The pivotal role of micro-environmental cells in a human blood–brain barrier in vitro model of cerebral ischemia: functional and transcriptomic analysis

The study has three main aspects. First, a human BBB cerebral ischemia in vitro model should be developed in which the desired paracellular damage to 35–60% can be achieved in at least 6 h. This was considered to be very essential in order to be able to realistically simulate the course of functional BBB damage observed in in vivo models and in the clinic [41]. Secondly, by using the standard growth medium for the hCMEC/D3 cells, a medium change to another basal medium for OGD treatment is necessary (from EBM-2 to DMEM), since no glucose-free EBM-2 medium is available by default. In order to better interpret the data from the OGD experiments, it is necessary to check to what extent the change to a distinctly different basal medium has a relevant influence on the final results. In addition, the influence of common cultivation variants for hCMEC/D3 prior to the OGD experiment was tested on the expression of barrier relevant targets. Thirdly, there has been a discussion for a long time which tight junction proteins, especially which claudins, occur at the BBB in general, but also species-specifically. The investigation on the protein level is very difficult because there is a lack of specific antibodies for all claudins due to their high sequence homologies. For this reason, we have decided to conduct a comprehensive study on the transcript level in which all human claudins 1–25 were analyzed together with other TJ and BBB relevant ABC transporters in the most different conditions. Since first publications showed that the compensation of claudins can play an important role in the post stroke regeneration process [42] and that data on jointly regulated clusters of these targets are hardly known, it was decided to perform hierarchical cluster analysis. The obtained data can then be applied to propose possibly first coherent regulatory clusters. For these analyses we have deliberately opted for qPCR as the analytical method, as this has the widest dynamic range, the lowest quantification limits and the least biased results in comparison to microarrays or RNA-seq analysis [6, 13, 15]. This is especially important for TJ proteins as they are often regulated within a small range of 0.5 to twofold.

In recent years, in vitro BBB models for cerebral ischemia based on mouse brain endothelial cells have shown that co-culture was essential for a significant barrier damage within a few hours. Both rat glioma cell line C6 and primary glial cells were applied in these mouse models using 0–1% O₂ [29, 31]. The selected oxygen range of 0–1% is physiologically relevant considering the fact that almost no oxygen is left in the ischemic core (less than 5 mm Hg pO₂) after 1 h cerebral ischemia in vivo [25]. Preliminary experiments with hCMEC/D3 showed that incubation with glioma C6 cells for 5 h could be sufficient for the desired barrier collapse. Since the paracellular barrier of hCMEC/D3 cells is generally rather moderate, it is important to note that methodically the use of Corning Costar inserts is advantageous for this type of studies due to the slits that define spatially the measuring point for the chopstick electrodes, and the higher porosity and thus lower inherent electrical resistance of the porous membranes. For the Transwell studies hCMEC/D3 were incubated as mono- and co-cultures for 5 h under normoxia and OGD conditions. Cell viability of hCMEC/D3 was not detrimentally reduced under these conditions (Additional file 4) which was also confirmed by others [36, 53]. In this context, it was previously shown that it was necessary to apply 16–24 h OGD at 1% O₂ to reduce cell viability and TEER of mono-cultures of hCMEC/D3 to 5–20% or of hiPSC-BCECs (hiPSC = derived from human induced pluripotent stem cells) to 20–50% of the respective normoxia controls [21, 36, 37, 53]. Moreover, hCMEC/D3 mono-cultures treated with OGD at 1% O₂ for 6 h resulted in slight, but not significant changes of TEER and fluorescein permeability compared to the 6 h incubated normoxia control [37]. These data together with ours confirmed that no reasonable BBB breakdown was achievable without co-cultures in the aimed time window of maximum 6 h. Co-cultivation of hCMEC/D3 with rat glioma C6 cells resulted in the aimed barrier breakdown after 5 h of OGD treatment at 1% O₂. In the case of co-cultivation with the 1:1 mixture of primary, human astrocytes/pericytes, in contrast to 1% O₂, clear barrier damage was achieved at 0.1% O₂ after 5 h (effects at 1% O₂, see Additional file 5). Noteworthy, the integrity of the mono-cultures were also significantly disrupted under these conditions. The difference between the effects of the co-cultures with C6 and the primary human cells could be explained by the different amounts of secreted growth factors, since the C6 cells secrete e.g. significant more barrier damaging VEGF than primary astrocytes [4, 52].

