells [20]. During renal ontogenesis, nephron stem cell renewal and differentiation are too controlled to generate adequate nephrons. As is known, the nephron number is defined by a closed interaction among ureter bud (UB) and metanephric mesenchyme (MM) progenitor cells [21–23]. MM cells proliferation and differentiation, constituting a mesenchymal cap (CM), is mediated by UB ends [25] and involves miRNA expression in a regulatory biological network during development.
Nephrogenesis involves fine control of gene expression, protein synthesis, tissue remodeling, cell renewal and differentiation, and fates of the kidney progenitor cells [20]. Recently we have demonstrated changes in metanephros miRNAs in the 17-GD protein-restricted male rat offspring [8, 9]. In parallel, it was observed that mRNA-encoding proteins related to renal development were 28% reduced in nephrogenic stem cells CM. These findings suggested that mRNA expression and protein disruption could have reduced proliferation and promoted early cell differentiation [8, 9]. However, information regarding the molecular mechanisms of the etiopathogenesis of nephrogenesis cessation is still scarce.
During embryo/fetal development, it has been demonstrated that reduced vessel density in the nephrogenic zone of the fetal kidney suggests a significant role for hypoxia in human kidney development. By the way, Hypoxia-Induced Factors (HIF) is identified virtually in the distal kidney tubules and collecting ducts and in a smaller amount in the peripheral cortex [24–26].
HIF-1α is a transcriptional factor from the helix-loop-helix-PAS family consisting of labile α and stable beta units to form a transcriptional complex [26, 27]. HIF-1α is hydroxylated and recognized by the VHL E3 compound (Von Hippel Lindau ubiquitin E3 ligase) at adequate tissue oxygen level, promoting proteasome degradation. Otherwise, in low oxygen tissue tension or the absence of VHL protein, HIF-1α escapes degradation [26, 27]. On the other hand, the activation of HIF-1α occurs in connection with tumor suppressor p53 mediated by ubiquitin E3 (MDM-2 murine double minute), leading to proteasome degradation, consequently decreasing p53 and reducing HIF-1 catabolism [28]. p53 function maintains the integrity of the genetic code by a set of reactions that activate repair proteins or block gene changes. HIF-1α is also inactivated by the action of the chaperone protein, HSP-90, by conformational changes. Previously, in kidneys from protein-restricted 17-GD male progeny, it was found that raised mTOR mRNA expression and protein 139% enhanced immunoreactivity in CAP cells [8, 9]. The PI3K/AKT signaling pathway, elF-4 factor, and mTOR activate the expression of HIF-1α in normal oxygen levels [29, 30]. Otherwise, the HIF-1α stimulates the synthesis of α and beta transformer growth factor (TGFα and TGFβ), as well as endothelial vascular growth factor (VEGF) and endothelial nitric oxide synthesize (NOS2). Previously, in 17-GD kidneys of gestational protein-restricted males, we found 30% enhanced TGFβ immunoreactivity in CAP cells associated with reduced VEGF mRNA expression [8, 9]. However, despite this strong interaction of HIF-1α with proteins involved in nephrogenesis, the participation of the HIF-1α signaling pathway in the changes observed in the offspring of animals whose mothers were submitted to protein restriction during the entire pregnancy is not clear. So, in the current study, we explored a new possibility linked to fetal kidney development disorder and specific HIF-1 pathway and its interactions in 17-GD LP offspring compared to NP progeny.
Material and methods
Animal and diets
The experiments were conducted as described in detail previously [3–8] on age-matched female and male rats of sibling-mated Wistar HanUnib rats (250–300 g) supplied by CEMIB/ UNICAMP, Campinas, SP, Brazil. The animal housing showed the right conditions for health and well-being during the experimental study. Immediately after weaning at three weeks of age, animals were kept under controlled temperature (25°C) and lighting conditions (07:00–19:00h) with free access to tap water and standard laboratory rodent chow (Purina Nuvital, Curitiba, PR, Brazil: Na+ content: 135 ± 3μEq/g; K+ content: 293 ± 5μEq/g), for 12 weeks before breeding. The Institutional Ethics Committee (#446-CEEA/UNESP) approved the experimental protocol, and the general guidelines established by the Brazilian College of Animal Experimentation were followed throughout the investigation. At 12 weeks of age, the animals were mated, and the day sperm were seen in the vaginal smear was designated day one of pregnancy. Then, dams were maintained ad libitum throughout the entire pregnancy on an isocaloric rodent laboratory chow with either normal protein [NP, n = 10] (17% protein) or low protein content [LP, n = 10] (6% protein). At 17 days of gestation (17DG), the dams were anesthetized by ketamine (75mg/kg) and xylazine (10mg/kg), and the uterus was exposed. The fetuses were randomly collected, including their position in the uterine horns, at the close time, at 17 gestational days for both experimental groups. An equal number of fetuses were taken from both uteri horn sides. The fetuses were removed and immediately euthanized by decapitation. The fetuses were weighed, and the tail and limbs were collected for sexing determination. In male fetuses from half of the dams (5 for each group), metanephros was isolated and collected for RT-Hpcr. The other half of the fetuses was immersion fixed for immunohistochemistry analyses. Each litter was considered n = 1 to prevent litter effects from biasing or data analysis, and only one pup per litter was used for each experiment.
