Background

The intestinal epithelial barrier (IEB) is the first boundary between the organism and the luminal environment. It plays a dual role by allowing the passage of nutrients and electrolytes but preventing the passage of pathogens. The maintenance of its homeostasis is of utmost importance for the survival of the organism. The IEB is formed by a monolayer of specialized intestinal epithelial cells (IEC) under constant renewal and maintained together via various cell-to-cell and cell-to-matrix interactions. The IEB is part of a complex network of specialized cell types constituting its microenvironment such as immune cells, subepithelial fibroblasts, endothelial cells or luminal bacteria. Emerging evidences suggest that under physiological conditions, the IEB's functions are actively regulated by its cellular microenvironment [1–3]. For instance, myofibroblasts have been shown to enhance epithelial cell proliferation and intestinal epithelial restitution [4]. In addition, microbiota have been shown to control both the maturation and the maintenance of the IEB [5].

The enteric nervous system (ENS) is also a major constituent of the cellular microenvironment of the IEB. Indeed IEB and, in particular, the proliferative compartment of the crypts are densely innervated by nerve fibres originating mainly from the submucosal plexus. Recent data have shown that, besides controlling secretory processes, activation of enteric neurons can reduce IEC proliferation and barrier permeability, in particular via the release of vasoactive intestinal peptide (VIP) [6–8]. Enteric neurons innervating the IEB are also closely associated with enteric glial cells (EGC), the major constituent of the ENS.

For many years, EGC have been considered as mainly passive and structural cells supporting neurons and ganglions. However, this concept has lately been revisited mainly focused on the role played by astrocytes in the central nervous system (CNS) [9–11]. Besides controlling and regulating neuronal functions, increasing evidence suggests that EGC could be major regulators of IEB functions, similar to astrocytes controlling blood brain barrier functions [10]. Supporting this concept, recent data have demonstrated that EGC can profoundly inhibit IEC proliferation, in part via the liberation of TGF-β1 [12]. EGC also decrease IEB paracellular permeability via the release of S-nitrosoglutathione (GSNO) [13]. Furthermore, in vivo lesions of EGC network increase IEB paracellular permeability and IEC proliferation and, at term, lead to major lethal intestinal inflammation [13–15]. However, the role of EGC in the control of other major IEC functions such as cell differentiation, cell-to-cell or cell-to-matrix adhesion, and the associated regulatory pathways remains largely unknown.

Therefore, in our study, we combined transcriptomic studies as well as functional studies to determine the impact of EGC on the regulation of major genes and functions involved in IEB homeostasis. Microarray approach was used to identify EGC-induced modifications in gene expression profiling of proliferating Caco-2. The identified genes and related functional pathways are consistent with the concept that EGC are a major constituent of the IEB microenvironment favoring barrier protection.

Results and Discussion

Enteric glial cells modulate intestinal epithelial cells transcriptome

Microarray experiments

We performed microarray analysis of EGC influence on the transcriptome of Caco-2 cells using oligonucleotide chips (Cancerochips) developed at West Genopole transcriptome core facility of Nantes. These microarrays contain around 6,864 genes and are dedicated to gene expression studies in Caco-2 cell line as well as to gene expression signature studies of multiple tumors. Caco-2 cells were cultured onto Transwell filters in the absence or presence of EGC seeded at the bottom of the wells for 8 or 24 hours. The Transwell filters did not allowed any contact between IEC and EGC, thus implicating only paracrine communication between the two cell types.

Hierarchical clustering of the whole data showed the impact of the time of culture as well as the impact of the presence of EGC on the transcriptional profiling of IEC, i.e. Caco-2 cells (Figure 1). We observed changes in IEC transcriptome over the 24 hours of culture in control condition. At 8 hours, differences in transcriptome profiling already existed in control condition as compared to t = 0. In general, the observed changes in differentially expressed genes between t = 0 and t = 8 hours in control conditions were increased in the same way of regulation when reaching t = 24 hours (Figure 1). These changes might be due to the growth and differentiation of the proliferating IEC over the 24 hours of culture. We observed no major differences in gene expression profiling between IEC cultured alone and IEC cultured in presence of EGC at 8 hours of culture. In contrast, at 24 hours, EGC presence led to consistent and major changes in IEC gene expression profiling (Figure 1).