As first step for the comprehensive barrier target analysis the relative expression of these targets was assessed in hCMEC/D3 under standard growth conditions. In the BBB research field the claudins-1, -3, -5, -11 and -12 are mostly investigated as surrogate markers for TJs, whereas recent studies with knock-out mice raised doubts about the presence and role of claudin-3 and -12 at the BBB [7, 8]. In the last 2 to 3 years some reports with expression data of primary human BCECs and hiPSC-BCECs have been published. These confirmed the expression of almost all claudins in human BBB in vitro models [11, 24, 47]. However, these data were mostly obtained from RNA-seq analysis and were not validated by a second method, so there is still a need to validate them with e.g. qPCR. For example, an open-accessible, but yet not peer reviewed report claims that the hiPSC-BCECs do not express claudin-5, although this has already been shown by many other groups [26]. This may be due to the general problem of lab-to-lab reproducibility of experiments and in particular by the lab-to-lab reproducibility of hiPSC differentiation protocols as well as the lack of validation of these expression data. Nevertheless, these data indicate that the human BBB may contain significantly more claudins than have been researched in detail so far. In order to classify the expression data of the hCMEC/D3 cells obtained in this work, Table 2 shows a comparison of these data with data from human isolated brain capillaries [3] and mouse brain endothelial cells from two RNAseq databases [46, 54]. The most strongly expressed claudins in the mouse brain endothelium found in both databases were claudin-5, claudin-12 and claudin-6. In addition, claudin-2, claudin-3, claudin-16, claudin-18, claudin-20 and claudin-22 were also listed in both databases. In case of the human capillary samples the most prominent claudins were claudin-5, claudin-11, claudin-12 and claudin-1. In comparison to these data, hCMEC/D3 cells expressed most claudin-11, claudin-1, claudin-12 and claudin-10. Interestingly, claudin-11 was not found in the mouse databases, whereas it was very strong in the human capillaries as well as in hCMEC/D3 cells. In this regard, Berndt et al. [3] proved the expression of claudin-11 also in mouse brain capillaries by qPCR indicating how important it is to validate RNAseq data by a second method. The most striking differences to the other samples was that hCMEC/D3 showed a high expression of claudin-10 and relatively low expression of claudin-5. In this context, the role of claudin-10 in hCMEC/D3 would still need to be investigated. According to Berndt et al. [3] claudin-10 is a paracellular pore forming claudin. It could be speculated, whether the knock-down of claudin-10 in hCMEC/D3 might increase paracellular tightness of hCMEC/D3 layers. The low amount of claudin-5 in hCMEC/D3 cells and the probably associated moderate paracellular barrier function were already shown by several groups [12] and confirmed by low TEER values in the present study. Recently, it was shown that the overexpression of claudin-5 in hCMEC/D3 cells led to a reduction in the permeation of A549 cancer cells by approximately two-thirds, but did not lead to a noticeable improvement in electrical impedance. This suggested that additional mechanisms were missing to functionally incorporate claudin-5 at the tight junctions in the cell membrane [27]. Single cell RNA-seq data of mouse brain derived cells from the Betsholtz group [46] showed that fibroblast-like cells and not brain capillary endothelial cells expressed claudin-1. This led to the question whether claudin-1 is present at the BBB and how relevant it is. In contrast to these data, claudin-1 was found in RNA-seq data of mouse brain endothelial cells by Zhang et al. [54]. Moreover, human brain capillaries and hCMEC/D3 cells showed significant expression of claudin-1 (Table 2). In this regard, a recent study showed that claudin-1 replaces claudin-5 at the TJ of brain capillary endothelial cells during the regeneration phase after stroke. This replacement was associated with a weaker barrier [42]. Considering these data it could be speculated whether the strong expression of claudin-1 in the hCMEC/D3 may also be partly responsible for the weaker barrier of hCMEC/D3 cell layers. Finally, it must be mentioned that Berndt et al. [3] reported that the gene Cldnd1 was expressed in human brain capillaries as the strongest claudin, even significantly more than claudin-5. Cldnd1 was also strongly expressed in mouse brain endothelial cells and seems to have sealing properties [3, 54]. It has to be mentioned that the cell line