Sexing determination
The sexing was determined by Sry conventional PCR (Polymerase Chain Reaction) sequence analysis. The DNA was extracted by enzymatic lysis with proteinase K and Phenol-Chloroform. The Master Mix Colorless—Promega was used for reaction with the manufacturer’s cycling conditions. The Integrated DNA Technologies (IDT) synthesized the primer following sequences below:
- Forward: 5’-TACAGCCTGAGGACATATTA-3’
- Reverse: 5’-GCACTTTAACCCTTCGATTAG-3’
It is essential to state here that sex hormones determine sexual phenotype dimorphism in the fetal-programmed disease model in adulthood by changes in the long-term control of neural, cardiac, and endocrine functions. Thus, the present study was limited and performed on male rats considering the findings above to eliminate interferences due to gender differences [7–9].
Total RNA extraction
Isolated two-kidney RNA pool was extracted from one fetus of each litter of the NP (17-GD, n = 5, from different mothers) and LP (17-GD, n = 5, from other mothers) offspring using Trizol reagent (Invitrogen), according to the instructions specified by the manufacturer. After centrifugation, the RNA remains in the aqueous phase were recovered through precipitation, carried out by washing isopropyl alcohol cycles. Total RNA quantity was determined by the absorbance at 260 nm using a nanoVue spectrophotometer (GE Healthcare, USA), and the RNA purity was assessed by the A 260 nm/A 280 nm and A 260 nm/A 230 nm ratios (acceptable when both ratios were >1.8). RNA Integrity was ensured by obtaining an RNA Integrity Number—RIN >8 with Agilent 2100 Bioanalyzer (Agilent Technologies, Germany).
Real-time quantitative PCR (mRNAs)
The High Capacity cDNA reverse transcription kit (Life Technologies, USA) was used for the cDNA synthesis. The genes expression study to NOS2, p53, HSP90, HIF-1α, NFκB, elF4, Ep300, TGFβ-1, mTOR, AT1a, AT1b, and AT2 in an isolated two-kidney pool was performed. The reaction of RT-qPCR was performed with SYBR Green Master Mix (Life Technologies, USA), using primers specific for each gene, provided by Exxtend (Campinas, SP, Brazil) (Table 1). The reactions were done in a total volume of 20μL using 5μL of cDNA (diluted 1:100), 10μL SYBER Green Master Mix (Life Technologies, USA), and 2.5μL of each specific primer (5nM). Amplification and detection were performed using the StepOnePlusTM Real-Time PCR System (Applied BiosystemsTM, USA). The cycling conditions were 95°C for 10 minutes, 45 cycles of 95°C for 15 seconds, and 60°C for 1 minute. Ct values were converted to relative expression values using the ΔΔCt method with offspring kidneys data normalized to GAPDH as a reference gene.
Analysis of the gene expression
The mRNA levels obtained for each gene (Table 1) was compared with the LP group concerning the appropriated NP group to analyze the discriminating expressions. Relative gene expression was evaluated using the comparative quantification method. All relative quantifications were assessed by DataAssist software v 3.0, using the ΔΔCT method. PCR efficiencies were calculated by linear regression from fluorescence increase in the exponential phase in the program LinRegPCR v 11.1 [7–9].
Immunohistochemistry
The fetus (n = 4 per group) was removed and immediately fixed in 4% paraformaldehyde (0.1 M phosphate, pH 7.4). After, they were washed in running water and followed by 70% alcohol until processed. The materials were dehydrated, diaphanized, and included in the paraplast (Sigma-Aldrich, United States). Five-micrometer-thick sections were deparaffinized and processed for immunoperoxidase. The slides were hydrated, and after being washed in PBS pH 7.2 for 5 minutes, the antigenic recovery was made with citrate buffer pH 6.0 for 25 minutes in the pressure cooker. The slides were washed in PBS, and endogenous peroxidase blockade with hydrogen peroxide and methanol was performed for 10 minutes in the dark. The sections were rewashed in PBS. For immunohistochemical analysis, sections were incubated with the primary antibody (Table 2) diluted in 1% BSA overnight at 4°C. Then, the slides were incubated with a blocking solution (5% skimmed milk powder in PBS) for 1 hour. After washing with PBS, the sections were exposed to the specific secondary antibody, diluted in 1% BSA, for 2 hours at room temperature and revealed with DAB (3,3’- diaminobenzidine tetrahydrochloride, Sigma—Aldrich CO®, USA). After successive washing with running water, the slides were counterstained with hematoxylin, dehydrated, and mounted with a coverslip using Entellan®. When the proteins studied had nuclear localization, the slices were not counterstained with hematoxylin to not cover the labeling. No immunoreactivity was seen in negative control experiments in which one of the primary antibodies was omitted (S1 Fig). The sections were analyzed using CellSens Dimension software from a photomicroscope (Olympus BX51). We quantified the percentage of the marked area in all CM of each metanephros surveyed (4NP and 4LP from different mothers).
Statistical analysis
Data was previously tested to assess the normality of distribution frequency and equality of variance by the Shapiro-Wilk and the Levene test. Data are expressed as the mean ± standard deviation (SD). The two groups were compared using Student’s t-test when data were normally distributed and the Mann-Whitney test when distributions were non-normal. Comparisons between the two groups through the weeks were performed using 2-way ANOVA for repeated measurements test, in which the first factor was the protein content in the pregnant dam’s diet and the second factor was time. The mean values were compared using Tukey´s post hoc analysis when the interaction was significant. The significance level was 5%. However, the Welch test was performed in situations of heteroscedasticity when a large variance was observed between the groups studied. Significant differences in the transcriptome were detected using a moderated t-test. GraphPad Prisma v. 01 software (GraphPad Software, Inc., USA) was used for statistical analysis and graph construction.
