Biology subjects

Engelhardt, B.

Publications and source records attributed to Engelhardt, B..

15 recordsLinked to original sources

bioRxiv2026

Extracellular methylglyoxal; the passage across brain endothelial cells and the effect on barrier function

BackgroundMethylglyoxal (MGO), a highly reactive by-product of glycolysis, has been associated with cognitive decline and Alzheimers disease, though the mechanistic role of MGO remains unclear. Moreover, conflicting findings exist regarding MGOs toxicity on the blood-brain barrier (BBB). This study investigated whether MGO can cross the BBB under physiologically relevant conditions and whether MGO affects BBB permeability. MethodsMice were intravenously injected with highly purified home-made MGO or PBS, and MGO concentration was measured at five timepoints in the cerebral cortex up to 4 hours after injection. MGO toxicity was screened on a human brain endothelial cell line (hCMEC/D3) using a live/dead assay prior to the study of selected MGO concentrations and on hiPSC-derived brain microvascular endothelial cells (EECM-BMECs). EECM-BMECs were cultured on Transwell(R) inserts, and barrier function was assessed by sodium fluorescein permeability and transendothelial passage of 13C3-MGO quantified by UPLC-MS/MS. ResultsMGO levels in the mouse cortex did not increase post-injection. MGO was not toxic to hCMEC/D3 cells, and it had no impact on barrier properties of EECM-BMECs. After 1-hour exposure, [~]13% of total 13C3-MGO was recovered in its free form, and only [~]1% of supplemented MGO was recovered from the abluminal side. ConclusionMGO does not cross the BBB in vivo and does not affect barrier properties of a human in vitro model of the BBB. In vitro MGO passage across the BBB is minimal. These findings suggest that circulating MGO is unlikely to directly affect neuronal function via BBB disruption or enter the brain in its free from.

neuroscience↗

bioRxiv2025

Vitamin D differentially modulates effector and regulatory T-cell migration across the blood-brain barrier

Multiple sclerosis (MS) is an inflammatory disease of the CNS influenced by a combination of genetic predisposition and environmental factors. Vitamin D (VitD) deficiency is considered a major risk factor for MS. While VitD is associated with immunomodulatory roles, the exact mechanisms by which VitD protects from disease are still largely unknown. CD4 T cells play a key role in MS pathogenesis with autoimmune effector T cells (Teff) infiltrating the CNS across the blood-brain barrier (BBB) and regulatory T cells (Treg) displaying impaired functions. Here we show that treatment of human CD4 T cells with the active form of VitD (1,25-Dihydroxyvitamin D3; 1,25(OH)2D3) decreased cell-surface expression of 4{beta}1- and L{beta}2-integrins on Teff but not Treg and reduced Teff adhesion to their endothelial ligands VCAM-1 and ICAM-1. By employing live cell imaging, we observed that VitD treatment reduced arrest of Teff but not Treg to the BBB as well as ICAM-1 and VCAM-1 under physiological flow in vitro and differentially affected post-arrest behaviour of Teff versus Treg on the BBB under physiological flow. Furthermore, VitD treatment favoured the migration of Treg over Teff across the BBB under static and flow conditions in vitro. In vivo live cell imaging showed that VitD reduced T cell arrest on the inflamed BBB during autoimmune neuroinflammation. Finally, VitD also reduced expression of integrins mediating CNS homing on pathogenic CD4 T cells isolated from the CSF of persons with MS (PwMS). As VitD treatment did not alter barrier properties or adhesion molecule profile of our BBB model we propose a beneficial effect of VitD supplementation in PwMS by reducing CNS trafficking of pro-inflammatory T cells while leaving CNS entry of Treg unaffected.

immunology↗

bioRxiv2025

Pericytes Repair Engineered Defects in the Basement Membrane to Restore Barrier Integrity in an in vitro Model of the Blood-Brain Barrier.

