Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2022.05.03.490335

Nuclear receptor ligand screening in an iPSC-derived in vitro blood-brain barrier model identifies new contributors to leptin transport

Shi, Y.·Kim, H.·Hamann, C. A.·Rhea, E. M.·Brunger, J. M.·Lippmann, E. S.
View original source ↗Export metadata ↓

Abstract

BackgroundThe peptide hormone leptin exerts its function in the brain to reduce food intake and increase energy expenditure to prevent obesity. However, most obese subjects reflect the resistance to leptin even with elevated serum leptin. Considering that leptin must cross the blood-brain barrier (BBB) in several regions to enter the brain parenchyma, altered leptin transport through the BBB might play an important role in leptin resistance and other biological conditions. Here, we report the use of a human induced pluripotent stem cell (iPSC)-derived BBB model to explore mechanisms that influence leptin transport. MethodsiPSCs were differentiated into brain microvascular endothelial cell (BMEC)-like cells using standard methods. BMEC-like cells were cultured in Transwell filters, treated with ligands from a nuclear receptor agonist library, and assayed for leptin transport using an enzyme-linked immune sorbent assay. RNA sequencing was further used to identify differentially regulated genes and pathways. The role of a select hit in leptin transport was tested with the competitive substrate assay and after gene knockdown using CRISPR techniques. ResultsFollowing a screen of 73 compounds, 17{beta}-estradiol was identified as a compound that could significantly increase leptin transport. RNA sequencing revealed many differentially expressed transmembrane transporters after 17{beta}-estradiol treatment. Of these, cationic amino acid transporter-1 (CAT-1, encoded by SLC7A1) was selected for follow-up analyses due to its high and selective expression in BMECs in vivo. Treatment of BMEC-like cells with CAT-1 substrates, as well as knockdown of CAT-1 expression via CRISPR-mediated epigenome editing, yielded significant increases in leptin transport. ConclusionsA major female sex hormone, as well as an amino acid transporter, were revealed as regulators of leptin BBB transport in the iPSC-derived BBB model. Outcomes from this work provide insights into regulation of peptide hormone transport across the BBB.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Shi, Y., Kim, H., Hamann, C. A., Rhea, E. M., Brunger, J. M., Lippmann, E. S.. 2022-05-03. Nuclear receptor ligand screening in an iPSC-derived in vitro blood-brain barrier model identifies new contributors to leptin transport. https://doi.org/10.1101/2022.05.03.490335

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗
bioRxiv2026

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗
bioRxiv2026

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