Results
The male 17-GD LP offspring showed a significant reduction in body mass compared to the age-matched NP group associated with unchanged placental weight (Fig 1). Additionally, in the 17-GD LP animals, the nephrogenic cortical area was 31% reduced (LP = 27.5 ± 1 vs. NP = 58.1 ± 1.6, n = 5 of each, p<0.0001) and the medullar 34% enhanced (LP = 72.5 ± 1 vs. NP = 42 ± 1.6, n = 5 of each, p<0.0001) when compared to that observed in NP group. The CMs presented an increase in both areas (103%) and several Six2 positive cells (32%) in the 21GD LP kidneys.
Mean ± SD, *p<0.05.
Gene expression analysis
Fig 2 shows the mRNA expression of the elected predicted gene expression analysis in metanephros of males in 17-DG. We observed a significant increase in elF4, HSP90, p53, p300, NFκβ, and AT2 compared to age-matched NP. Regarding discreet enhancement of HIF-1α encoding in the LP offspring was no observed statistical significance (p = 0.053) compared to NP progeny. The presentation of mRNAs encoding NOS2, AT1a, and AT1b, although AT2 receptors have been different between groups, was not altered in LP animals compared to control animals (Fig 2).
The expression was normalized with GAPDH. The authors established a cutoff point variation of 1.3 (upwards) or 0.65 (downwards), and data are expressed as fold change (mean ± SD, n = 5) concerning the control group. * p≤0.05: statistical significance versus NP.
Immunohistochemistry
The HIF-1α immunostaining was widely shown in cortical and medullar metanephros’s areas. The immunostaining was preferentially located in the nuclear site associated with low cytosolic intensity (Fig 3). The CAP cell staining presents higher labeling in 17-DG LP offspring than in age-matched NP offspring (t = 0,9669, df = 85, p = 0.0001). The elF4 immunoreactivity was dispersed in the cytosol of metanephros cell types (Fig 4). A significant elF4 immunostaining reduction was observed in LP progeny kidney tissue and CAP cells (t = 5.838, df = 101, p = 0.0001). The phosphorylated form of elF4 staining was also decreased in the CAP cells (t = 7,486, df = 89, p = 0.0001) (Fig 4). In NP metanephros offspring, the HSP90 protein is located in a negligible reactivity in the cytosol of different cells. Otherwise, endothelial cells showed higher immunostaining to HSP90 (Fig 5). Also, the immunoreactivity for HSP90 is higher in different metanephros nuclear cells from LP offspring (t = 6,770, df = 115, p = 0.0001). The HSP90 quantification showed an increased stain in the LP progeny CAP area compared to the NP offspring (Fig 5). In control animals (NP), the NFκβ staining is weak in all metanephric tissue (Fig 6). However, in 17DG LP, the NFκβ and nuclear immunoreactivity is significantly enhanced in all cells (t = 2,822, df = 117, p = 0.0056). Also, the percentage of labeled CAP area increased considerably in 17-DG LP (Fig 6). Although significantly increased in LP progeny metanephros, the NOS2 immunostaining occurred weakly throughout all metanephros extent (t = 4,482, df = 126, p = 0.009, Fig 7). The VEGF immunoreactivity was reduced in the LP CAP area compared to NP progeny (Fig 8).
The graphics represent the HIF-1α immunostained area/CAP area ratio in male 17-DG LP compared to age-matched NP progeny. Each histological section’s five cortical and medullar fields were analyzed, and the average immunoreactivity reading was determined. Data are presented as scatter dot plots on the left; unpaired Welch’s t-test was used for data analysis. UB: ureter bud and V: vesicle. Mean ± SD, ***p<0.0001.
The graphics represent the elF4E and pelF4E immunostained area/CAP area ratio in male 17-GD LP compared to age-matched NP progeny. Each histological section’s five cortical and medullar fields were analyzed, and the average immunoreactivity reading was determined. Data are presented as scatter dot plots on the left; unpaired Welch’s t-test was used for data analysis. UB: ureter bud and V: vesicle. Mean ± SD, ****p<0.0001.
The graphics represent the HSP90 immunostained area/CAP area ratio in male 17DG LP compared to age-matched NP progeny. Each histological section’s five cortical and medullar fields were analyzed, and the average immunoreactivity reading was determined. Data are presented as scatter dot plots on the left; unpaired Welch’s t-test was used for data analysis. UB: ureter bud and SV: S-shaped vesicles. Mean ± SD, ****p<0.0001.
The graphics represent the NFκβ immunostained area/CAP area ratio in male 17DG LP compared to age-matched NP progeny. Each histological section’s five cortical and medullar fields were analyzed, and the average immunoreactivity reading was determined. Data are presented as scatter dot plots on the left; unpaired Welch’s t-test was used for data analysis. UB: ureter bud. Mean ± SD, ****p<0.0001.
The graphics represent the NOS2 immunostained area/CAP area ratio in male 17DG LP compared to age-matched NP progeny. Each histological section’s five cortical and medullar fields were analyzed, and the average immunoreactivity reading was determined. Data are presented as scatter dot plots on the left; unpaired Welch’s t-test was used for data analysis. UB: ureter bud. Mean ± SD, ****p<0.0001.