Figure 1
figure 1

Hierarchical clustering of expression data. Four individual microarrays were used per condition. Hierarchical clustering was performed on genes using Gene Cluster. Each ratio was normalized to the median of the t = 0 hour-condition values of the corresponding gene. Each column represents an individual array (T0: t = 0 hour condition samples; T8control: t = 8 hours of culture without EGC; T8glia: t = 8 hours of culture in presence of EGC; T24control: t = 24 hours of culture without EGC; T24glia: t = 24 hours of culture in presence of EGC). Each line represents one individual gene. The clustering shows the impact of the time of culture on gene expression profiling in Caco-2 cells. The EGC-induced modulation of IEC transcriptome is highly visible at t = 24 hours.

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Gene expression modulated by EGC

Using Genespring software, we aimed to identify statistically significant differences in gene expression profiling between Caco-2 cells cultured alone or in presence of EGC. After 8 h of culture, no significant difference in gene expression profiling was found between IEC cultured alone (control condition) or in presence of EGC ("glia" condition). However, after 24 hours of culture, we identified 116 genes differentially expressed between control and EGC conditions by using two different strategies. Benjamini and Hochberg False Discovery Rate method was used to determine 98 differentially expressed genes between control and glia conditions at t = 24 hours, and we also selected 27 genes with a two-fold change and Student's t-test p-value less than or equal to 0.05. Among the 116 differentially expressed genes, 46 genes were down-regulated and 70 were up-regulated in IEC cultured with EGC as compared to control (Table 1, 2). Quantitative PCR was also performed on various genes to validate the microarray results. In particular, results showed an EGC-induced increase of CDH1, FN1, LAMA5, PPARG, PTK2 mRNA expression in IEC and a decrease of E2F1, FGFR2, GPX2 and SMAD3 mRNA expression in IEC, similar to the data obtained with microarrays (Figure 2A). We next sought to determine the specificity of EGC effects upon IEC transcriptome by characterizing the impact of fibroblasts on the expression of these genes in IEC. Under identical culture conditions, we showed that fibroblasts increased expression of PTK2 but did not significantly modify gene expression of CDH1, FN1, LAMA5, PPARG, E2F1, GPX2 and SMAD3 in IEC (Figure 2B).

Table 1 List of the genes up-regulated by enteric glial cells in intestinal epithelial cells.
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Table 2 List of the genes down-regulated by enteric glial cells in intestinal epithelial cells.
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Figure 2
figure 2

Enteric glial cells EGC) and fibroblasts differentially modulated intestinal epithelial cell (IEC) transcriptome. (A). Real-time quantitative PCR studies on CDH1(n = 5), FN1 (n = 7), LAMA5 (n = 6), PPARG (n = 5), PTK2 (n = 5), E2F1 (n = 7), FGFR2 (n = 6), GPX2 (n = 8), SMAD3 (n = 7) gene expression in IEC cultured for 24 hours alone (- EGC) or in presence of EGC(+ EGC) confirmed that EGC significantly modulate the level of expression of genes identified by the microarrays data analysis as differentially expressed in IEC cultured in presence of EGC (*p < 0.05; Mann-Whitney test). (B). In contrast, real-time quantitative PCR studies on CDH1 (n = 5), FN1 (n = 5), LAMA5 (n = 5), PPARG (n = 5), PTK2 (n = 5), E2F1 (n = 5), GPX2 (n = 5), SMAD3 (n = 5) gene expression in IEC cultured for 24 hours alone (- fibroblasts) or in presence of fibroblasts (+fibroblasts) showed a differential regulation of gene expression as compared to EGC effects (*p < 0.05; Mann-Whitney test).

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Hierarchical clustering of differentially expressed genes

Hierarchical clustering was used to visualize the expression profile of the 116 genes induced or repressed by EGC after 24 hours of culture (Figure 3).

