Cell type-specific isolation and transcriptomic profiling informs glial pathology in human temporal lobe epilepsy

Tomé-García, Jessica; Nudelman, German; Mussa, Zarmeen; Caballero, Elodia; Jiang, Yan; Kg, Beaumont; Wang, Y; Rg, Sebra; Akbarian, Schahram; Pinto, Dalila; Zaslavsky, Elena; Nm, Tsankova

doi:10.1101/2020.12.11.421370

Cited by 4 publications

(2 citation statements)

References 86 publications

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“…These included adipose ( 51 , 69 ) and atherosclerotic ( 70 , 71 ) tissue, as reported, as well as healthy tissues [placenta ( 72 ), testis ( 73 ), kidney ( 74 ), pancreas ( 75 ), prostate ( 38 ), decidua ( 72 ), liver ( 76 ), ovary ( 76 , 77 ), skeletal muscle ( 78 ), and intestine ( 26 )] and other disease contexts [acne ( 79 ), leprosy ( 79 ) and atopic dermatitis ( 80 , 81 ) (skin), and Crohn’s disease (ileum) ( 82 )]. Microglia from the central nervous system of epileptic patients ( 83 ) were also classified as LAM-like cells, indicating that microglia that express LAM signature genes extend beyond Alzheimer’s disease ( 66 – 68 ). LAM signature genes were enriched for genome-wide association study (GWAS) genes associated with levels of high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol, triglycerides, type 2 diabetes, and the tau to Aβ1-42 ratio in cerebrospinal fluid (fig.…”

Section: Resultsmentioning

confidence: 99%

Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function

Eraslan

Drokhlyansky

Anand

et al. 2022

Science

236

224

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Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, generating a cross-tissue atlas of 209,126 nuclei profiles, which we integrated across tissues, donors, and laboratory methods with a conditional variational autoencoder. Using the resulting cross-tissue atlas, we highlight shared and tissue-specific features of tissue-resident cell populations; identify cell types that might contribute to neuromuscular, metabolic, and immune components of monogenic diseases and the biological processes involved in their pathology; and determine cell types and gene modules that might underlie disease mechanisms for complex traits analyzed by genome-wide association studies.

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Section: Resultsmentioning

confidence: 99%

Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function

Eraslan

Drokhlyansky

Anand

et al. 2022

Science

236

224

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“…Numerous scRNA‐Seq studies have been performed on epilepsy. For example, Tome‐Garcia et al 13 . used scRMA‐Seq, cell‐type‐specific isolation, and transcriptomic profiling to investigate glial pathology in human traumatic temporal lobe epilepsy.…”

Section: Introductionmentioning

confidence: 99%

Molecular mechanism analyses of post‐traumatic epilepsy and hereditary epilepsy based on 10× single‐cell transcriptome sequencing technology

Wen,

Tan,

Huang

et al. 2024

CNS Neurosci Ther

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BackgroundSingle‐cell RNA sequencing analysis has been usually conducted on post‐traumatic epilepsy (PET) and hereditary epilepsy (HE) patients; however, the transcriptome of patients with traumatic temporal lobe epilepsy has rarely been studied.Materials and MethodsHippocampus tissues isolated from one patient with PTE and one patient with HE were used in the present study. Single cell isolates were prepared and captured using a 10× Genomics Chromium Single‐Cell 3′ kit (V3) according to the manufacturer's instructions. The libraries were sequenced on an Illumina NovaSeq 6000 sequencing system. Raw data were processed, and the cells were filtered and classified using the Seurat R package. Uniform Manifold Approximation and Projection was used for visualization. Differentially expressed genes (DEGs) were identified based on a p‐value ≤0.01 and log fold change (FC) ≥0.25. Gene Ontology (GO, http://geneontology.org/) and KEGG (Kyoto Encyclopedia of Genes and Genomes, www.genome.jp/kegg) analyses were performed on the DEGs for enrichment analysis.ResultsThe reads obtained from the 10× genomic platform for PTE and HE were 39.56 M and 30.08 M, respectively. The Q30 score of the RNA reads was >91.6%. After filtering, 7479 PTE cells and 9357 HE cells remained for further study. More than 96.4% of the reads were mapped to GRCh38/GRCm38. The cells were differentially distributed in two groups, with higher numbers of oligodendrocytes (6522 vs. 2532) and astrocytes (133 vs. 52), and lower numbers of microglial cells (2242 vs. 3811), and neurons (3 vs. 203) present in the HE group than in the PTE group. The DEGs in four cell clusters were identified, with 25 being in oligodendrocytes (13 upregulated and 12 downregulated), 87 in microglia cells (42 upregulated and 45 downregulated), 222 in astrocytes (115 upregulated and 107 downregulated), and 393 in neurons (305 upregulated and 88 downregulated). The genes MTND1P23 (downregulated), XIST (downregulated), and RPS4Y1 (upregulated) were commonly expressed in all four cell clusters. The DEGs in microglial cells and astrocytes were enriched in the IL‐17 signaling pathway.ConclusionOur study explored differences in cells found in a patient with PE compared to a patient with HE, and the transcriptome in the different cells was analyzed for the first time. Studying inflammatory and immune functions might be the best approach for investigating traumatic temporal lobe epilepsy in neurons.

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The molecular landscape of neurological disorders: insights from single-cell RNA sequencing in neurology and neurosurgery

Awuah,

Ahluwalia,

Ghosh

et al. 2023

Eur J Med Res

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Single-cell ribonucleic acid sequencing (scRNA-seq) has emerged as a transformative technology in neurological and neurosurgical research, revolutionising our comprehension of complex neurological disorders. In brain tumours, scRNA-seq has provided valuable insights into cancer heterogeneity, the tumour microenvironment, treatment resistance, and invasion patterns. It has also elucidated the brain tri-lineage cancer hierarchy and addressed limitations of current models. Neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis have been molecularly subtyped, dysregulated pathways have been identified, and potential therapeutic targets have been revealed using scRNA-seq. In epilepsy, scRNA-seq has explored the cellular and molecular heterogeneity underlying the condition, uncovering unique glial subpopulations and dysregulation of the immune system. ScRNA-seq has characterised distinct cellular constituents and responses to spinal cord injury in spinal cord diseases, as well as provided molecular signatures of various cell types and identified interactions involved in vascular remodelling. Furthermore, scRNA-seq has shed light on the molecular complexities of cerebrovascular diseases, such as stroke, providing insights into specific genes, cell-specific expression patterns, and potential therapeutic interventions. This review highlights the potential of scRNA-seq in guiding precision medicine approaches, identifying clinical biomarkers, and facilitating therapeutic discovery. However, challenges related to data analysis, standardisation, sample acquisition, scalability, and cost-effectiveness need to be addressed. Despite these challenges, scRNA-seq has the potential to transform clinical practice in neurological and neurosurgical research by providing personalised insights and improving patient outcomes.

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Cell type-specific isolation and transcriptomic profiling informs glial pathology in human temporal lobe epilepsy

Cited by 4 publications

References 86 publications

Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function

Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function

Molecular mechanism analyses of post‐traumatic epilepsy and hereditary epilepsy based on 10× single‐cell transcriptome sequencing technology

The molecular landscape of neurological disorders: insights from single-cell RNA sequencing in neurology and neurosurgery

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