Pericytes play a key role in the brain where they support the blood-brain barrier (BBB). Their loss has been reported in response to systemic inflammation and neurodegenerative disease. We recently demonstrated that iPSC-derived brain pericyte-like cells (BPLCs) and brain microvascular endothelial cell (BMEC)-like cells collaboratively form a nascent, 3D basement membrane when cultured across a nanoporous membrane1. Building on this, we aimed to engineer defects in the basement membrane to investigate whether pericytes could facilitate its repair. In BMEC monocultures, we observed that micropore patterns in nanomembranes created discontinuities in laminin, which destabilized barrier function. Remarkably, the addition of pericytes to the basal side of the membrane restored both laminin integrity and barrier function. Our results align with the role of pericytes as support cells for microvasculature and encourage the use of our tissue barrier platform (the {micro}SiM) to model neurological disorders involving pericyte dysfunction and/or disruption of basement membrane.

bioengineering↗

bioRxiv2023

CITE-seq reveals inhibition of NF-kB pathway in B cells from vitamin D-treated multiple sclerosis patients

Vitamin D deficiency is a recognized risk factor for multiple sclerosis (MS) and has been associated with disease activity and progression. Vitamin D treatment has emerged as potentially protective, despite conflicting results from randomized controlled trials. Here, we used single-cell RNA-sequencing (scRNA-seq) combined with barcoded antibodies targeting surface markers (CITE-seq) to uncover candidate genes and pathways regulated in PBMC subpopulations from MS patients receiving high-dose vitamin D (n=5) or placebo (n=5). Best candidates were combined with genes involved in immune function and vitamin D metabolism for validation in a new cohort (n=8 in each group) by high-throughput quantitative polymerase chain reaction (HT-qPCR) in FACS-sorted naive CD4, Th1, Th17, Treg, naive CD8, memory and naive B cells, and MAIT cells. CITE-seq revealed no significant changes in the proportions of these subpopulations in response to vitamin D treatment. Out of the 92 candidate genes identified by CITE-seq, we validated differential expression of five genes (UXT, SNRPN, SUB1, GNLY and KLF6) using HT-qPCR. Furthermore, CITE-seq uncovered vitamin D-induced regulation of several pathways in naive and memory B cells, including MAPK, TLR and interleukin pathways, that may contribute to counteract Epstein-Barr virus (EBV)-induced resistance to apoptosis, notably through inhibition of the NF-{kappa}B pathway. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/559400v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1ad28c1org.highwire.dtl.DTLVardef@14ed135org.highwire.dtl.DTLVardef@188fea1org.highwire.dtl.DTLVardef@105353c_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2023

UFMTrack: Under-Flow Migration Tracker enabling analysis of the entire multi-step immune cell extravasation cascade across the blood-brain barrier in microfluidic devices

The endothelial blood-brain barrier (BBB) strictly controls immune cell trafficking into the central nervous system (CNS). In neuroinflammatory diseases such as multiple sclerosis, this tight control is, however, disturbed, leading to immune cell infiltration into the CNS. The development of in vitro models of the BBB combined with microfluidic devices has advanced our understanding of the cellular and molecular mechanisms mediating the multi-step T-cell extravasation across the BBB. A major bottleneck of these in vitro studies is the absence of a robust and automated pipeline suitable for analyzing and quantifying the sequential interaction steps of different immune cell subsets with the BBB under physiological flow in vitro. Here we present the Under-Flow Migration Tracker (UFMTrack) framework for studying immune cell interactions with endothelial monolayers under physiological flow. We then showcase a pipeline built based on it to study the entire multi-step extravasation cascade of immune cells across brain microvascular endothelial cells under physiological flow in vitro. UFMTrack achieves 90% track reconstruction efficiency and allows for scaling due to the reduction of the analysis cost and by eliminating experimenter bias. This allowed for an in-depth analysis of all behavioral regimes involved in the multi-step immune cell extravasation cascade. The study summarizes how UFMTrack can be employed to delineate the interactions of CD4+ and CD8+ T cells with the BBB under physiological flow. We also demonstrate its applicability to the other BBB models, showcasing broader applicability of the developed framework to a range of immune cell-endothelial monolayer interaction studies. The UFMTrack framework along with the generated datasets is publicly available in the corresponding repositories. Author summaryImmune cells continuously travel through our body to perform immune surveillance. They travel within blood vessels at a very high speed and slow down upon reaching their target organ by the sequential interaction with different adhesion and signaling molecules on the vascular endothelial cells. The study of molecular mechanisms mediating this multi-step extravasation of immune cells has been significantly advanced by in vitro cultures of microvascular endothelial cell monolayers. The dynamic interaction of the immune cells with endothelial monolayers can be imaged over time in vitro in microfluidic devices under physiological flow. The 2-dimensional structure of the endothelial monolayer allows for reliable visualization of the extravasation process required for the study of the molecular mechanisms involved. The manual analysis of the acquired imaging data is time- consuming and prone to experimenter error. Analysis automation is, however, hampered by the similar appearance of the unlabeled immune and endothelial cells and by the flow causing rapid immune cell displacement. Here we introduce UFMTrack, the under-flow migration tracker framework allowing for automated analysis of immune cell interactions with microvascular endothelial cells under flow in vitro. UFMTrack performs comparably to the manual analysis of an experienced researcher, eliminates experimenters bias, and improves the accuracy of the immune cell tracking. Taken together, UFMTrack sets the stage for scalability of in vitro live cell imaging studies of immune cell extravasation.

