Project description:Temporal lobe epilepsy is the fourth most common neurological disorder with about 40% of patients not responding to pharmacological treatment. Increased cellular loss in the hippocampus is linked to disease severity and pathological phenotypes such as heightened seizure propensity. While the hippocampus is the target of therapeutic interventions such as temporal lobe resection, the impact of the disease at the cellular level remains unclear in humans. Here we show that properties of hippocampal granule cells change with disease progression as measured in living, resected hippocampal tissue excised from epilepsy patients. We show that granule cells increase excitability and shorten response latency while also enlarging in cellular volume, surface area and spine density. Single-cell RNA sequencing combined with simulations ascribe the observed electrophysiological changes to gradual modification in three key ion channel conductances: BK, Cav2.2 and Kir2.1. In a bio-realistic computational network model, we show that the changes related to disease progression bring the circuit into a more excitable state. In turn, we observe that by reversing these changes in the three key conductances produces a less excitable, “early disease-like” state. These results provide mechanistic understanding of epilepsy in humans and will inform future therapies such as viral gene delivery to reverse the course of the disorder.
Project description:Plasma cells are key components of humoral immunity by secreting antibodies and providing protection against pathogens. These cells can be of IgM, IgA, or IgG subclass and migrate to class-specific niches. Localization and rareness of plasma cells make it challenge to define subclass-specific molecular hallmarks. Here, we describe how in-vitro differentiation of peripheral B-cells results in antibody-secreting plasma cells. Using a single-cell multi-modal sequencing approach (RAID) we find subclass-specific hallmark transcriptional profiles, surface protein expression and signaling pathway activation.
Project description:Epilepsy causes altered gene expression; transient adenosine treatment inhibits progression of epileptogenesis Hippocampus of epileptic rat is hypermethylated compared to naïve; adenosine treatment causes hypomethylation Metylation state in epileptic rats (9 weeks post kainic acid induced status epilepticus) was compared to naïve (untreated) rats and epileptic rats treated with adenosine for 5 days
Project description:We report dynamics of X-chromosome upregulation (XCU) along X-chromosome inactivation (XCI) in mESCs as they differentiate into EpiSCs. F1 hybrid C57BL6/J × CAST/EiJ male and female mESCs were grown in serum/LIF conditions were differentiated using Fgf2 and Activin A for 1, 2, 4 and 7 days to induce random XCI in female cells. Multi-modal single-cell sequencing was performed using scATAC on nuclei and Smart-seq3 to assay chromatin accessibility and poly-A+ RNA expression, respectively. Allelic resolution is achieved using strain-specific SNPs in the data. We reveal dynamic balancing of X alleles as cells undergo XCI to compensate dosage imbalances between sexes as well as between X and autosomes. Furthermore, we reveal that female naïve mESCs with two active X chromosomes lack XCU on both alleles which has major implications for reprogramming studies. Finally, we estimate allelic transcriptional burst kinetics from the data and find that progressively increased burst frequencies underlies the XCU process.
Project description:As people become more motivated to exercise regularly and stay healthy, tendinopathy is a common problem in both active athletes and inactive individuals, which imposes a considerable social and economic burden. Here we provide a single-cell multi-modal ATAC + gene expression sequencing in tendinopathy. We have identified pathways and genes regulated in tendinopathy samples that will help contribute to further investigation into the development and molecular hallmarks of tendinopathy.
Project description:The expression of inhibitory immune checkpoint molecules such as PD-L1 is frequently observed in human cancers and can lead to the suppression of T-cell mediated immune responses. Here we apply ECCITE-seq, a technology which combines pooled CRISPR screens with single-cell mRNA and surface protein measurements, to explore the molecular networks that regulate PD-L1 expression. We also develop a computational framework, mixscape, that substantially improves the signal-to-noise ratio in single-cell perturbation screens by identifying and removing confounding sources of variation. Applying these tools, we identify and validate regulators of PD-L1, and leverage our multi-modal data to identify both transcriptional and post-transcriptional modes of regulation. In particular, we discover that the kelch-like protein KEAP1 and the transcriptional activator NRF2, mediate levels of PD-L1 upregulation after IFNγ stimulation. Our results identify a novel mechanism for the regulation of immune checkpoints and present a powerful analytical framework for the analysis of multi-modal single-cell perturbation screens.