Identification of a combination of transcription factors that synergistically increases endothelial cell barrier resistance

Endothelial cells (ECs) display remarkable plasticity during development before becoming quiescent and functionally mature. EC maturation is directed by several known transcription factors (TFs), but the specific set of TFs responsible for promoting high-resistance barriers, such as the blood-brain barrier (BBB), have not yet been fully defined. Using expression mRNA data from published studies on ex vivo ECs from the central nervous system (CNS), we predicted TFs that induce high-resistance barrier properties of ECs as in the BBB. We used our previously established method to generate ECs from human pluripotent stem cells (hPSCs), and then we overexpressed the candidate TFs in hPSC-ECs and measured barrier resistance and integrity using electric cell-substrate impedance sensing, trans-endothelial electrical resistance and FITC-dextran permeability assays. SOX18 and TAL1 were the strongest EC barrier-inducing TFs, upregulating Wnt-related signaling and EC junctional gene expression, respectively, and downregulating EC proliferation-related genes. These TFs were combined with SOX7 and ETS1 that together effectively induced EC barrier resistance, decreased paracellular transport and increased protein expression of tight junctions and induce mRNA expression of several genes involved in the formation of EC barrier and transport. Our data shows identification of a transcriptional network that controls barrier resistance in ECs. Collectively this data may lead to novel approaches for generation of in vitro models of the BBB.

www.nature.com/scientificreports www.nature.com/scientificreports/ To gain more insights into how and which TFs direct BBB formation, we perused the literature [4][5][6]8 and identified several candidate TFs that could direct naïve ECs into BBB-like cells. Since stem-cell derived ECs are more amenable to gain-of-functional assays than primary cells 15 , we transduced combinations of candidate TFs in naïve human pluripotent stem cells derived ECs (hPSC-ECs) 16,17 and measured gene expression, tightness and permeability of the cell-cell junctions. Using this approach, we identified a network of TFs (ETS1+SOX7+SOX18 and either TAL or LEF1) that significantly induced barrier resistance and induced expression of tight junction proteins and transporters characteristic of BBB ECs. These findings are important since improved BBB in vitro models may be useful for drug screening and functional testing.

