Gene expression comparison reveals distinct basal expression of HOX members and differential TNF-induced response between brain- and spinal cord-derived microvascular endothelial cells

To identify genes that presented a distinct basal expression in BMECs and SCMECs, different criteria were applied on the transcriptomic data. Only values for all controls higher than the background (according to Agilent calculations) were considered. In a first approach, ratios (BMEC values versus SCMEC) were filtered based on a fold change (FC) ≥1.45. Only genes exhibiting the defined FCs for all combinations between duplicates were considered. These criteria led to select 648 genes exhibiting a higher expression in BMECs and 444 with a higher expression in SCMECs. Further analysis indicated that a high number of genes encoding known endothelial markers [17] and adhesion/TJ molecules have a similar expression pattern in BMECs and SCMECs (Table 1). However, some of the genes related to the extracellular matrix (ECM) such as Bgn (biglycan), Col3a1 (collagen type III alpha 1), Col1a1 (collagen type I alpha 1), Col1a2 (collagen type I alpha 2), Slit3 (slit guidance ligand 3), Mgp (matrix Gla protein), Spp1 (secreted phosphoprotein 1/osteopontin), Ctgf (connective tissue growth factor), and Cldn9 (claudin-9) were among the most strongly expressed genes in BMECs (Table 1). Other highly expressed BMEC genes (data not shown) were related to either cellular messengers within the central and peripheral nervous systems: Gal (galanin), Geft (Rho guanine nucleotide exchange factor 25), Nsg1 (neuron specific gene family member 1), Npy (neuropeptide Y); atherosclerosis: Ldb2 (LIM domain binding 2), Xdh (xanthine dehydrogenase), Il1rl1/Il33r (interleukin 1 receptor like 1); or fatty acid metabolism: Lpl (lipoprotein lipase), and Apoe (apolipoprotein E). Among the genes encoding growth factors, only Vegfc (vascular endothelial growth factor C) and Tgfb2 (transforming growth factor beta 2) exhibited a differential expression (Table 1). High basal expression of Tgfb2 in BMECs might be correlated to the higher expression of TGF-β-target genes such as Bgn, Ctgf, and collagens [18‐20].

Thus, the transcriptomic analysis of SCMEC and BMEC monolayers showed differential basal expression of a significant number of genes indicative of phenotypical differences between these two CNS endothelial cell types. Indeed, distinct and characteristic gene expression profiles were found among blood vessels and MECs from different tissues [21]. For instance, TGF-β2 was reported to be higher in primary human cerebral endothelial cells (HCECs) than in human umbilical vein endothelial cells (HUVECs) at both mRNA and protein levels [22]. However, at this stage, we cannot exclude that the gene expression profile in BMECs and SCMECs resulted from the cell culture conditions or a technical bias.

To investigate whether these differences at the basal expression level exist also in vivo, RT-qPCR was performed on RNA from freshly extracted BMVs and SCMVs as the in vivo tissues closest to cultured MECs. With the exception of Spp1, RT-qPCR confirmed the differential expression observed in the transcriptomic analysis for Bgn, Col3a1, Col1a2, Cldn9, Ctgf, and Tgfb2 (Table 2). Among these transcripts, Cldn9 exhibited the strongest differential expression in vivo. Although the functional impact of such a difference in Cldn9 basal expression between BMECs and SCMECs remains unclear, the level of its expression in BMECs could reflect a distinct degree of activation of signaling components. Indeed, it was shown that silencing of c-Jun NH(2)-terminal kinases (JNKs), JNK1 or JNK2, increased CLDN9 mRNA expression in epithelial cells [23]. Thus, it can be postulated that differential Cldn9 expression might reflect different basal activities of JNKs in BMVs and SCMVs, which consequently would impact the barrier integrity through the modulation of claudins.

As shown in Fig. 1, we also observed differential expression of other genes such as Tnfrsf1b, Mmp9, Mmp13, and to a lesser extent of Mmp14 in BMVs and SCMVs that followed the expression pattern deduced from the transcriptomic data in BMEC and SCMEC monolayers. In contrast, RT-qPCR for Mmp3 and Mmp12 in BMVs and SCMVs led to opposite values when compared to the transcriptomic analysis (Fig. 1), which might illustrate differences between cultured MEC monolayers and freshly extracted MVs.

The basal differences observed between BMECs and SCMECs at the gene expression level suggested differential regulation of master program genes involved in cell differentiation. Interestingly, among the top 50 genes presenting higher expression in SCMECs than in BMECs, Hoxa9 and Hoxb7 were listed in the first rank and these results were confirmed using RT-qPCR (not shown). Moreover, other members of the same family exhibited a similar profile (Table 3). Similar differences were observed in vivo when Hoxa9 and Hoxb7 expression was assessed on mRNAs extracted from BMVs and SCMVs. Using RT-qPCR, we found higher expression levels of Hoxa9 and Hoxb7 mRNAs in SCMVs compared to BMVs (Table 3). Western blot performed on protein extracts generated from BMV and SCMV samples confirmed differential expression of HOXA9 and HOXB7 at the protein level (Fig. 2).