Figure 3
figure 3

Hierarchical clustering of the 116 identified genes expression data. Four individual microarrays were used per condition. Hierarchical clustering was performed on conditions and on the 116 genes identified with Genespring. Each ratio was normalized to the median of the t = 0 hour-condition values of the corresponding gene. Each column represents an individual array (T0: t = 0 hour condition samples; T8control: t = 8 hours of culture without EGC; T8glia: t = 8 hours of culture in presence of EGC; T24control: t = 24 hours of culture without EGC; T24glia: t = 24 hours of culture in presence of EGC). Each line represents one individual gene. The clustering reveals clusters of genes with similar pattern of expression among the different conditions. The cluster also shows the distance between the five conditions demonstrating major changes induced by the culture with EGC at t = 24 hours.

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All these genes exhibit a differential expression between control and EGC conditions at t = 24 hours. Furthermore, some of them already exhibited a slight difference in expression profile between control and EGC conditions at 8 hours. These results indicate that EGC effects on genes identified as differentially expressed in IEC at 24 hours probably started as early as at 8 hours, even though the modifications were not statistically significant.

Two groups of samples exhibited a very different profile from other samples: EGC condition at t = 24 hours and controls at t = 24 hours (Figure 3). These observations confirm that 1) no major changes existed between control and EGC conditions at t = 8 hours and 2) that the 24 hour-time of culture impacted on gene expression profiling in IEC, likely reflecting differentiation of IEC over the time of culture.

EGC regulate IEC functions

Gene network interactions

Biological interactions among the 116 genes of the gene set provided by Genespring analysis were identified using Ingenuity Pathways Analysis. Among the 116 genes differentially expressed, Ingenuity identified 92 genes contributing to a total of 10 functional networks (Table 3). Each of the 6 first networks contained at least 14 genes that were associated with cell-to-cell signalling and interaction, cellular growth and proliferation, cell morphology, cellular movement, cell death and cell cycle. The 116 genes were also classified into Ingenuity cellular and molecular pathways as well as into Ingenuity signalling pathways (Table 4 and 5). All the functions described above and identified by building functional networks among our gene set were found in the 25 cellular and molecular functions obtained with Ingenuity (Table 4). Moreover, these 6 functions were among the 10 first functions presenting the highest score (Table 4). Finally, the signalling pathways identified by the Ingenuity analysis of our gene set were also relevant to those 6 functions (Table 5). The limit of Ingenuity analysis for our study is that it is not restricted to one specific organ or cell, so that all the results of Ingenuity analysis could not be transposed directly to the regulation of IEC functions by EGC. We therefore performed an "epithelial" specific analysis of the major functions identified with Ingenuity.

Table 3 Lists of differentially expressed genes involved in functional networks regulated in intestinal epithelial cells by enteric glial cells.
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Table 4 Lists of differentially expressed genes involved in cellular and molecular functions regulated in intestinal epithelial cells by enteric glial cells.
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Table 5 Lists of differentially expressed genes involved in signalling pathways regulated in intestinal epithelial cells by enteric glial cells.
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Cell-to cell and cell-to-matrix interaction

EGC regulated the expression of numerous genes involved in the control of IEC adhesive processes. In particular, EGC induced an up-regulation of the expression of all 7 genes with pro-adhesive functions and a down-regulation of the 2 genes with anti adhesive properties, among the gene set found to be differentially expressed in IEC cultured in presence of EGC (Table 6). These genes are crucially involved in the control of cell-to-cell and cell-to-matrix adhesion.

