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. 2018 Mar 2;19(1):173.
doi: 10.1186/s12864-018-4518-z.

Identification of placental nutrient transporters associated with intrauterine growth restriction and pre-eclampsia

Xiao Huang  1   2 , Pascale Anderle  3   4 , Lu Hostettler  2 , Marc U Baumann  1   5 , Daniel V Surbek  1   5 , Edgar C Ontsouka  1   2 , Christiane Albrecht  6   7
Affiliations

Identification of placental nutrient transporters associated with intrauterine growth restriction and pre-eclampsia

Xiao Huang et al. BMC Genomics. .

Abstract

Background: Gestational disorders such as intrauterine growth restriction (IUGR) and pre-eclampsia (PE) are main causes of poor perinatal outcomes worldwide. Both diseases are related with impaired materno-fetal nutrient transfer, but the crucial transport mechanisms underlying IUGR and PE are not fully elucidated. In this study, we aimed to identify membrane transporters highly associated with transplacental nutrient deficiencies in IUGR/PE.

Results: In silico analyses on the identification of differentially expressed nutrient transporters were conducted using seven eligible microarray datasets (from Gene Expression Omnibus), encompassing control and IUGR/PE placental samples. Thereby 46 out of 434 genes were identified as potentially interesting _targets. They are involved in the fetal provision with amino acids, carbohydrates, lipids, vitamins and microelements. _targets of interest were clustered into a substrate-specific interaction network by using Search Tool for the Retrieval of Interacting Genes. The subsequent wet-lab validation was performed using quantitative RT-PCR on placentas from clinically well-characterized IUGR/PE patients (IUGR, n = 8; PE, n = 5; PE+IUGR, n = 10) and controls (term, n = 13; preterm, n = 7), followed by 2D-hierarchical heatmap generation. Statistical evaluation using Kruskal-Wallis tests was then applied to detect significantly different expression patterns, while scatter plot analysis indicated which transporters were predominantly influenced by IUGR or PE, or equally affected by both diseases. Identified by both methods, three overlapping _targets, SLC7A7, SLC38A5 (amino acid transporters), and ABCA1 (cholesterol transporter), were further investigated at the protein level by western blotting. Protein analyses in total placental tissue lysates and membrane fractions isolated from disease and control placentas indicated an altered functional activity of those three nutrient transporters in IUGR/PE.

Conclusions: Combining bioinformatic analysis, molecular biological experiments and mathematical diagramming, this study has demonstrated systematic alterations of nutrient transporter expressions in IUGR/PE. Among 46 initially _targeted transporters, three significantly regulated genes were further investigated based on the severity and the disease specificity for IUGR and PE. Confirmed by mRNA and protein expression, the amino acid transporters SLC7A7 and SLC38A5 showed marked differences between controls and IUGR/PE and were regulated by both diseases. In contrast, ABCA1 may play an exclusive role in the development of PE.

Keywords: Bioinformatics; Intrauterine growth restriction; Membrane transporters; Placenta; Pre-eclampsia.

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Conflict of interest statement