hCMEC/D3 was originally immortalized from brain endothelial cells isolated from resected brain tissue from an epileptic patient [50]. Thus, it cannot be totally excluded that still disease specific properties are present in this cell line. This could be e.g. relevant for ABC transporter profiles, since it is known that the transporter ABCB1 can be upregulated during epilepsy [22]. The comparison of the expression of ABC transporters in hCMEC/D3 under standard conditions with mRNA and proteomics data from isolated capillaries showed that only ABCB1, ABCG2 and ABCC4 were detected at the protein level in human brain capillaries, whereas on the mRNA level ABCB1, ABCC5, ABCG2, ABCC1 and ABCC4 could be found in this expression order (ABCC2 and ABCC3 were not measured on the mRNA level in the brain capillaries [23, 40, 45]). Analysis of hCMEC/D3 samples showed that all tested ABC transporters of this work were also found in previous publications, but partly in different order (mRNA: ABCB1, ABCC3, ABCC1, ABCC4, ABCC5 and very little ABCC2, [48]; protein: ABCB1, ABCG2, ABCC1, ABCC4 (ABCC2, 3 and 5 under detection limit); [35]. This may also have been due to the fact that a different basal growth medium was used in the compared publication or barrier regulating supplements such as hydrocortisone were already present in the medium [48]. For this reason, the effects of switching the medium from EBM-2 to DMEM for the OGD experiment were also investigated as a parameter of transcript analysis. In this regard, it is known that EBM-2 basal medium contains significantly less glucose than the used DMEM (1.2 versus 4.5 g glucose/L) and that ABC transporters can be regulated by different glucose levels [39]. Moreover, it was shown recently that sole medium exchange in the controls of OGD experiments led to a significant decrease of paracellular tightness of a BBB in vitro model based on primary endothelial cells [44]. In addition, the influence of serum reduction and the addition of hydrocortisone was included in the study as both treatments were used to increase the low claudin-5 content and thus the paracellular barrier of hCMEC/D3 layers [14]. The mRNA expression data were then not only used to learn about the relative regulations dependent on the different conditions, they were also subjected to hierarchical cluster analysis (Figs. 3, 5 and 7) to identify more general regulation patterns. In this case, the differences in experimental designs should be not neglected such as the type of growth surface (well plates—Fig. 3; Transwell inserts—Fig. 5 and 7) or the amount of data points (Fig. 3 > than Figs. 5 or 7). However, some general observations could be made. The hypoxia markers VEGFa and SLC2A1 clustered together in every of the three experimental series as expected and confirmed the reliability of the applied method. Interestingly, several target pairs clustered together only in both Transwell experimental set-ups, for example, claudin-1 with claudin-15, claudin-17 with claudin-25, ABCC3 with JAM-1, ABCG2 with tricellulin and CDH5 with claudin-6. On the contrary, ABCC3 clustered with claudin-3 and claudin-4 in the co-culture Transwell experiment with human primary astrocytes/pericytes (Fig. 7) as well as in the well-plate experiment (Fig. 2) just like claudin-5 with claudin-18 tv2a, whereas ABCB1 clustered together with ZO-1 in the co-culture set-up with glioma C6 cells (Fig. 5) and the well-plate experiment (Fig. 2). Interestingly, the clustering of claudin-3 with claudin-4, claudin-5 with claudin-18 and CDH5 with claudin-6 is concerning paracellular sealing proteins, whereas the clustering of claudin-17 with claudin-25 represented a claudin pair which is known for paracellular pore-formation [3]. In case of the cluster pair ABCG2 and tricellulin it was shown for both targets that they were regulated under hypoxic or OGD conditions [9, 44].

Although claudin-1 and claudin-5 were not found in the same cluster of the first level, these two major sealing proteins were located in quite near clusters (Figs. 3 and 5) indicating possible connected regulations. In this regard, Sladojevic et al. (2018) reported that claudin-1 was embedded in the TJ complex after stroke and counteracted regeneration processes by inhibiting the renewal of claudin-5 within the TJ structure. In summary, it was shown that hierarchical cluster analysis could be used to suggest novel regulatory relationships of barrier targets, but also highlighted that single experimental manipulations can have a significant impact on the outcome. Further in-depth studies have to be conducted to investigate and validate the found relationships on a molecular level.