Table 6 Genes controlling intestinal epithelial cells adhesion and modulated by enteric glial cells.
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First, EGC concomitantly increased the expression of CDH-1, which encodes E-cadherin, and decreased the expression of CDK5R1. E-Cadherin is the major component of the adherent junction complexes and the level of E-Cadherin in IEC is to be correlated to adhesion complexes formation between IEC [16, 17]. Further evidences confirming a pro-adhesive influence of EGC on IEC is the EGC-induced down-regulation of CDK5R1 expression. Indeed, CDK5R1 encodes p35, a regulator of CDK-5 (cyclin-dependent kinase), which induces the degradation of E-Cadherin precursor [18]. In addition, EGC also up-regulated IQGAP2 expression in IEC. This gene encodes for a protein member of IQGAP family that interacts with several molecules controlling cytoskeleton organization, cell adhesion and cell motility such as CDC42 and Rac [19]. Interestingly, IQGAP2 has been shown to mediate E-Cadherin-based cell-to-cell adhesion during development [20]. All these results suggest that EGC enhance cell-to-cell adhesion in IEC.

Our data also demonstrate that EGC modulate the expression of genes that are involved in cell-to-matrix interactions. First, EGC increased expression of several genes encoding proteins of the extracellular matrix such as LAMA5, LAMC1 and FN1. LAMA5 and LAMC1 encode respectively for laminin α5 and γ1 chains which, together with laminin β1 chain, compose laminin-10 [21]. Laminin-10 has been shown to be the most adhesive substratum of laminin isoforms when studying abilities of laminin-2,-5 and -10 in modulating Caco-2 cell adhesion [22]. Furthermore, EGC up-regulated FN1 expression, encoding the fibronectin protein. Interestingly, fibronectin has recently been shown to enhance Caco-2 cell attachment and wound healing [23]. EGC down-regulated KLK14 expression, which encodes KLK (kallikrein) 14, an extracellular serine protease which has been shown to cleave and digest various extracellular matrix proteins such as collagen IV, laminin and fibronectin [24]. In addition, EGC up-regulated PTK2 expression in IEC which may result in increased expression of FAK (Focal Adhesion Kinase) protein, a major regulator of focal adhesions turnover and maturation [25]. Finally, EGC induced an up-regulation of KRT8 expression whose increased expression has recently been shown to cause enhanced adhesion of human breast tumor cells to their extracellular matrix [38].

In conclusion, based on our analysis, EGC-mediated regulation of IEC transcriptome appears to strongly favor IEC differentiation.

Cell motility

EGC regulated in IEC the expression of genes encoding proteins that are known to play a role in IEC motility (Table 8). In particular, EGC induced an increase in FN1 expression in IEC. FN1 has been demonstrated as a major factor in promoting cell migration of IEC and subepithelial fibroblasts, thus favoring epithelial wound healing [39, 40]. Interestingly, EGC induced a down-regulation in LSP1 expression in IEC. LSP1 gene encodes for LSP1, a cytoplasmic actin-binding protein, whose overexpression in melanoma cells has been described to inhibit cell motility [41]. EGC-induced up-regulation of PTK2 expression also supports a role of EGC in promoting IEC motility. Indeed, increased FAK protein level promoted epithelial restitution via an increased IEC migration [42, 43]. Similarly, the increased PPARγ expression could enhance cell motility as inhibitors of PPARγ inhibit epithelial cell migration [44–46].

Table 8 Genes controlling intestinal epithelial cells motility and modulated by enteric glial cells.
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Cell proliferation

Expression of genes involved in cell proliferation was differentially regulated in IEC cultured in presence of EGC as compared to control (Table 9). In fact, EGC appeared to modulate the expression of anti-proliferative and pro-proliferative genes toward a dominant anti-proliferative effect (Table 9).