Hox genes encode transcriptional factors of the homeobox (HOX) protein family. Expression of these genes is involved in morphogenesis and differentiation and is spatially and temporally regulated during embryonic development. The role of HOXA9 is critical for endothelium commitment resulting from the differentiation of circulating endothelial progenitor cells into mature endothelial cells [24]. On the other hand, HOXB7 was reported to act as a key factor upregulating a variety of pro-angiogenic stimuli leading to increased matrix metalloproteinase-9 (MMP9) expression [25], which is in line with its higher expression in SCMVs (Fig. 2). Recently, a transcript analysis study revealed shared and differential patterns of Hox gene expression between endothelial cells from different vascular beds [26]. Hoxd1, Hoxd3, Hoxd4, Hoxd8, and Hoxd9 were found to be expressed at a higher level in blood-derived outgrowth endothelial cells (BOECs) than in pulmonary artery endothelial cells (PAECs). It was suggested that the HOX clusters Hoxa7-10 and Hoxb5-7, which were consistently expressed in BOECs, HUVECs, and human aortic endothelial cells (HUAECs), remain expressed in differentiated endothelial cells. In line with this study, our results showing a differential expression in microvessels of distinct vascular beds sustain the possibility that Hox genes, known as master regulators of positional identity, can define endothelial phenotypes. It is tempting to speculate that upstream epigenetic events, which are known to regulate Hox gene expression [27], are responsible for these different endothelial phenotypes. Indeed, Hox gene expression during development undergoes tight spatiotemporal regulation, partly by chromatin structure and epigenetic factors [28]. Particularly, HOXA9 expression was found to be downregulated by histone deacetylase (HDAC) inhibitors while its overexpression partially rescued the endothelial differentiation of adult progenitor cells blocked by these inhibitors [29]. Although the impact of such differences in Hox gene expression in SCMEC and BMEC monolayers is unclear, it can be postulated that they might influence the intrinsic capacity of MECs to respond to external stimuli, such as pro-inflammatory cytokines.

To investigate whether rat BMEC and SCMEC monolayers respond differently to pro-inflammatory cytokines, they were either treated with TNF-α for 12, 24, and 48 h or left untreated. Validation of the TNF-α response in these cellular models was achieved by following expression and secretion of CCL2 in all tested conditions (Fig. 3). RT-qPCR showed that the steady state levels of CCL2 mRNA increased rapidly in BMECs after 12 h of TNF-α treatment and then decreased progressively from 24 to 48 h (Fig. 3a). Although a similar TNF-α response was observed in SCMECs, the level of induction at 12 h was much lower than in BMECs. The inflammatory response of BMECs and SCMECs to TNF-α was confirmed by measuring CCL2 protein levels in the culture supernatants (Fig. 3b). TNF-α-induced secretion of CCL2 was maximal at 24 h in BMECs and at 48 h in SCMECs. TJ proteins are essential in BBB homeostasis and among them, occludin, ZO-1, and claudins in different vascular beds show differential expression in development, pathology, and BBB demise [1]. Occludin immunostaining in TNF-α-treated BMEC and SCMEC (not shown) monolayers systematically showed decreased tight junction/pericellular distribution and cytoplasmic/vesicular-like distribution compared to non-treated cells (Fig. 4a). This altered distribution was not associated with overall changes in occludin steady state levels as shown by western blot analysis in BMEC monolayers (Fig. 4b). Higher doses of TNF-α (100 ng/mL) on epithelial Caco-2 monolayers followed by western blot analysis have been shown to decrease levels of phosphorylated occludin (85 kDa), but had no effect on the non-phosphorylated form (65 kDa) [30]. Our results suggest that the MEC monolayers may express mainly the non-phosphorylated form of occludin, with no effect of TNF-α on steady state levels. In contrast, western blot analysis of claudin-5 and ZO-1 (Fig. 4b) indicated decreased steady state levels of these TJ proteins. Together, changes in occludin distribution and decreased claudin-5 and ZO-1 strongly suggested disruption of MECs monolayer integrity by TNF-α. This was confirmed by the increased Lucifer Yellow (LY) paracellular leakage in the abluminal compartment as shown for the BMEC monolayer, (Fig. 4c), in agreement with previous studies [12, 31, 32].

Transcriptomic analysis performed on rat MEC monolayers confirmed at the transcript level the decreased expression of Cldn5 (claudin-5) upon TNF-α treatment at all time points in both BMECs and in SCMECs (Table 4). Such a transcriptional repression of Cldn5 was reported to be triggered via nuclear factor kappa B (NFkB) signaling activity in retinal endothelial cells [33]. Like for Cldn5, expression of Cldn9 was strongly repressed by TNF-α in both BMECs and SCMECs at nearly all kinetic time points (data not shown). This downregulation of genes involved in TJ formation is likely associated with the TNF-α-induced opening of the BBB.