The graphics represent the VEGF immunostained area/CAP area ratio in male 17DG LP compared to age-matched NP progeny. Each histological section’s five cortical and medullar fields were analyzed, and the average immunoreactivity reading was determined. Data are presented as scatter dot plots on the left; unpaired Welch’s t-test was used for data analysis. UB: ureter bud and V: vesicle. Mean ± SD, ****p<0.0001.
Discussion
Assuming that chronic diseases in adulthood result from embryo-fetal programming, studying triggering factors for this gestational programming is very relevant. Nephrogenesis depends on adequate progenitor cells’ self-renewal, survival, proliferation, and differentiation capacity during perinatal kidney development. Prior studies demonstrated that epigenetic factors drive renal growth-regulating gene expression of proteins involved in critical signaling developmental pathways [7–9, 31–33]. Recently, we identified global miRNA and elected target mRNA changed expression in gestational low-protein intake 17-GD male kidney offspring [7–9]. The current study explores an additional and new path linked to fetal kidney programming ontogenesis by evaluating and predicting target genes of the specific proteins related to the HIF-1 pathway in the maternal low protein intake model (LP progeny) compared to NP offspring.
The cellular mechanisms responsible for the impairment of renal outcome in programmed animals’ show a complex network of protein and miRNA interactions involved in renal organogenesis. Previous studies reveal that maternal caloric and protein restriction reduced the number of nephrons observed in fetal and adult life, probably associated with fewer progenitor cells [5, 6, 10, 34]. Therefore, the HIF-1α signaling pathway was evaluated based on the prior observation of altered mTOR, TGFβ, and VEGF pathways in metanephros of programmed animals at the same experimental design [7–9].
Preliminary data showed that a low-protein intake during embryonic development in rats increases miR-199a-5p expression, followed by enhanced TGFβ-1 and mTOR encoding in metanephros from 17-DG fetuses compared to age-matched NP progeny [9]. mTOR signaling plays a central role in sensing response to intracellular nutrient availability [35]. In this way, we may suppose that increased mTOR expression promotes activation of the PI-3K/AKT path, subsequently inducing the expression of HSP90, contributing to the stabilization and translocation of HIF-1α to the nuclei of the cells. A study of fetal baboon kidneys in restricted caloric-protein dams confirmed the mTOR signaling pathway’s central role in reducing the nephron number in this model [35]. Although widely known that the mTORC1 path has an essential function in embryo/fetal development, its role remains unclear in nutritional stress conditions [36]. Hudson et al., 2002 [37] have established a strict relationship between increased mTOR pathway activity and HIF-1α stimuli in cell cultures.
On the other hand, findings show that a fall in HSP90 expression decreases tissue HIF-1α levels, associated with reduced transposition to the cell nuclei and target genes binding [38–42]. However, the current study demonstrated an elevated HSP90 metanephros protein level in 17-GD LP progeny that may reduce the HIF-1α catabolism, accelerating its transcriptional activity [42]. In addition, the high expression of HSP90 also may promote a decrease in VHL protein, reducing the ubiquitination and degradation of HIF-1α and consequently elevating its transcriptional activity. Studies have demonstrated that components of the HIF-1α and NFκβ signaling pathways share genetic targets. van Uden et al. (2008) showed that stimulation of NFκβ by TNFα also led to an increased level of HIF-1α mRNA encoding [40, 43]. Under different circumstances, these findings confirm the results of the current study in 17-DG LP compared to NP metanephros. However, the maternal low-protein LP offspring did not show an increase in NFκβ mRNA expression in the present study.
As previously mentioned, p53 plays a primary role in maintaining the integrity of the genetic code. However, the relationship between the tumor suppressor p53 and HIF-1α is still unclear. HIF-1α and p53 need to bind Ep300, which allows the specific response of HIF-1α, reducing its hydroxylation and enhancing its transposition to the nuclei of cells for their respective transcriptional activities. Likewise, the reduction of p53 would cause an increase in the stability of HIF-1α and its transcriptional activity [28, 44–52].
So, elevated levels of p53 encoding may accelerate the metanephric mesenchymal progenitor cell apoptosis process. However, the present study demonstrated an increased p53 mRNA associated with increased HIF-1α, suggesting an opposite and positive relationship with the previously described negative regulation of HIF-1α by p53. Therefore, the relationship between p53 and HIF-1α in this experimental model needs further clarification.
HIF-1α is activated by several growth factors and cytokines, including IGF-1, IGF-2, NFκβ, and angiotensin II (Ang II) [7–9, 53–56]. Signaling pathways modulated by growth factors, such as PI-3k/AKT/PKB and MAPK pathways, also stabilize and activate HIF-1α expression. Conversely, some authors argue that PI-3k/AKT signaling is not involved in the induction of HIF-1α in abnormal O2 tissue tension. Thus, the function of this activation has not yet been precisely established [55, 57, 58].
Angiotensin II acts differently at the cell level, stimulating cell growth and hypertrophy or inducing apoptosis. It has been demonstrated that NOS-2 influences enhanced HIF-1α levels. On the other hand, the type-1 Ang II receptor promotes enhanced blood pressure in parallel with intracellular increasing nitric oxide production by NOS activity, which counter-regulated some cellular effects of Ang II [59–62]. In the current study, the enhanced HIF-1α levels are also associated with high AT2 receptor mRNA expression.
