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. 2019 Nov 8;11(11):587.
doi: 10.3390/pharmaceutics11110587.

IVIVC Assessment of Two Mouse Brain Endothelial Cell Models for Drug Screening

Ina Puscas  1 , Florian Bernard-Patrzynski  1 , Martin Jutras  1 , Marc-André Lécuyer  2   3 , Lyne Bourbonnière  2 , Alexandre Prat  2 , Grégoire Leclair  1 , V Gaëlle Roullin  1
Affiliations

IVIVC Assessment of Two Mouse Brain Endothelial Cell Models for Drug Screening

Ina Puscas et al. Pharmaceutics. .

Erratum in

Abstract

Since most preclinical drug permeability assays across the blood-brain barrier (BBB) are still evaluated in rodents, we compared an in vitro mouse primary endothelial cell model to the mouse b.End3 and the acellular parallel artificial membrane permeability assay (PAMPA) models for drug screening purposes. The mRNA expression of key feature membrane proteins of primary and bEnd.3 mouse brain endothelial cells were compared. Transwell® monolayer models were further characterized in terms of tightness and integrity. The in vitro in vivo correlation (IVIVC) was obtained by the correlation of the in vitro permeability data with log BB values obtained in mice for seven drugs. The mouse primary model showed higher monolayer integrity and levels of mRNA expression of BBB tight junction (TJ) proteins and membrane transporters (MBRT), especially for the efflux transporter Pgp. The IVIVC and drug ranking underlined the superiority of the primary model (r2 = 0.765) when compared to the PAMPA-BBB (r2 = 0.391) and bEnd.3 cell line (r2 = 0.019) models. The primary monolayer mouse model came out as a simple and reliable candidate for the prediction of drug permeability across the BBB. This model encompasses a rapid set-up, a fair reproduction of BBB tissue characteristics, and an accurate drug screening.

Keywords: IVIVC; bEnd.3 cell line; blood-brain barrier; mouse brain microvascular endothelial cells; primary cell culture.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
mRNA expression fold-change between BMEC and bEnd.3 cells, the latter used as the calibrator. Both cell monolayers were either grown in simple DMEM medium (a) or in specialized BMEC medium (b). Relative gene expression was calculated using the 2−ΔΔCt method, with HPRT as the housekeeping gene and the bEnd.3 cell line as the calibrator. Bars indicate the average mRNA fold change ± SD (n = 3). Data were analyzed using an unpaired t test with Welch’s correction (non-statistically significant (ns): p ≥ 0.0332, * p < 0.0332, ** p < 0.0021, *** p < 0.0002).
Figure 2
Figure 2
Effect of puromycin on BMEC (blue) and bEnd.3 cell (red) viability. Data were analyzed using a 2-way ANOVA test (*** p < 0.0001). Points represent the average cell viability ± SD (n = 6).
Figure 3
Figure 3
(a) Transendothelial electrical resistance (TEER, expressed as Ω × cm2) and (b) endothelial Pe for sodium fluorescein (NaFl) and FITC-dextran (Pe, expressed in cm/s) of the blood–brain barrier models built from mouse primary brain endothelial cells (BMEC, blue) and from mouse brain endothelial cell line (bEnd.3, red) at day 7. All data are presented as means ± SD (n = 12 for TEER, n = 4 for Pe). Statistical analysis: unpaired t test with Welch’s correction (ns: p ≥ 0.0332, **** p < 0.0001, ND-not detected).
Figure 4
Figure 4
Differences in the fold-change of gene expression between (a) BMEC and (b) bEnd.3 cells grown on a polyester membrane insert filter compared to cells grown on plastic cell culture flask. Relative gene expression was calculated using the 2−ΔΔCt method, with HPRT as the housekeeping gene and cells grown on the plastic cell culture flask as the calibrator. Data were analyzed using an unpaired t test with Welch’s correction (ns: p ≥ 0.0332, * p < 0.0332, ** p < 0.0021, *** p < 0.0002, **** p < 0.0001). The bars indicate the average mRNA fold change ± SD (n = 3).
Figure 5
Figure 5
Linear regression plots for in vitro Pe–in vivo log BB correlation (IVIVC) using different models for seven drugs: (a) PAMPA-BBB, (b) bEnd.3 model and (c) BMEC. Pe measurements were realized on day 7. LogBB were quantify 2 h post drugs injection. (d) Distribution of drug ranking according to the selected model. D1: chlorpromazine; D2: midazolam, D3 caffeine, D4: theophylline, D5: verapamil, D6: atenolol, D7: tenoxicam. Each point indicates the average Log BB or Log Pe for a given drug (n ≥ 4).
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