Analysis of the overall transcriptomic data showed that TNF-α induction was consistently more efficient in BMECs and appeared earlier than in SCMECs (Fig. 5). Indeed, in BMECs, the number of genes whose expression was moderately induced by TNF-α (FC ≥1.45 and <2) reached a peak at 12 h, then decreased in the course of time (Fig. 5a). Within the same FC range, the maximal number of genes more strongly induced in SCMECs was higher at 24 h, then decreased at 48 h but remained slightly higher than that in BMECs (Fig. 5a). For a FC ≥2, the number of induced genes increased from 12 to 24 h in SCMECs while it decreased in BMECs (Fig. 5b). This differential induction might reflect either the presence of cell-type specific TNF-α related signaling factors or distinct basal activities of these factors in BMECs and SCMECs.

To confirm the differential TNF-α response in BMECs and SCMECs, we investigated the expression levels of several known TNF-α targeted genes such as those encoding chemokines, including CCL2 and adhesion molecules (ICAM1, VCAM1). Most of these genes exhibited a stronger induction upon TNF-α treatment in BMECs compared to SCMECs at 12 h while, except for Ccl5, the opposite was true at 48 h in SCMECs (Table 5). Basal expression of these genes was either similar in the two cell types or higher in SCMECs (Table 5).

Remarkably, among the top ten genes with the highest induction following TNF-α treatment at 12 h, in either BMECs (Table 6(A)) or SCMECs (Table 6(B)), several genes including Mmp3, Mmp9, Mmp10, Mmp12, and Mmp13 that belong to the MMPs family were identified. MMPs are important in development and in numerous physiopathological processes including neuroinflammation. In the CNS, they cleave, activate, or release cytokines, growth factors, receptors, and death-inducing ligands and receptors through sheddase activity, and degrade components of the basal lamina leading to disruption of the BBB [34‐36]. Most of the top ten genes exhibited a stronger TNF-α response in BMECs and, with the exception of Ass1 (argininosuccinate synthase), Ptgs2 (prostaglandin-endoperoxide synthase 2), and Ptges (prostaglandin E synthase), a higher basal expression in SCMECs (Table 6).

Overall, our results indicate that TNF-α induced the expression of similar sets of genes in BMECs and SCMECs with, however, distinct efficiency and/or kinetics. Such a finding in primary cell cultures is in line with the generalized notion that responses of human MECs (HMECs) and macrovascular human umbilical vein ECs (HUVECs) to inflammatory molecules are basically comparable. Nevertheless, a considerable number of genes could also be regulated in a distinct manner in different EC types [37, 38] depending on the time points. It is noteworthy to mention that most of these reports analyzing differential TNF-α induced gene expression in ECs were performed for an incubation period not exceeding 12 h. As mentioned above, one possibility is that basal expression or activity levels of signal transducers might impact the level or the delay of the TNF-α response in BMECs and SCMECs.

To investigate whether the delay of response in BMECs and SCMECs was correlated with differences in TNF signaling, we assessed whether genes encoding known factors involved in this pathway were modulated. Interestingly, while a slight difference was observed between BMECs and SCMECs for Tnfrsf1a encoding TNFR1/p55, expression of Tnfrsf1b encoding TNFR2/p75 was higher in BMECs compared to SCMECs (Table 7). Western blots performed on protein extracts generated from freshly extracted BMV and SCMV samples confirmed higher TNFR1 and TNFR2 protein levels (2.3- and 2.8-fold, respectively) in BMVs (Fig. 6). However, no difference was observed for genes encoding other TNF-related receptor members or products involved in the TNF signaling pathway such as Birc2 (protein: c-IAP1), Birc3 (protein: c-IAP2), Tradd, Traff-2/3, Rela, Nfkb-1/2, Nfkbi-a/b, Ikbkb, Jun, Junb, and Jund (Additional file 1: Table S1). Among all genes encoding TNF-α receptors, Tnfrsf11b was significantly induced by TNF-α at all time points in BMECs and at 24 and 48 h in SCMECs, while Tnfrsf1b was induced at 24 and 48 h in SCMECs but not in BMECs (Table 7).

TNFR1 and TNFR2 elicit distinct features [39]. Soluble TNF (sTNF) only activates TNFR1, while membrane-bound TNF (mTNF) activates both receptors [40, 41]. In contrast to TNFR1 expressed in nearly all cells, TNFR2, which can be recognized by both TNF-α and LTA (TNF-β) ligands, is limited to some cell types including endothelial cells [42]. TNFR1 and TNFR2 subunits form a heterocomplex leading to NFkB/MAPK and NFkB/PI3K-AKT-dependent NFkB/JNK signaling pathways, respectively, which trigger distinct impacts on apoptosis, proliferation, and survival [43‐46]. On the other hand, it was postulated that the observed variability in TNF-induced CXCR3 chemokine expression in different microvascular beds might depend on the endothelial TNFR2 expression according to distinct anatomic loci [47].

Noteworthy, only two other genes, Tgfb2 and Prkcb, exhibited an expression pattern similar to Tnfrsf1b, which is higher in BMECs vs SCMECs (2.5- and 2.3-fold, respectively) and induced 2.5-fold by TNF-α at 24 and 48 h in SCMECs (not shown). It is likely that the higher basal expression of Prkcb in BMECs sustained the stronger and earlier TNF-α response in these cells since this gene encodes protein kinase Cβ, which plays a major role in TNF-α-induced human vascular endothelial cell apoptosis [48].