Additionally, authors have demonstrated that in environments with elevated concentrations of NOS and NO, the stabilization of HIF-1α occurs. In an opposite situation of a low concentration of NO, there is a significant decrease in the HIF-1α levels [60–64]. It is believed that degradation of HIF-1α would be secondary to inhibiting mitochondrial respiration, which leads to local changes in oxygen activating the prolyl-hydroxylase (PHD) enzyme, which maintains increased HIF-1α tissue activity [60–64]. The present study demonstrated a high NOS-2 expression in the kidney of 17-GD low-protein diet offspring compared to NP offspring. Based on these findings, we could suggest that the uterine environment to a low-protein diet exposition would stabilize cytoplasmatic HIF-1α levels, favoring its migration to the cell nucleus.
The low protein intake in the murine model has been demonstrated to be associated with miR 199a-5p expression and activation of the WNT pathway, which regulates nephron development [7–9]. Considering these findings, WNT stimuli may modulate VEGF mRNA encoding and protein synthesis in the fetal LP kidneys. VEGF signaling is a downstream event of the mTOR pathway. However, the current study did not confirm the increased VEGF mRNA encoding. Kitamoto and col (1997) studied in vivo the role of VEGF in murine newborns’ kidney development by blocking VEGF activity, demonstrating a reduced nephron number and abnormal glomeruli development [65]. Thus, in the current study, unchanged VEGF mRNA expression in LP 17-GD renal tissue could be an additional factor that promotes reduced nephron units in the LP progeny [66].
Considering the evidence mentioned above indicating mTOR acting simultaneously as a stimulator of HIF-1α and an inhibitor of elF4 expression, we may hypothesize that decreased transcriptional elF4 expression contributes to reducing the stabilization of HIF-1α and its nuclear effects. The current study results align with the increased mTOR levels in fetal programming studies, contributing to elevated HIF-1α expression and its cellular effects [7–9, 34].
In conclusion, the current study supported the hypothesis that reduced nephron number in the 17-DG offspring, programmed by gestational low-protein intake, may, at least partially, be related to changes in the HIF-1α signaling path. So, factors that facilitate the cytoplasmatic levels and the transposition of HIF-1α to progenitor renal cell’s nucleus, such as increased expressions of NOS, Ep300, and HSP90, may have a crucial role in this regulatory system. The HIF-1α changes could be associated with a reduction in the transcription factor elF-4 and its respective signaling path. Although unexpected, the elevated expression of p53 may be involved in the apoptotic process, culminating with reduced proliferation and early cell differentiation in the current experimental model (Fig 9). Speculatively, we may suppose that an early differentiation of progenitor CAP cells associated with decreased cell proliferation culminates with reduced functional nephron units in the male offspring of rats submitted to severe gestational protein restriction. The present study took place in fetuses on 17-GD. The authors acknowledge that kidney development is a dynamic that occurs both pre- and postnatal in the rat. Taking into account the alterations in renal development already observed immediately after the birth of the offspring, we assume that the renal cellular and molecular alterations, particularly in the LP group, may be closely related to the reduction in the number of nephrons in this offspring. However, selecting an isolated gestational point may only partially reflect changes in renal development observed after a while.
The figure depicted the nephron onset impairment in 17DG fetuses’ kidneys, programmed by gestational low-protein intake, related to canonical pathways alterations in the HIF-1α signaling pathway. Expressions of NOS, Ep300 potentiate the transposition of HIF-1α to the mesenchymal cell’s nucleus, and HSP90, possibly associated with a reduction in the transcription factor elF-4 and proteins of their respective signaling pathways. These results may suggest an early maturation process of renal cells, inhibition of nephron progenitor cell division, and reduction of renal functional units in the offspring of rats submitted to severe gestational protein restriction.
Supporting information
S1 Fig. This Figure shows the representative immunohistochemistry negative control images.
https://doi.org/10.1371/journal.pone.0266293.s002
(TIF)
References
- 1. Barker DJ, Osmond C, Golding J, Kuh D, Wadsworth ME. Growth in utero, blood pressure in childhood and adult life, and mortality from cardiovascular disease. BMJ. 1989; 298(6673):564–567. pmid:2495113
- 2. Barker DJP, Osmond C, Winter PD, Margetts B, Simmonds SJ. Weight in infancy and death from ischaemic heart disease. Lancet. 1989; 2:577–580. pmid:2570282
- 3. Lucas A. Symposium: The Effects of Childhood Diet on Adult Health and Disease Psychological Influences on Childhood Diet 1. J Nutr. 1998; 128: 401S–406S. https://doi.org/10.1093/jn/128.2.401S
- 4. Langley-Evans SC. Developmental programming of health and disease. Proc Nutr Soc. 2006; 65: 97–105. https://doi.org/10.1079/pns2005478 pmid:16441949.
- 5. Mesquita FF, Gontijo JA, Boer PA. Expression of renin-angiotensin system signaling compounds in maternal protein-restricted rats: effect on renal sodium excretion and blood pressure. Nephrol Dial Transplant 2010a; 25, 380–388.
- 6. Mesquita FF, Gontijo JAR, Boer PA. Maternal undernutrition and the offspring kidney: from fetal to adult life. Braz J Med Biol Res 2010b; 2010b; 43, 1010–1018. pmid:21049242
- 7. Sene LB, Mesquita FF, de Moraes LN, Santos DC, Carvalho R, Gontijo JA, et al. Involvement of renal corpuscle microRNA expression on epithelial-to-mesenchymal transition in maternal low protein diet in adult programmed rats. PLoS One. 2013; 19: e71310. pmid:23977013.