Results
To identify TFs that direct the differentiation of naïve hPSCs to BBB-like ECs, we first analyzed published gene profiling datasets from non-and CNS-derived murine ECs (GSE35802 8 , GSE48209 5 , GSE56777 4 , and GSE47067 1,6 ). We entered the datasets with the largest number of tissues into RankProdit, a tool that compares multi-array data based on rank-model 18 (Supplementary Dataset 1). Human and murine TFs were subsequently filtered from the dataset according to RIKEN TFs database 19 (Supplementary Dataset 2). Studies based on similar tissue comparisons were used for validation (Supplementary Dataset 3) [4][5][6]8 . Finally, we excluded TFs with RankProdit fold-change values of <1.5 (based on GSE47067 1,6 ; Supplementary Fig. 1). We then included some TFs based on literature compelling evidence (summarized in Supplementary Dataset 4).
Using the criteria described above, we identified 17 TF candidates, and tested them using gain-of-function assays in hPSC-ECs (via adenovirus transduction; 80 MOI). The effects were measured using Electric cell-substrate impedance sensing (ECIS) after resistance values are known to stabilize (10 h post-transduction). Some TFs (TAL1 and SOX18) induced significantly enhanced barrier properties, and a positive trend was seen when seven others were transduced (colored bars) (Fig. 1a). Real-time ECIS data showed that TAL1 induced more rapid and dramatic effects than SOX18 (Fig. 1b). ETS1 also induced high resistance, albeit more slowly (Fig. 1b). Permeability assays using FITC-dextran were also employed; permeability was reduced in cells transduced with SOX18, SOX7, ETS1 and LEF1 48 h post-transduction (Fig. 1c). Somewhat paradoxically, no effect was observed in TAL1 transduced cells (Fig. 1c). However, ECIS effects due to TAL1 overexpression were also abolished at 48 h due to rapid activity of TAL1 (Fig. 1b).
We then set out to determine the molecular basis of the candidate TF activities using gene profiling. Gene profiling analyzes (RNA-seq; 48 h post-transduction) confirmed that transduced TFs were significantly upregulated (Fig. 1d, Supplementary Dataset 5). For this, GSEA 20 data were analyzed using the Molecular Signatures Database (MSigDB) hallmark gene set 21 focusing on pathways relevant to EC barrier integrity (Fig. 1e, f, Supplementary Dataset 5). Data showed that Hedgehog-related and canonical Wnt-related signaling family members were upregulated by all TFs tested except by KLF11, and ETS1 (and FOXF2 exerted the broadest effects). ETS1 and TAL1 activated angiogenesis-related genes, and KLF11 uniquely activated proliferation-related genes. The effects of SOX18 and SOX7 transduction largely overlapped (converging on canonical Wnt, Hedgehog and Notch pathways). FOXF2, FOXC1 and KLF11 reduced expression of classic EC markers VEGFR2, VEGFR1 and CD34 (Fig. 1g, Supplementary Dataset 5) and were therefore removed from future considerations.
Since TFs rarely operate independently 35 , we next forced expression of quadruple combinations of the promising candidate TFs identified in our functional barrier assays (Fig. 1a-c) but at lower MOI (20 each; 80 MOI total) in hPSC-ECs. First, ECs were transduced with individual TFs with 20 MOI, and no significant resistance increase was observed 24 h post-stabilization resistance (Fig. 2a), except for SOX18 that induced a modest increase (Fig. 2b). Only SOX18 decreased barrier permeability in FITC-dextran permeability assay (Fig. 2c). For combinatorial gain of function assays, we chose TFs that induced more resistant barrier in functional assays ( Fig. 1b; SOX18, TAL1) with TFs that induced genes involved in barrier formation ( Fig. 1h; ETS1, SOX7). Gene profiling assays suggested that the combinations of ETS1, SOX7 and SOX18 induced the largest number of barrier-related genes (Fig. 1h, Supplementary Fig. 2). Addition of either LEF1 or TAL1 to that TF combination led to an additional significant increase in barrier resistance (Fig. 2d,e). The highest induction was 1.7-fold (combination with TAL1), which is more than the additive effect of the 4 factors (at 20 MOI) and also higher than overexpression of the single most efficient TF when transduced at 80 MOI (Fig. 2b). There was a significant reduction in FITC-dextran permeability (both 4 and 40 kDa) for both combinations of TFs (Fig. 2f). Next, we focused on expression of the three most important tight junction molecules for EC barrier integrity CLDN5 36 (Fig. 3a), OCLN 37 (Fig. 3b) and ZO1 (TJP1 38 , Fig. 3c) by immunocytochemistry and we observed significant induction of protein expression of CLDN5 and OCLN with both TF combination and induction of ZO1 by overexpression of combination that included TAL1. To understand more broadly the effect on barrier integrity by the TF R el ativ e expr es sion ( em pty= 1)  Prolif. Inflam.
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Discussion
The molecular profiles of CNS-derived ECs have been well characterized 1,[4][5][6] ; what sets our study apart from the others is that we characterized the effects of candidate TFs using combinatorial gain-of-function assays. TFs are activated in key temporal sequences to regulate gene expression and to control key steps in development 39 . However, the transcriptional program required to generate a mature BBB is incompletely understood 13,14 . We      www.nature.com/scientificreports www.nature.com/scientificreports/ (hPSC-ECs) 16,40 . We measured the effects using impedance and FITC-dextran permeability (paracellular permeability) assays (but did not explore the transcellular permeability).
From the gene expression comparisons, we selected these candidates: LEF1, FOXF2, FOXF1, and ZIC3. In our hands, LEF1, which may interact with β-catenin to regulate gene expression of ECs in BBB 41 , significantly increased barrier resistance post transduction. FOXF2 was shown to be involved in EC BBB development and maintenance 42 , but in our study, FOXF2 overexpression induced expression of several important EC tight junctions, but reduced CLDN5 (Fig. 1h). FOXF2 overexpression had only a modest effect in increasing resistance of EC barrier (Fig. 1a), and therefore was not used in subsequent combinations. FOXF2 may act synergistically with FOXF1 43 , which regulates EC barrier of lung ECs 44 . Therefore, it would be interesting in further studies to determine if FOXF2 and FOXF1 simultaneous overexpression would increase EC resistance. Finally, ZIC3 may be acting uniquely in CNS ECs to regulate the epigenetic status of CNS ECs (methylation and chromatin structure). qRT-PCR analyses showed that ZIC3 induced PECAM1 expression (data not shown) but did change the barrier properties of ZIC3-transfected ECs.
We continued to add candidates to our final combination of TFs based on the observations summarized below. ETS1 was included in subsequent combinations because it slowly improved barrier integrity post-transduction (Fig. 1b), and it is the only candidate TF that activated CLDN5 (Fig. 1h). In our hands, both SOX7 and SOX18 induced higher barrier resistance in accordance with another study showing that SOX7, SOX17 (not tested in our study) and SOX18 contribute to murine blood retinal barrier generation 45 (Fig. 1b). TAL1 rapidly strengthened the barrier properties of ECs and TAL1 is reported to be involved in EC specification 46 . LYL1, a close homolog in TAL1, may be to be critical for generating the barrier in lung ECs.
Combinatorial interaction among TFs is critical for the differentiation of various cell types 35,47 , and here we determined that the combination of SOX18, SOX7, ETS1 and LEF1 (or TAL1) synergistically induces EC barrier resistance in hPSC-ECs. The combination of these factors was able to induce significantly protein expression of important tight junction proteins (Claudin5, Occludin, ZO1) and induced mRNA of several other important molecules involved in EC barrier integrity and transport across the barrier. The characterized combination of TFs could be used by researchers to generate optimized BBB models. Our gene-profiling results, collected after overexpressing nine TFs TAL1, FOXC1, KLF11, FOXF2, SOX18, LMO2, LEF1, SOX7 and ETS1, or a combinations thereof, could also serve as a comprehensive resource for vascular biologists.

