Biology subjects

Gibbs, S.

Publications and source records attributed to Gibbs, S..

6 recordsLinked to original sources

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↗

bioRxiv2025

Integration of lymphatic vasculature to a human lymph node-on-chip enhances physiological immune properties

To study systemic human innate and adaptive immune responses in detail, competent in vitro lymph node (LN) models with LN stromal cells (LNSCs) are required to recapitulate the physiological microenvironment. The multicellular organisation of LNs possesses a challenge for designing such microphysiological systems (MPS), particularly with the structural complexity of LNs and the lymphatic vasculature. Here, we established an organotypic LN model with integrated lymphatics in an organ-on-chip (OoC) platform containing a printed sacrificial structure, and studied the influence of a perfused lymphatic endothelial cell (LEC)-lined channel on the LN-on-chip microenvironment. Upon one-week of culture under lymphatic flow, LECs lined the tubular structure forming a lymphatic vessel through the LN model, and stable metabolic conditions within the LN-on-chip were confirmed. Interestingly, LECs in the LN-on-chip displayed the phenotype found in human LNs with upregulation of LEC-specific LN markers, such as atypical chemokine receptor 4 (ACKR4). The presence of the LEC-lined perfused vessel in the LN-on-chip resulted in the increase of native immune cells, most notably B cells, and the secretion of survival and migratory signals, namely interleukin-7 (IL-7) and CC motif chemokine ligand 21 (CCL21). Likewise, LECs promoted the abundance of immune cell clusters closer to the vessel. As such, these features represent an enhanced physiological microenvironment to allow for immune cell migration and interactions for efficient LN functioning. This approach paves the way for LN integration into multi-OoC (MOC) platforms to investigate immunological crosstalk between tissue-derived factors, immune cell trafficking and organ-specific adaptive immune responses.

bioengineering↗

bioRxiv2025

A Sacrificial 3D Printed Vessel-on-Chip Demonstrates a Versatile Approach to Model Connective Tissue Pathology

For in vitro organ models, perfused vasculature is crucial to overcome nutrient diffusion limits and to generate immunocompetent models by allowing trans-endothelial migration of immune cells in and out of the tissue. However, vasculature is often disregarded due to its complexity to generate and the necessity to integrate flow. The aim here was to overcome these limitations by combining 3D printing and multi-organ-chip technology to generate a vascularized, fibroblast-populated connective tissue matrix on-chip. A 3D printed, sacrificial, water-dissolvable structure was incorporated into a multi-organ-chip to generate hollow channels within a collagen/fibrin hydrogel. Subsequently, the channels were populated with endothelial cells. Different hydrogel concentrations of fibrin were used to mimic healthy and early granulation tissue. The vessels were perfused, and stable metabolic/viability conditions (lactate dehydrogenase, glucose, lactate) acquired after 3 days for 7 days total. In high fibrin gels, angiogenic sprouting and increased secretion of angiogenic cytokines was observed. Perfusion with monocytes revealed differentiation into macrophages and migration across the endothelium into the tissue. In conclusion, the versatile, easy method to pattern hydrogels in multi-organ-chips can serve as the basis to build the next generation of vascularized, immunocompetent human organ models, and opens new possibilities to study health and disease.

bioengineering↗

bioRxiv2023

Quantitative image analysis pipeline for detecting circulating hybrid cells in immunofluorescence images with human-level accuracy

Circulating hybrid cells (CHCs) are a newly discovered, tumor-derived cell population identified in the peripheral blood of cancer patients and are thought to contribute to tumor metastasis. However, identifying CHCs by immunofluorescence (IF) imaging of patient peripheral blood mononuclear cells (PBMCs) is a time-consuming and subjective process that currently relies on manual annotation by laboratory technicians. Additionally, while IF is relatively easy to apply to tissue sections, its application on PBMC smears presents challenges due to the presence of biological and technical artifacts. To address these challenges, we present a robust image analysis pipeline to automate the detection and analyses of CHCs in IF images. The pipeline incorporates quality control to optimize specimen preparation protocols and remove unwanted artifacts, leverages a {beta}-variational autoencoder (VAE) to learn meaningful latent representations of single-cell images and employs a support vector machine (SVM) classifier to achieve human-level CHC detection. We created a rigorously labeled IF CHC dataset including 9 patients and 2 disease sites with the assistance of 10 annotators to evaluate the pipeline. We examined annotator variation and bias in CHC detection and then provided guidelines to optimize the accuracy of CHC annotation. We found that all annotators agreed on CHC identification for only 65% of the cells in the dataset and had a tendency to underestimate CHC counts for regions of interest (ROI) containing relatively large amounts of cells (>50,000) when using conventional enumeration methods. On the other hand, our proposed approach is unbiased to ROI size. The SVM classifier trained on the {beta}-VAE encodings achieved an F1 score of 0.80, matching the average performance of annotators. Our pipeline enables researchers to explore the role of CHCs in cancer progression and assess their potential as a clinical biomarker for metastasis. Further, we demonstrate that the pipeline can identify discrete cellular phenotypes among PBMCs, highlighting its utility beyond CHCs.

bioinformatics↗

bioRxiv2021

A framework for multiplex imaging optimization and reproducible analysis

Multiplex imaging technologies are increasingly used for single-cell phenotyping and spatial characterization of tissues; however, transparent methods are needed for comparing the performance of platforms, protocols and analytical pipelines. We developed a python software, mplexable, for reproducible image processing and utilize Jupyter notebooks to share our optimization of signal removal, antibody specificity, background correction and batch normalization of the multiplex imaging with a focus on cyclic immunofluorescence (CyCIF). Our work both improves the CyCIF methodology and provides a framework for multiplexed image analytics that can be easily shared and reproduced.

cancer biology↗

bioRxiv2020

Simultaneous human intracerebral stimulation and HD-EEG: ground-truth for source localization methods

Precisely localizing the sources of brain activity as recorded by EEG is a fundamental procedure and a major challenge for both research and clinical practice. Even though many methods and algorithms have been proposed, their relative advantages and limitations are still not well established. Moreover, these methods involve tuning multiple parameters, for which no principled way of selection exists yet. These uncertainties are emphasized due to the lack of ground-truth for their validation and testing. Here we provide the first open dataset that comprises EEG recorded electrical activity originating from precisely known locations inside the brain of living humans. High-density EEG was recorded as single-pulse biphasic currents were delivered at intensities ranging from 0.1 to 5 mA through stereotactically implanted electrodes in diverse brain regions during pre-surgical evaluation of patients with drug-resistant epilepsy. The uses of this dataset range from the estimation of in vivo tissue conductivity to the development, validation and testing of forward and inverse solution methods.

neuroscience↗