- 8. Sene LB, Rizzi VHG, Gontijo JAR, Boer PA. (2018). Gestational low-protein intake enhances whole-kidney miR-192 and miR-200 family expression and epithelial-to-mesenchymal transition in rat adult male offspring. J Exp Biol 2018; 221:jeb171694. pmid:29789348
- 9. Sene LB, Scarano WR, Zapparoli A, Gontijo JAR, Boer PA. Impact of gestational low-protein intake on embryonic kidney microRNA expression and in nephron progenitor cells of the male fetus. PLoS One 2021; 16:e0246289. pmid:33544723
- 10. Lamana GL, Ferrari ALL, Gontijo JAR, Boer PA. Gestational and breastfeeding low-protein intake on blood pressure, kidney structure, and renal function in male rat offspring in adulthood. Front. Physiol 2021; 12:658431 pmid:33967827
- 11. Langley-Evans SC, Welham SJ, Jackson A. Fetal exposure to a maternal low protein diet impairs nephrogenesis and promotes hypertension in the rat. Life Sci. 1999; 64(Issue 11): 965–974. pmid:10201645
- 12. Gluckman PD, Hanson MA. The developmental origins of the metabolic syndrome. Trends Endocrinol Metab. 2004;15(4):183–187. pmid:15109618
- 13. McMullen IC, Adam CL, Mühlhäusler BS. Early origins of obesity: Programming the appetite regulatory system. J Physiol. 2005; 565(1):9–17.
- 14. Burdge GC, Hanson MA, Slater-Jefferies JL, Lillycrop KA. Epigenetic regulation of transcription: A mechanism for inducing variations in phenotype (fetal programming) by differences in nutrition during early life? Br J Nutr. 2007;97(6):1036–1046. pmid:17381976
- 15. Hanson MA, Gluckman PD. Developmental origins of health and disease: New insights. Basic Clin Pharmacol Toxicol. 2008; 102(2):90–93. pmid:18226060
- 16. Mariano VS, Boer PA, Gontijo JAR. Fetal Undernutrition Programming, Sympathetic Nerve Activity, and Arterial Hypertension Development. Front. Physiol 2021; pmid:34867434
- 17. Grigoletti-Lima GB; Lopes MG; Barufi Franco AT; Damico AM; Boer PA; Gontijo JAR. Severe Gestational Low-Protein Intake Impacts Hippocampal Cellularity, Tau, and Amyloid- Levels, and Memory Performance in Male Adult Offspring: An Alzheimer-Simile Disease Model? J Alzheimer’s Dis Rep, 2022; 6(1):17–30.
- 18. Fall CHD. Fetal Programming and the Risk of Noncommunicable Disease. Indian J Pediatr. 2013;80(S1):13–20. Available from: http://link.springer.com/10.1007/s12098-012-0834-5. pmid:22829248
- 19. Schreuder M, Delemarre-Van De Waal H, Van Wijk A. Consequences of intrauterine growth restriction for the kidney. Kidney Blood Press Res 2006; 29, 108–125. pmid:16837795
- 20. Huang B, Liu Z, Vonk A, Zeng Z, Li Z. Epigenetic regulation of kidney progenitor cells. Stem Cells Transl Med 2020; 9(6): 655–660. pmid:32163228
- 21. Grobstein C. Inductive interaction in the development of the mouse metanephros. J. Exp. Zool. 1955; 130: 319–339.
- 22. Saxen L, Sariola H. Early organogenesis of the kidney. Pediatr. Nephrol 1987; 1: 385–392. https://doi.org/10.1007/BF00849241 pmid:3153305.
- 23. Pan C, Chen H, Wang L, Yang S, Fu H, Zheng Y, et al. Down-regulation of MiR-127 facilitates hepatocyte proliferation during rat liver regeneration. PLoS One 2012; 7: 1–10. pmid:22720056
- 24. Gerosa C, Fanni D, Faa A., et al. Low vascularization of the nephrogenic zone of the fetal kidney suggests a major role for hypoxia in human nephrogenesis. Int Urol Nephrol 2017; 49, 1621–1625 (2017). https://doi.org/10.1007/s11255-017-1630-y.
- 25. Phua YL, Chu JYS, Marrone AK, Bodnar AJ, Sims‐Lucas S, Ho J. Renal stromal miRNAs are required for normal nephrogenesis and glomerular mesangial survival. Physiol Rep 2015; 3(10). PII: e12537. pmid:26438731
- 26. Gunaratnam L, Bonventre JV. HIF in Kidney Disease and Development. J Am Soc Nephrol 2009; 20(9): 1877–1887. pmid:19118148
- 27. Jochmanová I, Chunzhang Y, Zhengping Z, Karel P. Hypoxia-Inducible Factor Signaling in Pheochromocytoma: Turning the Rudder in the Right Direction. J Nat Cancer Inst 2013; 105(17): 1270–1283. pmid:23940289
- 28. Ashcroft M, Yoichi T, Vousden KH. Stress Signals Utilize Multiple Pathways To Stabilize P53. Mol Cell Biol 2000; 20(9): 3224–3233. pmid:10757806
- 29. Yee KM, Powis G. Passing the Baton: The HIF Switch. Trends Biochem Sci 2012; 37(9): 364–72. pmid:22818162
- 30. Powis G, Lynn Kirkpatrick. Hypoxia-Inducible Factor-1α as a Cancer Drug Target. Mol Cancer Ther 2004; 3(5): 647–54.
