de Kok, M. | Search bioRxiv

bioRxiv2025

Pericytes and Wnt signaling induce functional blood-brain barrier phenotype in human iPSC-based model

The blood-brain barrier (BBB), formed by brain microvascular endothelial cells (BMECs), restricts vascular permeability through tight junctions, selective transporters, and low transcytosis. BBB dysfunction contributes to cerebrovascular and neurodegenerative disease, yet current human in vitro models recapitulate only a subset of BMEC features. Here, we describe a strategy generate BMECs (hiBMECs) from human induced pluripotent stem cell-derived endothelial cells by co-culture with isogenic brain pericytes and activation of Wnt/{beta}-catenin signaling. The resulting hiBMECs display barrier properties, active efflux transporters, and appropriate inflammatory responses. Transcriptomic profiling revealed convergence of pericyte-derived cues and Wnt/{beta}-catenin activation on ETS1, SMAD3/4, and PPAR{gamma} transcriptional networks, establishing a gene signature closely matching the adult human BBB. Downstream analysis revealed that hiBPC cues engaged sphingosine-1-phosphate, TGF-{beta}, and angiopoietin/Tie2 pathways, which were further regulated by canonical Wnt activation. These findings uncover a synergistic mechanism by which brain pericytes and Wnt/{beta}-catenin signaling orchestrate BMEC differentiation and function, providing mechanistic insight into human BBB development and an improved hiPSC-derived BBB model for future drug screening and disease modeling. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=36 SRC="FIGDIR/small/678752v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@186ba4corg.highwire.dtl.DTLVardef@310cc7org.highwire.dtl.DTLVardef@3e1970org.highwire.dtl.DTLVardef@f80f5e_HPS_FORMAT_FIGEXP M_FIG C_FIG The paper explainedO_ST_ABSPROBLEMC_ST_ABSThe blood-brain barrier (BBB) protects the brain by tightly regulating the passage of molecules and cells. Its dysfunction contributes to disorders such as stroke, dementia, and multiple sclerosis. Yet, existing human in vitro models fail to capture the full complexity of BBB biology, limiting our ability to study disease mechanisms or test brain-targeted drugs. RESULTSWe discovered that two signals are essential for generating functional human BBB endothelial cells from stem cells: cues from brain pericytes and activation of the Wnt/{beta}-catenin pathway. Together, these signals enabled endothelial cells to form tight barriers, operate transporters, and mount appropriate responses to inflammation. Transcriptomic analyses of the resulting cells revealed a gene signature closely matching the adult human BBB and identified how pericyte- and Wnt-activated pathways converge on specific transcriptional programs driving BBB identity. IMPACTThis study provides both a molecular framework for in vitro BBB development and a reliable and reproducible human BBB model. This platform can be applied to explore BBB dysfunction in neurological disease and to accelerate the development of drugs that need to reach the brain or target the brain vasculature.

bioengineering↗

bioRxiv2023

Unbiased method for spectral analysis of cells with great diversity of autofluorescence spectra

Autofluorescence is an intrinsic feature of cells, caused by the natural emission of light by its cellular content, that can complicate analysis of flow cytometry data. Different cell types have different autofluorescence spectra and even within one cell type heterogeneity of autofluorescence spectra can be present, for example as a consequence of activation status or metabolic changes. By using full spectrum flow cytometry, the emission spectrum of a fluorochrome is captured by a set of detectors across a range of wavelengths, creating an unique spectrum for this fluorochrome, that is used to unmix the signal of a full stained sample into the signals of the different fluorochromes. Importantly, this technology can also be used to identify the aut-ofluorescence signal of an unstained sample, which can be used for unmixing purposes and to separate the autofluorescence signal from the fluorophore signals. However, this only works if the sample has one homogeneous autofluorescence spectrum. To analyze samples with a heterogeneous autofluorescence spectral profile, we here setup an unbiased workflow to detect all different autofluorescence spectra present in a sample to take them along as autofluorescence signatures during the unmixing of the full stained samples. First, clusters of cells with similar autofluorescence spectra are identified by unbiased dimensional reduction and clustering. Then, unique autofluorescence clusters are determined and are used to improve the unmixing accuracy of the full stained sample. This unbiased method allows for the identification of all autofluorescence spectra present in a sample, independent of cell types and intensity of the autofluorescence spectra. Furthermore, this method is equally useful for spectral analysis of different biological samples, including tissue cell suspensions, peripheral blood mononuclear cells and in vitro cultures of (primary) cells.

cell biology↗