Methods
Human PSC culture and differentiation. The hPSC line SA001 48 (Cellartis AB) was differentiated as described 16,17 with the following modifications. Expansion medium consisting of StemPro with 50 ng/mL of VEGFA was used for the first cell division, after which cells were cultured using VascuLife VEGF Endothelial Medium Complete Kit (LifeLine Cell Technology). The final composition of supplements added to the media was as follows: 10% FBS, 4 mM L-glutamine, 0.75 U/mL heparin sulfate, 5 ng/mL FGF-2, 5 ng/mL EGF, 5 ng/mL VEGFA, 15 ng/mL IGF1, 1 µg/mL hydrocortizone hemisuccinate, and 50 µg/mL Ascorbic acid. SB431542 (10 µM) was supplemented to the media.
Adenovirus production. We tested several different promoters (UbiC, E1Fα and CMV) with GFP expression and several different multiplicities of infection (MOI) for introducing adenovirus (data not shown) and selected the UbiC promoter. Experiments with adenovirus expressing GFP with 20 MOI and 80 MOI were performed to identify MOI that would transduce all cells and show moderate expression of (20 MOI) or high expression (80 MOI), data not shown. The final construct had the UbiC promoter followed by the ORF and then the 3′UTR of GFP with a polyadenylation sequence. For all the TFs ORFs the consensus CDS (CCDS) or the most abundant expressed form of transcript in hPSC-ECs was cloned. Bacterial artificial chromosomes (BAC) were generated by transformation and recombination in E. coli DH10B carrying SIR-BAC-Ad5 encoding an E1-and E3-deficient adenovirus genome. Recombinant adenovirus particles were generated by transfecting the linearized construct into HEK293 cells and purifying the replication-competent adenoviruses using AdenoONE Purification Kit (Sirion Biotech). Adenovirus production was done by Sirion Biotech.
Electric cell-substrate impedance sensing (ECIS). 96-well plates (Applied Biophysics) were coated with 100 μL of fibronectin (25 μg/mL), which was then replaced with complete media and electrodes were allowed to stabilize. hPSC-ECs were seeded at 10,000 cells/well and grown for 2 days to reach full confluence before transduction with adenovirus overexpressing TFs. ECIS was measured in real time using the ECIS ® Z-theta system 49 (Applied Biophysics) at 250 Hz 50 .

Transendothelial electrical resistance (TEER).
The TEER values of hPSC-ECs were measured using the cellZscope (nanoAnalytics, Münster, Germany). Cells were prepared on HTS Transwell ® -24 Well format (Corning; 3378) at 0.4 × 10 6 cells/cm 2 and let them grow for two days in order to form a monolayer. Afterwards SB431542 10 µM or RepSox 10 µM or DMSO were added on the apical chamber. The TEER values were recorded in real-time every 30 minutes automatically in triplicates.
FITC-dextran permeability assay. hPSC-ECs were seeded in fibronectin-coated Transwell ® 96-well plates (pore size: 0.4 µm, Corning) in complete media. EC media was added to both the bottom chamber (235 μL) and the top chamber (75 µL). Cells were incubated for 2 days to allow attachment and to generate a confluent monolayer before transduction with adenovirus overexpressing TFs in the upper chamber. Analysis was carried out 2 days later by adding 10 μL of 4 kDa or 40 kDa FITC-dextran to the top chamber and then by incubating for 30 min at 37 °C under 5% CO 2 . After 30 min, top wells were removed and the bottom plate, containing media and leaked FITC-dextran, was measured in a fluorescent reader (Molecular Devices, excitation 485 nm, emission 535 nm).
Imaging and quantification. Images were prepared using ZEISS LSM 710 confocal microscope with 40x objective (Carl Zeiss Microscopy GmbH). The image data was reconstructed into a single image for each Z-stack using maximum intensity projection function in ImageJ. The intensity of entire area of fluorescence images was taken into account for analysis.

RNA-sequencing and analysis.
Total RNA was subjected to oligo (dT) capture and enrichment, and the resulting mRNA fraction was used to construct cDNA libraries. Sequencing was performed on an Illumina HiSeq platform using the standard protocol (TruSeq Stranded Total RNA Library, Illumina) that generates approximately 30 million reads of 50 base pairs per sample. Reads were mapped to the human genome (either hg19 or hg38/Refseq) using either STAR or SAMtools 51,52 and counting was performed using the union mode of HtSeq. 53 . Differential expression was performed using DESeq. 2 with the FDR correction 52 and read counts for RPKM were normalized by sequencing library size and gene length according to the reference 54 . Gene set enrichment analysis (GSEA) 20 was performed using the hallmark gene set at the MsigDb database 21 with weighted analysis to sort the gene list based on fold-change from upregulated to downregulated genes using default conditions and ignoring gene sets smaller than 15 or larger than 500 genes. The generated RNA-seq files have been deposited to GEO (GSE142132). Statistical analysis. Prism 7 (GraphPad) was used for statistical analysis, which was an unpaired, two-tailed Student's t-test unless mentioned otherwise (RNA-seq analysis). For all bar graphs, data are represented as mean ± SD. P values <0.05 were considered significant.

Data availability
RNA-seq files have been deposited to GEO (GSE142132).