Biology subjects

Augustin, J. J.

Publications and source records attributed to Augustin, J. J..

5 recordsLinked to original sources

bioRxiv2026

Scalable high-fidelity human vascularized cortical assembloids recapitulate neurovascular co-development and cell specialization

Human cortical development involves the coupling of neurogenesis and cerebrovascular growth. However, interactions between neural and vascular cells are largely missing in most brain organoids, which are crucial models for studying neurodevelopment and disease. Here, we establish vascularized cortical assembloids (vCAs) by fusing mesoderm-derived vascular organoids (VOs) with cortical organoids (COs). vCAs self-assemble lumenized networks of endothelial cells, pericytes, and perivascular fibroblasts that acquire blood-brain barrier (BBB) specialization and arteriovenous specification in vitro. Single-cell RNA-sequencing and immunofluorescence imaging revealed that vascularization improves neuroepithelial architecture, reduces hypoxia and apoptosis, expands cortical progenitor pools, and enhances neuronal maturation and connectivity compared with COs. Moreover, atlas-level integration with human neurodevelopmental tissue and cross-protocol benchmarking demonstrate superior transcriptional concordance, especially for vascular cell and glial populations, relative to existing approaches. This scalable and reproducible platform improves fidelity and throughput for modeling human neurovascular co-development and enables systematic studies across brain regions and diseases using engineered or patient-derived iPSCs.

developmental biology↗

bioRxiv2024

Molecular and cellular dynamics of the developing human neocortex at single-cell resolution

The development of the human neocortex is a highly dynamic process and involves complex cellular trajectories controlled by cell-type-specific gene regulation1. Here, we collected paired single-nucleus chromatin accessibility and transcriptome data from 38 human neocortical samples encompassing both the prefrontal cortex and primary visual cortex. These samples span five main developmental stages, ranging from the first trimester to adolescence. In parallel, we performed spatial transcriptomic analysis on a subset of the samples to illustrate spatial organization and intercellular communication. This atlas enables us to catalog cell type-, age-, and area-specific gene regulatory networks underlying neural differentiation. Moreover, combining single-cell profiling, progenitor purification, and lineage-tracing experiments, we have untangled the complex lineage relationships among progenitor subtypes during the transition from neurogenesis to gliogenesis in the human neocortex. We identified a tripotential intermediate progenitor subtype, termed Tri-IPC, responsible for the local production of GABAergic neurons, oligodendrocyte precursor cells, and astrocytes. Remarkably, most glioblastoma cells resemble Tri-IPCs at the transcriptomic level, suggesting that cancer cells hijack developmental processes to enhance growth and heterogeneity. Furthermore, by integrating our atlas data with large-scale GWAS data, we created a disease-risk map highlighting enriched ASD risk in second-trimester intratelencephalic projection neurons. Our study sheds light on the gene regulatory landscape and cellular dynamics of the developing human neocortex.

neuroscience↗

bioRxiv2022

Pantr2, a trans-acting lncRNA, modulates the differentiation potential of neural progenitors in vivo

Ablation of the long non-coding RNA (lncRNA) Pantr2 results in microcephaly in a knockout murine model of corticogenesis, however, the precise mechanisms used are unknown. We present evidence that Pantr2 is a trans-acting lncRNA that regulates gene expression and chromatin accessibility both in vivo and in vitro. We demonstrate that ectopic expression of Pantr2 in a neuroblastoma cell line alters gene expression under differentiating conditions, and that both loss and gain of function of Pantr2 results in changes to cell-cycle dynamics. We show that expression of both the transcription factor Nfix and the cell cycle regulator Rgcc are negatively regulated by Pantr2. Using RNA binding protein motif analysis and existing CLIP-seq data, we annotate potential HuR and QKI binding sites on Pantr2, and demonstrate that HuR does not directly bind Pantr2 using RNA immunoprecipitation assay. Finally, using Gene Ontology enrichment analysis, we identify disruption of both Notch and Wnt signaling following loss of Pantr2 expression, indicating potential Pantr2-dependent regulation of these pathways.

neuroscience↗

bioRxiv2021

Universal prediction of cell cycle position using transfer learning

BackgroundThe cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data. ResultsHere, we present tricycle, an R/Bioconductor package, to address this challenge by leveraging key features of the biology of the cell cycle, the mathematical properties of principal component analysis of periodic functions, and the use of transfer learning. We estimate a cell cycle embedding using a fixed reference dataset and project new data into this reference embedding; an approach that overcomes key limitations of learning a dataset dependent embedding. Tricycle then predicts a cell-specific position in the cell cycle based on the data projection. The accuracy of tricycle compares favorably to gold-standard experimental assays, which generally require specialized measurements in specifically constructed in vitro systems. Using internal controls which are available for any dataset, we show that tricycle predictions generalize to datasets with multiple cell types, across tissues, species and even sequencing assays. ConclusionsTricycle generalizes across datasets, is highly scalable and applicable to atlas-level single-cell RNA-seq data.

genomics↗

bioRxiv2018

Transcriptional suppression from KMT2D loss disrupts cell cycle and hypoxic responses in neurodevelopmental models of Kabuki syndrome

Chromatin modifiers act to coordinate gene expression changes critical to neuronal differentiation from neural stem/progenitor cells (NSPCs). Lysine-specific methyltransferase 2D (KMT2D) encodes a histone methyltransferase that promotes transcriptional activation, and is frequently mutated in cancers and in the majority (>70%) of patients diagnosed with the congenital, multisystem intellectual disability (ID) disorder Kabuki syndrome 1 (KS1). Critical roles for KMT2D are established in various non-neural tissues, but the effects of KMT2D loss in brain cell development have not been described. We conducted parallel studies of proliferation, differentiation, transcription, and chromatin profiling in KMT2D-deficient human and mouse models to define KMT2D-regulated functions in neurodevelopmental contexts, including adult-born hippocampal NSPCs in vivo and in vitro. We report cell-autonomous defects in proliferation, cell cycle, and survival, accompanied by early NSPC maturation in several KMT2D-deficient model systems. Transcriptional suppression in KMT2D-deficient cells indicated strong perturbation of hypoxia-responsive metabolism pathways. Functional experiments confirmed abnormalities of cellular hypoxia responses in KMT2D-deficient neural cells, and accelerated NSPC maturation in vivo. Together, our findings support a model in which loss of KMT2D function suppresses expression of oxygen-responsive gene programs important to neural progenitor maintenance, resulting in precocious neuronal differentiation in a mouse model of KS1.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC=\"FIGDIR/small/484410v3_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (22K):\norg.highwire.dtl.DTLVardef@55dd1aorg.highwire.dtl.DTLVardef@1270c80org.highwire.dtl.DTLVardef@a5bda2org.highwire.dtl.DTLVardef@144df37_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