Table 9 Genes controlling intestinal epithelial cells proliferation and modulated by enteric glial cells.
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The expression of major anti-proliferative and pro-proliferative genes was found to be up-regulated and down-regulated, respectively, by EGC. In particular, PPARG, TXNIP and BTG1 expressions in IEC were up-regulated by EGC. PPARγ activation has been described both in vivo and in vitro to inhibit intestinal epithelial cell proliferation [47, 48] and to induce a G1 phase cell cycle arrest [27]. Furthermore, TXNIP encodes the thioredoxin-interacting protein, a negative regulator of thioredoxin. Thioredoxin is an important growth-promoting factor of IEC [49]. Moreover, TXNIP has also recently been suggested to be a tumor suppressor gene in hepatocellular carcinoma [50] and interestingly, TXNIP expression is decreased in colorectal cancer and ulcerative colitis [51]. Similarly, BTG1 has been shown to negatively regulate cell proliferation and to present a maximal expression during G0/G1 phases of the cell cycle in fibroblasts [52]. Further reinforcing the anti-proliferative effects of EGC on IEC is the EGC-induced down-regulation of the expression of pro-proliferative genes such as E2F1, FGFR2 and PPIL1. E2F1 is a gene encoding a protein member of the E2F family of transcription factors that regulate cell cycle progression by modulating expression of proteins required for the G1/S transition. It has been well described that growth stimulatory signals lead to active E2F1 accumulation and S-phase entry [53, 54]. FGFR2 encodes a member of the FGF (Fibroblast Growth Factor) receptor family with high affinity for KGF (Keratinocyte Growth Factor) which is a major actor in the mesenchymal stimulation of epithelial cell proliferation [55, 56]. Finally, PPIL1, which encodes a cyclophilin-related protein, PPIL1 (peptidyl prolyl isomerase-like protein), implicated in spliceosome activation, has recently been described to be overexpressed in colon tumors and PPIL1 silencing led to an inhibition of colon cancer cell growth [57, 58].

These global anti-proliferative effects of EGC upon IEC have to be associated with the EGC-induced modulation of genes that would tend to be pro-proliferative, although these are clearly in reduced numbers. For instance, EGC increase MKI67 expression, which encodes the proliferation marker Ki-67. Indeed, Ki-67 is increasingly expressed during the cell cycle phases [59], excepted in G0 or in cells just esca** from G0 [60]. Its function is still unclear but knock-down for Ki-67 in cancerous cells leads to an inhibition of proliferation mainly via an induction of apoptosis [61, 62]. Interestingly, EGC reduced the expression of TP53RK and SFRP4 in IEC that encode proteins involved in anti-proliferative pathways. TP53RK encodes PRPK which is a short kinase that phosphorylates p53, enhancing its transcriptional activity [63] and suppressing cell cycle transition G1/S [64]. SFRP4 encodes the protein sFRP4 (secreted frizzled-related protein), which is an inhibitor of the Wnt-signaling cascade through binding and sequestering Wnt ligand and, thus, has been shown to decrease cell proliferation in many cell lines [65–67].

Taken together, these data suggest that EGC tend to shift IEC transcriptome toward an anti-proliferative phenotype. These results could lead to the identification of specific targets responsible for the anti proliferative effects of EGC previously reported [12]. In addition, this global effect is supported further by the observation that EGC inhibit cell proliferation in part by inducing a cell cycle arrest in G0/G1 phase [11].

Cell survival

EGC differentially regulated in IEC the expression of genes involved in cell death. EGC appeared to modulate the expression of anti-apoptotic and pro-apoptotic genes toward a dominant pro-apoptotic effect (Table 10).

Table 10 Genes controlling intestinal epithelial cells survival and modulated by enteric glial cells.
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Indeed, expressions of pro-apoptotic and anti-apoptotic genes were found to be up-regulated and down-regulated, respectively, by EGC. In particular, BNIP3 and CASP4 expression in IEC were up-regulated by EGC. CASP4, coding for the caspase-4 pro-apoptotic protein has been shown to induce cell death [http://www.ncbi.nlm.nih.gov/geo/ and are available under the access number GSE17027.

RT-quantitative PCR

Extraction of total RNA from Caco-2 cells cultured alone, in presence of EGC or fibroblasts for 24 hours was performed with RNeasy Mini kit (Qiagen) according to the manufacturer's protocol. For reverse transcription, 1 μg of purified total RNA was denatured and subsequently processed for reverse transcription using SuperScript II Reverse Transcriptase (Invitrogen) according to the manufacturer's recommendations. PCR amplifications were performed using the Absolute Blue SYBR green fluorescein kit (ABgene) according to the manufacturer's protocol and run on MyiQ thermocycler (Biorad). The expression of the gene S6 was analyzed in parallel as an internal control.