- 31. Lv X, Mao Z, Lyu Z, Zhang P, Zhan A, Wang J, et al. miR181c promotes apoptosis and suppresses the proliferation of metanephric mesenchyme cells by targeting Six2 in vitro. Cell Biochem Funct 2014; 32: 571–579.
- 32. Marrone AK, Ho J. MicroRNAs: potential regulators of renal development genes that contribute to CAKUT. Pediatr Nephrol. 2014; 29: 565–574. pmid:23996519
- 33. Wei J, Zhang Y, Luo Y, Wang Z, Bi S, Song D, et al. Aldose reductase regulates miR-200a-3p/141-3p to coordinate Keap1-Nrf2, Tgf1/2, and Zeb1/2 signaling in renal mesangial cells and the renal cortex of diabetic mice. Free Rad Biol. Med 2014; 67: 91–10.2.
- 34. Vaccari B, Mesquita FF, Gontijo JAR, Boer PA. Fetal kidney programming by severe food restriction: effects on structure, hormonal receptor expression, and urinary sodium excretion in rats. J. Renin Angiotensin Aldosterone Syst 2015; 16: 33–46. pmid:23482371
- 35. Nijland MJ, Schlabritz-loutsevitch NE, Hubbard GB, Nathanielsz PW, Cox LA. Non-human primate fetal kidney transcriptome analysis indicates the mammalian target of rapamycin (mTOR) is a central nutrient-responsive pathway. J. Physiol 2007; 579, 643–656.
- 36. Gürke J, Schindler M, Pendzialek SM, Thieme R, Grybel KJ, Heller R, et al. Maternal diabetes promotes mTORC1 downstream signaling in rabbit preimplantation embryos. Soc Reprod Fertil 2016; 1–51.
- 37. Hudson CC, Liu M, Chiang GG, Otterness DM, Loomis DC, Fiona Kaper F, et al. Regulation of Hypoxia-Inducible Factor 1α Expression and Function by the Mammalian Target of Rapamycin. Mol Cell Biol 2002; 22(20): 7004–7014.
- 38. GradinK , McGuire J, Wenger RH, Kvietikova I, Whitelaw ML, Toftgård R, et al. Functional Interference between Hypoxia and Dioxin Signal Transduction Pathways: Competition for Recruitment of the Arnt Transcription Factor. Mol Cell Biol 1996; 16(10): 5221–5231. pmid:8816435
- 39. Minet E Y, Mottet D, Michel G, Roland I, Raes M, Remacle J, et al. Hypoxia-Induced Activation of HIF-1: Role of HIF-1 K -Hsp90 Interaction. 1999; 460: 251–256.
- 40. Hur E, Kim HH, Choi SM, Kim JH, Yim S, Kwon HJ, et al. Reduction of Hypoxia-Induced Transcription through the Repression of Hypoxia-Inducible Factor-1α/Aryl Hydrocarbon Receptor Nuclear Translocator DNA Binding by the 90-KDa Heat-Shock Protein Inhibitor Radicicol. Mol Pharmacol 2002; 62(5): 975–982.
- 41. Isaacs JS, Jung Y-J, Mimnaugh EG, Martinez E, Cuttitta F, Neckers LM. Hsp90 Regulates a von Hippel Lindau-Independent Hypoxia-Inducible Factor-1 Alpha-Degradative Pathway. J Biol Chem 2002; 277(33): 29936–29944. pmid:12052835
- 42. Katschinski DM, Le L, Heinrich D, Wagner KF, Hofer T, Schindler SG, et al. Heat Induction of the Unphosphorylated Form of Hypoxia-Inducible Factor-1 α Is Dependent on Heat Shock Protein-90 Activity. J Biol Chem 2002; 277(11): 9262–9267.
- 43. van Uden P, Kenneth NS, Rocha S. Regulation of Hypoxia-Inducible Factor-1αa by NF-ΚB. Biochem J 2008; 412(3): 477–484.
- 44. An WG, Kanekal M, Simon MC, Maltepe E, Blagosklonny MV, Neckers LM. Stabilization of Wild-Type P53 by Hypoxia-Inducible Factor 1α. Nature 1998; 392(6674): 406–508.
- 45. Grossman SR. P300/CBP/P53 Interaction and Regulation of the P53 Response. Eur J Biochem 2001; 268(10): 2773–2778. pmid:11358491
- 46. Koumenis C, Alarcon R, Hammond E, Sutphin P, Hoffman W, Murphy M, et al. Regulation of P53 by Hypoxia: Dissociation of Transcriptional Repression and Apoptosis from P53-Dependent Transactivation. Mol Cell Biol 2001; 21(4): 1297–1310. pmid:11158315
- 47. Suzuki H, Tomida A, Tsuruo T. Dephosphorylated Hypoxia-Inducible Factor 1α as a Mediator of P53-Dependent Apoptosis during Hypoxia. Oncogene 2001; 20(41): 5779–5788.
- 48. Arany Z, Huang LE, Eckner R, Bhattacharya S, Jiang C, Goldberg MA, et al. An Essential Role for P300/CBP in the Cellular Response to Hypoxia. PNAS USA 1996; 93(23): 12969–12973. pmid:8917528
- 49. Ebert BL, Bunn HF. 1998. Regulation of Transcription by Hypoxia Requires a Multiprotein Complex That Includes Hypoxia-Inducible Factor 1, an Adjacent Transcription Factor, and P300/CREB Binding Protein. Mol Cell Biol 1998; 18(7): 4089–4096.
