Benchmarking in vitro tissue-engineered blood–brain barrier models

Abstract The blood–brain barrier (BBB) plays a key role in regulating transport into and out of the brain. With increasing interest in the role of the BBB in health and disease, there have been significant advances in the development of in vitro models. The value of these models to the research community is critically dependent on recapitulating characteristics of the BBB in humans or animal models. However, benchmarking in vitro models is surprisingly difficult since much of our knowledge of the structure and function of the BBB comes from in vitro studies. Here we describe a set of parameters that we consider a starting point for benchmarking and validation. These parameters are associated with structure (ultrastructure, wall shear stress, geometry), microenvironment (basement membrane and extracellular matrix), barrier function (transendothelial electrical resistance, permeability, efflux transport), cell function (expression of BBB markers, turnover), and co-culture with other cell types (astrocytes and pericytes). In suggesting benchmarks, we rely primarily on imaging or direct measurements in humans and animal models

Functional brain-specific microvessels from iPSC-derived human brain microvascular endothelial cells: the role of matrix composition on monolayer formation

Abstract Background Transwell-based models of the blood–brain barrier (BBB) incorporating monolayers of human brain microvascular endothelial cells (dhBMECs) derived from induced pluripotent stem cells show many of the key features of the BBB, including expression of transporters and efflux pumps, expression of tight junction proteins, and physiological values of transendothelial electrical resistance. The fabrication of 3D BBB models using dhBMECs has so far been unsuccessful due to the poor adhesion and survival of these cells on matrix materials commonly used in tissue engineering. Methods To address this issue, we systematically screened a wide range of matrix materials (collagen I, hyaluronic acid, and fibrin), compositions (laminin/entactin), protein coatings (fibronectin, laminin, collagen IV, perlecan, and agrin), and soluble factors (ROCK inhibitor and cyclic adenosine monophosphate) in 2D culture to assess cell adhesion, spreading, and barrier function. Results Cell coverage increased with stiffness of collagen I gels coated with collagen IV and fibronectin. On 7 mg mL−1 collagen I gels coated with basement membrane proteins (fibronectin, collagen IV, and laminin), cell coverage was high but did not reliably reach confluence. The transendothelial electrical resistance (TEER) on collagen I gels coated with basement membrane proteins was lower than on coated transwell membranes. Agrin, a heparin sulfate proteoglycan found in basement membranes of the brain, promoted monolayer formation but resulted in a significant decrease in transendothelial electrical resistance (TEER). However, the addition of ROCK inhibitor, cAMP, or cross-linking the gels to increase stiffness, resulted in a significant improvement of TEER values and enabled the formation of confluent monolayers. Conclusions Having identified matrix compositions that promote monolayer formation and barrier function, we successfully fabricated dhBMEC microvessels in cross-linked collagen I gels coated with fibronectin and collagen IV, and treated with ROCK inhibitor and cAMP. We measured apparent permeability values for Lucifer yellow, comparable to values obtained in the transwell assay. During these experiments we observed no focal leaks, suggesting the formation of tight junctions that effectively block paracellular transport

A tissue-engineered model of the blood-tumor barrier during metastatic breast cancer

Abstract Metastatic brain cancer has poor prognosis due to challenges in both detection and treatment. One contributor to poor prognosis is the blood–brain barrier (BBB), which severely limits the transport of therapeutic agents to intracranial tumors. During the development of brain metastases from primary breast cancer, the BBB is modified and is termed the ‘blood-tumor barrier’ (BTB). A better understanding of the differences between the BBB and BTB across cancer types and stages may assist in identifying new therapeutic targets. Here, we utilize a tissue-engineered microvessel model with induced pluripotent stem cell (iPSC)-derived brain microvascular endothelial-like cells (iBMECs) and surrounded by human breast metastatic cancer spheroids with brain tropism. We directly compare BBB and BTB in vitro microvessels to unravel both physical and chemical interactions occurring during perivascular cancer growth. We determine the dynamics of vascular co-option by cancer cells, modes of vascular degeneration, and quantify the endothelial barrier to antibody transport. Additionally, using bulk RNA sequencing, ELISA of microvessel perfusates, and related functional assays, we probe early brain endothelial changes in the presence of cancer cells. We find that immune cell adhesion and endothelial turnover are elevated within the metastatic BTB, and that macrophages exert a unique influence on BTB identity. Our model provides a novel three-dimensional system to study mechanisms of cancer-vascular-immune interactions and drug delivery occurring within the BTB

Additional file 3 of Three-dimensional microenvironment regulates gene expression, function, and tight junction dynamics of iPSC-derived blood–brain barrier microvessels

Additional file 3. Summary of tight junction dynamics data

Additional file 2 of Three-dimensional microenvironment regulates gene expression, function, and tight junction dynamics of iPSC-derived blood–brain barrier microvessels

Additional file 2. Summary of bulk RNA-sequencing data

Additional file 1 of Three-dimensional microenvironment regulates gene expression, function, and tight junction dynamics of iPSC-derived blood–brain barrier microvessels

Additional file 1: Figure S1. Characterization of iBMEC phenotype following differentiation in 1 mL or 2 mL of medium. Figure S2. TEER and permeability measurements of 2D iBMEC confluent monolayers. Figure S3. Media volume effect on phenotype of 2D iBMEC confluent monolayers. Figure S4. Details of bulk RNA sequencing and iPC characterization. Figure S5. Benchmarking iBMEC gene expression to brain microvessel, endothelial, and epithelial datasets. Figure S6. Abundance measurements of endothelial and epithelial transcripts across cell sources and model types. Figure S7. Images of angiogenic sprouts across models. Figure S8. Assessment of tight junction dynamics in confluent iBMEC monolayers. Figure S9. Time course of morphological metrics across cell types. Figure S10. Violin plots of metrics across cell types. Figure S11. Response of three-dimensional iBMEC microvessels to wound formation by laser ablation. Figure S12. Comparison of morphological metrics between homeostasis, ablation, and melittin exposure. Figure S13. Monolayer area dynamics during wound healing and melittin exposure. Table S1. Summary of bulk RNA transcriptomes used in this study. Table S2. Antibodies used in this study. Note S1. Validation of media volume effect on TEER. Note S2. Variability of iBMEC differentiation. Note S3. Mechanisms of media volume effect on iBMEC phenotype. Note S4. Calculation of permeability in 2D and 3D. iBMEC differentiation. Transwell barrier characterization. Oxygen and glucose recordings. Pericyte differentiation and characterization