immunology↗

bioRxiv2022

A potent and selective inhibitor for the modulation of MAGL activity in the neurovasculature

Chronic inflammation and blood-brain barrier dysfunction are key pathological hallmarks of neurological disorders such as multiple sclerosis, Alzheimers disease and Parkinsons disease. Major drivers of these pathologies include pro-inflammatory stimuli such as prostaglandins, which are produced in the central nervous system by the oxidation of arachidonic acid in a reaction catalyzed by the cyclooxygenases COX1 and COX2. Monoacylglycerol lipase hydrolyzes the endocannabinoid signaling lipid 2-arachidonyl glycerol, enhancing local pools of arachidonic acid in the brain and leading to cyclooxygenase-mediated prostaglandin production and neuroinflammation. Monoacylglycerol lipase inhibitors were recently shown to act as effective anti-inflammatory modulators, increasing 2-arachidonyl glycerol levels while reducing levels of arachidonic acid and prostaglandins, including PGE2 and PGD2. In this study, we characterized a novel, highly selective, potent and reversible monoacylglycerol lipase inhibitor (MAGLi 432) in a mouse model of lipopolysaccharide-induced blood-brain barrier permeability and in both human and mouse cells of the neurovascular unit: brain microvascular endothelial cells, pericytes and astrocytes. We confirmed the expression of monoacylglycerol lipase in specific neurovascular unit cells in vitro, with pericytes showing the highest expression level and activity. However, MAGLi 432 did not ameliorate lipopolysaccharide-induced blood-brain barrier permeability in vivo or reduce the production of pro-inflammatory cytokines in the brain. Our data confirm monoacylglycerol lipase expression in mouse and human cells of the neurovascular unit and provide the basis for further cell-specific analysis of MAGLi 432 in the context of blood-brain barrier dysfunction caused by inflammatory insults.

neuroscience↗

bioRxiv2022

The Modular μSiM: a Mass Produced, Rapidly Assembled, and Reconfigurable Platform for the Study of Barrier Tissue Models In Vitro

Advanced in vitro tissue chip models can reduce and replace animal experimentation and may eventually support on-chip clinical trials. To realize this potential, however, tissue chip platforms must be both mass-produced and reconfigurable to allow for customized design. To address these unmet needs, we introduce an extension of our {micro}SiM (microdevice featuring a silicon-nitride membrane) platform. The modular {micro}SiM (m-{micro}SiM) uses mass-produced components to enable rapid assembly and reconfiguration by laboratories without knowledge of microfabrication. We demonstrate the utility of the m-{micro}SiM by establishing an hiPSC-derived blood-brain barrier (BBB) in bioengineering and non-engineering, brain barriers focused laboratories. We develop and validate in situ and sampling-based assays of small molecule diffusion as a measure of barrier function. BBB properties show excellent interlaboratory agreement and match expectations from literature, validating the m-{micro}SiM as a platform for barrier models and demonstrating successful dissemination of components and protocols. We then demonstrate the ability to quickly reconfigure the m-{micro}SiM for co-culture and immune cell transmigration studies through addition of accessories and/or quick exchange of components. Because the development of modified components and accessories is easily achieved, custom designs of the m-{micro}SiM should be accessible to any laboratory desiring a barrier-style tissue chip platform.