- 50. Hewitson KS, McNeill LA, Riordan MV, Tian Y-M, Bullock AN, Welford RW, et al. Hypoxia-Inducible Factor (HIF) Asparagine Hydroxylase Is Identical to Factor Inhibiting HIF (FIH) and Is Related to the Cupin Structural Family. J Biol Chem 2002; 277(29): 26351–26355. pmid:12042299
- 51. Kung AL, Zabludoff SD, France DS, Freedman SJ, Tanner EA, Vieira A, et al. Small Molecule Blockade of Transcriptional Coactivation of the Hypoxia-Inducible Factor Pathway. Cancer Cell 2004; 6(1): 33–43. pmid:15261140
- 52. McNeill LA, McNeill LA, Hewitson KS, Claridge TD, Seibel JF, Horsfall LE, et al. Hypoxia-Inducible Factor Asparaginyl Hydroxylase (FIH-1) Catalyses Hydroxylation at the β-Carbon of Asparagine-803. Biochem J 2002; 367(3): 571–575.
- 53. Jiang BH, Jiang G, Zheng JZ, Lu Z, Hunter T, Vogt PK. Phosphatidylinositol 3-Kinase Signaling Controls Levels of Hypoxia-Inducible Factor 1. Cell Growth Diff 2001; 12(7): 363–369. pmid:11457733
- 54. Fukuda R, Hirota K, Fan F, Jung YD, Ellis LM, Semenza GL. Insulin-like Growth Factor 1 Induces Hypoxia-Inducible Factor 1-Mediated Vascular Endothelial Growth Factor Expression, Which Is Dependent on MAP Kinase and Phosphatidylinositol 3-Kinase Signaling in Colon Cancer Cells. J Biol Chem 2002; 277(41): 38205–38211. pmid:12149254
- 55. Bárdos JI, Ashcroft M. 2004. Hypoxia-Inducible Factor-1 and Oncogenic Signalling. BioEssays 2004; 26(3): 262–269. pmid:14988927
- 56. Zhou J, Schmid T, Frank R, Brüne B. PI3K/Akt Is Required for Heat Shock Proteins to Protect Hypoxia-Inducible Factor 1α from PVHL-Independent Degradation. J Biol Chem 2004; 279(14): 13506–13513.
- 57. Feldser D, Agani F, Iyer NV, Pak B, Ferreira G, Semenza GL. Reciprocal Positive Regulation of Hypoxia-Inducible Factor 1α and Insulin-like Growth Factor 2. Cancer Res 1999; 59(16): 3915–3918.
- 58. Hena A, Maizels ET, Park Y, Ghaey S, Feiger ZJ, Chandel NS, et al. Follicle-Stimulating Hormone Activation of Hypoxia-Inducible Factor-1 by the Phosphatidylinositol 3-Kinase/AKT/Ras Homolog Enriched in Brain (Rheb)/Mammalian Target of Rapamycin (mTOR) Pathway Is Necessary for Induction of Select Protein Markers of Follicular Differentiation. J Biol Chem 2004; 279(19): 19431–19440. pmid:14982927
- 59. Forrester SJ, Kawai T, O’Brien S, Thomas W, Harris RC, Eguchi S. EGFR Transactivation: Mechanisms, Pathophysiology and Potential Therapies in Cardiovascular System. Annu Rev Pharmacol Toxicol 2016; 56(2): 627–653.
- 60. Mateo J, Garcia-Lecea M, Cardenas S, Hernandez C, Moncada S. Regulation of Hypoxia-Inducible Factor-1α by Nitric Oxide through Mitochondria-Dependent and -Independent Pathways. Biochem J 2003; 376(2): 537–544.
- 61. Chandel NS, Maltepe E, Goldwasser E, Mathieu CE, Simon MC, Schumacker PT. Mitochondrial Reactive Oxygen Species Trigger Hypoxia. Proc Nat Acad Sci USA 1998; 95(September): 11715–11720.
- 62. Chandel NS. Reactive Oxygen Species Generated at Mitochondrial Complex III Stabilize Hypoxia-Inducible Factor-1α during Hypoxia: A Mechanism of O2 Sensing. J Biol Chem 2000; 275(33): 25130–32518. http://dx.doi.org/10.1074/jbc.M001914200.
- 63. Page EL, Robitaille GA, Pouysségur J, Richard DE. Induction of Hypoxia-Inducible Factor-1α by Transcriptional and Translational Mechanisms. J Biol Chem 2002; 277(50): 48403–48409.
- 64. Moeller BJ, Yiting CC, Li Y, Dewhirst MW. Radiation Activates HIF-1 to Regulate Vascular Radiosensitivity in Tumors: Role of Reoxygenation, Free Radicals, and Stress Granules. Cancer Cell 2004; 5(5): 429–441. pmid:15144951
- 65. Kitamoto Y, Tokunaga H & Tomita K. Vascular endothelial growth factor is an essential molecule for mouse kidney development: glomerulogenesis and nephrogenesis. J Clin Invest 1997; 99, 2351–2357. pmid:9153276
- 66. Lee EY, Shim MS, Kim MJ, Hong SY, Shin SG, Chung CH. Angiotensin II Receptor Blocker Attenuates Overexpression of Vascular Endothelial Growth Factor in Diabetic Podocytes. Exp Mol Med 2004; 36(1): 65–70. pmid:15031673