CDH1[GenBank: NM_004360]

Forward primer:

5'-GACCAGGACTATGACTACTTGAACG-3'

Reverse primer:

5'-ATCTGCAAGGTGCTGGGTGAACCTT-3'

E2F1[GenBank: NM 005225]

Forward primer:

5'-CCGCTCGAGGAGAAGTCACGCTATGA-3'

Reverse primer:

5'-CCCAAGCTTTTGGTGATGTCATAGATGC-3'

FN1[GenBank: NM_054034]

Forward primer:

5'-GCAGGCTCAGCAAATGGTTCAG-3'

Reverse primer:

5'-AGGTAGGTCCGCTCCCACTG-3'

FGFR2[GenBank: NM_022970]

Forward primer:

5'-GTCCTGCCAAAACAGCAAG-3'

Reverse primer:

5'-CCCCTATGCAGTAAATGGCTA-3'

GPX2[GenBank: NM_002083]

Forward primer:

5'-gtccttggcttcccttgc-3'

Reverse primer:

5'-tgttcaggatctcctcattctg-3'

LAMA5[GenBank: NM_005560]

Forward primer:

5'-CCCACCGAGGACCTTTACTGC-3'

Reverse primer:

5'-GGTGTGCCTTGTTGCTGTTGG-3'

PPARG[GenBank: NM_138712/NM_005037/NM_138711/NM_015869]

Forward primer:

5'-ttgctgtcattattctcagtgga-3'

Reverse primer:

5'-gaggactcagggtggttcag-3'

PTK2[GenBank: NM_153831/NM_005607]

Forward primer:

5'- GAGATCCTGTCTCCAGTCTAC-3'

Reverse primer:

5'- TGCACCTGCTATTTTTAGTTG-3'

SMAD3[GenBank: NM 005902]

Forward primer:

5'-CCAAGCTTAGAACGGGCAGGAGGAG-3'

Reverse primer:

5'-CACTCGAGTGGTGGCTGTGCAGGTC-3'

S6[GenBank: NM_001010]

Forward primer:

5'-TGGCAAGATGATCCCAATGA-3'

Reverse primer:

5'-AGCTTCTTTGGGACACCTGCT-3'

Adhesion experiments

Global adhesion assay

IEC adhesion was estimated by performing a "global adhesion assay" that evaluated total IEC adhesion to their environment, i.e. adhesion to neighboring IEC and adhesion to matrix. IEC were cultivated on filters (12-well Transwell clear, 0.40 μm porosity, Corning) alone or in the presence of EGC for 24 hours. IEC were then trypsinized with 0.01% trypsin-EDTA free (Sigma) allowing gentle trypsinization for 30 minutes at 37°C. Non-adherent IEC were harvested and counted in a blind fashion using Malassez slides (VWR international). IEC remaining adhered on filters were trypsinized with 2.5% trypsin with EDTA (Gibco), harvested and counted. Results are expressed in percentage of remaining adherent IEC normalized to the total number of counted IEC (i.e., adherent IEC and non-adherent IEC). Only those series in which the percentage of IEC total adhesion in control condition was comprised between 20 and 70% were analyzed.

Cell-to-matrix adhesion assay

IEC were cultivated on filters (12-well Transwell clear, 0.40 μm porosity, Corning) alone or in presence of EGC for 24 hours. IEC were then trypsinized for 10 minutes with a 2.5% trypsin-EDTA (Gibco). Trypsin was neutralized with IEC culture medium (see above). IEC were subsequently reseeded on filters and incubated for 3 hours at 37°C. Time of incubation has been defined to allow 50% of seeded IEC to adhere to filters in control condition. Following incubation, unseeded cells were harvested and counted in a blind fashion using Malassez slides (VWR international). IEC that had adhered on filters were trypsinized and counted. Results are expressed in percentage of adherent IEC normalized to the total number of counted IEC (i.e., adherent IEC and non-adherent IEC). Only those series in which the percentage of IEC total adhesion in control condition was comprised between 20 and 70% were analyzed.