bioengineering↗

bioRxiv2021

Brain endothelial antigen presentation detains CD8+ T cells at the blood-brain barrier leading to its breakdown

Blood-brain barrier (BBB) breakdown and immune cell infiltration into the central nervous system (CNS) are early hallmarks of multiple sclerosis (MS). High numbers of CD8+ T cells are found in MS lesions and antigen (Ag)-presentation at the BBB was proposed to promote CD8+ T-cell entry into the CNS. Employing live cell imaging and primary mouse brain microvascular endothelial cells (pMBMECs) as in vitro model of the BBB and a mouse model of CNS autoimmunity, we here show that pMBMECs process and present antigens leading to effector CD8+ T-cell differentiation. Under physiological flow, endothelial Ag-presentation prohibited CD8+ T-cell crawling and diapedesis leading to pMBMEC apoptosis. Reduced motility of Ag-specific CD8+ T cells was also observed in CNS microvessels in neuroinflammation in vivo. Luminal MHC class I Ag-presentation at the BBB thus prohibits CD8+ T-cell entry into the CNS and rather triggers CD8+ T cell mediated focal BBB breakdown.

immunology↗

bioRxiv2021

Hierarchical Gaussian Processes and Mixtures of Experts to Model COVID-19 Patient Trajectories

Gaussian processes (GPs) are a versatile nonparametric model for nonlinear regression and have been widely used to study spatiotemporal phenomena. However, standard GPs offer limited interpretability and generalizability for datasets with naturally occurring hierarchies. With large-scale, rapidly-updating electronic health record (EHR) data, we want to study patient trajectories across diverse patient cohorts while preserving patient subgroup structure. In this work, we partition our cohort of over 2000 COVID-19 patients by sex and ethnicity. We develop and apply a hierarchical Gaussian process and a mixture of experts (MOE) hierarchical GP model to fit patient trajectories on clinical markers of disease progression. A case study for albumin, an effective predictor of COVID-19 patient outcomes, highlights the predictive performance of these models. These hierarchical spatiotemporal models of EHR data bring us a step closer toward our goal of building flexible approaches to capture patient data that can be used in real-time systems*.

bioinformatics↗

bioRxiv2021

Nano-scale Architecture of Blood-Brain Barrier Tight-Junctions

Tight junctions (TJs) between blood-brain barrier (BBB) endothelial cells construct a robust physical barrier, whose damage underlies BBB dysfunctions related to several neurodegenerative diseases. What makes these highly specialized BBB-TJs extremely restrictive remains unknown. Here, we use super-resolution microscopy (dSTORM) to uncover new structural and functional properties of BBB TJs. Focusing on three major components, Nano-scale resolution revealed sparse (occludin) vs. clustered (ZO1/claudin-5) molecular architecture. Developmentally, permeable TJs become first restrictive to large molecules, and only later to small molecules, with claudin-5 proteins arrangement compacting during this maturation process. Mechanistically, we reveal that ZO1 clustering is independent of claudin-5 in-vivo. In contrast to accepted knowledge, we found that in the developmental context, total levels of claudin-5 inversely correlate with TJ functionality. Our super-resolution studies provide a unique perspective of BBB TJs and open new directions for understanding TJ functionality in biological barriers, ultimately enabling restoration in disease or modulation for drug delivery.

cell biology↗

bioRxiv2021

Wnt signaling mediates acquisition of blood-brain barrier properties in naïve endothelium derived from human pluripotent stem cells

Endothelial cells (ECs) in the central nervous system (CNS) acquire their specialized blood-brain barrier (BBB) properties in response to extrinsic signals, with Wnt/{beta}-catenin signaling coordinating multiple aspects of this process. Our knowledge of CNS EC development has been advanced largely by animal models, and human pluripotent stem cells (hPSCs) offer the opportunity to examine BBB development in an in vitro human system. Here we show that activation of Wnt signaling in hPSC-derived naive endothelial progenitors, but not in matured ECs, leads to robust acquisition of canonical BBB phenotypes including expression of GLUT-1, increased claudin-5, and decreased PLVAP. RNA-seq revealed a transcriptome profile resembling ECs with CNS-like characteristics, including Wnt-upregulated expression of LEF1, APCDD1, and ZIC3. Together, our work defines effects of Wnt activation in naive ECs and establishes an improved hPSC-based model for interrogation of CNS barriergenesis.

neuroscience↗

bioRxiv2019

Cell-specific targeting by Clostridium perfringens β-toxin unraveled: the role of CD31 as the toxin receptor.