Ethics approval and consent to participate

The study protocol was approved by the local ethic committees of the Canton of Bern, Switzerland (178/03). Written informed consent was obtained from each participant for this research prior to the caesarean section. A copy of the consent form is available for review by the Editor of this journal.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Strategy to _target nutrient transporters in intrauterine growth restriction and pre-eclampsia using multiple approaches. The funnel like structure of the different analytical approaches represents the decreasing number of _targets which overlap in every step of the analyses. Originating from 434 genes in meta-analysis of microarray data (1), 46 differentially expressed candidate genes were selected and clustered by STRING network (2). Gene expression screening of an in house placental tissue collection in the laboratory (3) was analysed by statistical evaluation and mathematical diagramming (4). The resulting 3 overlapping transporters were finally subjected to the biochemical analyses of protein translation and membrane localization
Fig. 2
Fig. 2
Functional interaction networks of proteins encoded by the potential candidate _targets. Forty six transporters selected from microarray analysis were clustered by Search Tool for the Retrieval of Interacting Genes (STRING). The protein-protein interaction in human placenta was performed using customized settings, including medium confidence of 0.4, Markov cluster algorithm (MCL) and 8 criteria for linkage (neighbourhood, gene fusion, co-occurrence, co-expression, experiments, databases, text mining and homology). The red, yellow and blue clusters highlight the substrate-specific components, which are vitamin transporters, microelements and ion transporters, and amino acid transporters, respectively. The available 3D protein structural information is embedded in the node, and the dashed lines represent the inter-cluster edges
Fig. 3
Fig. 3
Nutrient transporter mRNA expression profiles of placenta tissues. Heatmap generated from quantitative RT-PCR data from an in-house placental tissue collection, hierarchically clustering the gene expression values of 46 transporters in selected gestational conditions. The clinical status of individual patients, e.g. term (n = 13), preterm (n = 7), intrauterine growth restriction (IUGR, n = 8), pre-eclampsia (PE, n = 5), PE combined with IUGR (PE + IUGR, n = 10), is indicated on the top, and gene names are listed on the right. Up-regulated expressions are marked in red, down-regulations are coloured in green; black reflects no difference in expression levels
Fig. 4
Fig. 4
Identification of transporters with a significantly aberrant expression pattern in gestational diseases. The expression patterns of nutrient transporters in placental tissues obtained from controls and the gestational diseases described in Fig. 3 were screened by quantitative RT–PCR. Based on Kruskal-Wallis test (p <  0.05), eight candidate transporters showed significantly altered mRNA abundance in patients, i.e. SLC7A7 (a), SLC38A2 (b), SLC38A5 (c), SLC2A1 (d), ABCA1 (e), SLC19A3 (f), SLC22A15 (g) and SLC26A2 (h). Log 2-fold change (FC) values of gene expressions are shown as scatter plots with lines drawn at median ± range. Each symbol represents the gene expression of one individual. In the same figure, the differential expression trends of transporters in IUGR or PE from the meta-analysis (see Fig. 1) are illustrated by arrows. Red and green colours depict up-regulation and down-regulation, respectively
Fig. 5
Fig. 5
Scatter plot on the influence of IUGR/ PE on transporter expression. Each point represents one nutrient transporter, whose X-axis is defined by its log (FC) expression value in the IUGR group, and the Y-axis is presented by its log (FC) expression value in PE. 0.2 was defined as error threshold. The top 3 genes dominantly influenced by the pathology of IUGR (SLC16A4, ABCA1, ABCG2) or PE (SLC23A1, SLC7A11, SLC26A2), are marked with blue and yellow squares, respectively. Red squares (SLC7A7, SLC7A8, SLC38A5) indicate the transporters that receive comparable effects from IUGR and PE. The points with cross mark depict the significantly regulated transporters by a Kruskal-Wallis test. Abbreviations: log (FC): log 2 fold change
Fig. 6
Fig. 6
Protein expression of the membrane transporters ABCA1, SLC7A7 and SLC38A5 in total tissue lysates. ABCA1 (a; 250 kD), SLC7A7 (b; 56 kD), and SLC38A5 (c; 51 kD) protein expressions in total lysates were quantified from control and diseased placentas. Western blotting (upper panels) was performed with 90 μg total lysates from term (n = 4), preterm (n = 5), IUGR (n = 6), PE + IUGR (n = 6), and PE (n = 5) (upper panels). After overnight exposure, an immunoreactive signal was observed in all lanes at the expected size. Relative protein expression levels from western blotting results were then calculated as the densitometric ratio of _target versus β-actin (43 kD; lower panels). Data are expressed as median ± range. Significance at p <  0.05 was assessed by a Kruskal-Wallis test, followed by Dunn’s multiple comparison
Fig. 7
Fig. 7
Protein expression of the amino acid transporters SLC7A7 and SLC38A5 in enriched plasma membrane fractions. Representative Western blots of SLC7A7 (a; 56 kD) and SLC38A5 (b; 51 kD) protein expression from isolated placental membrane fractions. Western blotting was performed with 30 μg membrane proteins from term (n = 4), preterm (n = 5), IUGR (n = 6), PE + IUGR (n = 6), and PE (n = 5) (Left panels). Both β-actin (43 kD) and Na+/K+ ATPase (112 kD) were used as loading controls. Relative protein expression levels from western blotting results were then calculated as the densitometric ratio of _targeted transporter versus β-actin (43 kD; upper right panel) and Na+/K+ ATPase (112 kD; lower right panel). Data are expressed as median ± range. Based on Kruskal-Wallis test followed by Dunn’s multiple comparison, *, ** denote p < 0.05 and < 0.01, respectively
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