Clostridium perfringens {beta}-toxin (CPB) is a highly active hemolysin {beta}-pore forming toxin and the essential virulence factor for a severe, necro-hemorrhagic enteritis in animals and humans. In vivo and in vitro it exerts a remarkable cell type specificity towards endothelial cells, platelets and some leucocytic cell lines. The target cell specificity of CPB is, however, poorly understood and a receptor explaining this selective toxicity has not been identified. This has hampered further research into the pathogenesis of C. perfringens type C induced enteritis. Here we identify Platelet Endothelial Cell Adhesion Molecule-1 (CD31 or PECAM-1) as the specific membrane receptor for CPB on endothelial cells. CD31 expression is essential for CPB toxicity in endothelial cells and lethality in mice and sufficient to render previously resistant cells highly susceptible to the toxin. We further demonstrate, that the extracellular membrane proximal Ig6 domain of CD31 is required for the interaction with CPB and that expression of CD31 corresponds with the specificity of the toxin towards cultured cell lines. Our results thus provide an explanation for the cell type specificity of CPB and can be linked to the characteristic lesions observed a devastating enteric disease in animals and humans.

molecular biology↗

bioRxiv2018

Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology

Histological images are used to identify and to characterize complex phenotypes such as tumor stage. Our goal is to associate histological image phenotypes with high-dimensional genomic markers; the limitations to incorporating histological image phenotypes in genomic studies are that the relevant image features are difficult to identify and extract in an automated way, and confounders are difficult to control in this high-dimensional setting. In this paper, we use convolutional autoencoders and sparse canonical correlation analysis (CCA) on histological images and gene expression levels from paired samples to find subsets of genes whose expression values in a tissue sample correlate with subsets of morphological features from the corresponding sample image. We apply our approach, ImageCCA, to three data sets, two from TCGA and one from GTEx v6, and we find three types of biological associations. In TCGA, we find gene sets associated with the structure of the extracellular matrix and cell wall infrastructure, implicating uncharacterized genes in extracellular processes. Across studies, we find sets of genes associated with specific cell types, including muscle tissue and neuronal cells, and with cell type proportions in heterogeneous tissues. In the GTEx v6 data, we find image features that capture population variation in thyroid and in colon tissues associated with genetic variants, suggesting that genetic variation regulates population variation in tissue morphological traits. The software is publicly available at: https://github.com/daniel-munro/imageCCA.

genomics↗

bioRxiv2018

A robust nonlinear low-dimensional manifold for single cell RNA-seq data

Modern developments in single cell sequencing technologies enable broad insights into cellular state. Single cell RNA sequencing (scRNA-seq) can be used to explore cell types, states, and developmental trajectories to broaden understanding of cell heterogeneity in tissues and organs. Analysis of these sparse, high-dimensional experimental results requires dimension reduction. Several methods have been developed to estimate low-dimensional embeddings for filtered and normalized single cell data. However, methods have yet to be developed for unfiltered and unnormalized count data. We present a nonlinear latent variable model with robust, heavy-tailed error and adaptive kernel learning to estimate low-dimensional nonlinear structure in scRNA-seq data. Gene expression in a single cell is modeled as a noisy draw from a Gaussian process in high dimensions from low-dimensional latent positions. This model is called the Gaussian process latent variable model (GPLVM). We model residual errors with a heavy-tailed Students t-distribution to estimate a manifold that is robust to technical and biological noise. We compare our approach to common dimension reduction tools to highlight our models ability to enable important downstream tasks, including clustering and inferring cell developmental trajectories, on available experimental data. We show that our robust nonlinear manifold is well suited for raw, unfiltered gene counts from high throughput sequencing technologies for visualization and exploration of cell states.

genomics↗

bioRxiv2017

Clustering gene expression time series data using an infinite Gaussian process mixture model

Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP), which jointly models cluster number with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison with state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal novel regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.

bioinformatics↗