Dissociation of microdissected mouse brain tissue for artifact free single-cell RNA sequencing.
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ABSTRACT:
SUBMITTER: Liu L
PROVIDER: S-EPMC8196224 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundRecent technological advances opened the opportunity to simultaneously study gene expression for thousands of individual cells on a genome-wide scale. The experimental accessibility of such single-cell RNA sequencing (scRNAseq) approaches allowed gaining insights into the cell type composition of heterogeneous tissue samples of animal model systems and emerging models alike. A major prerequisite for a successful application of the method is the dissociation of complex tissues into individual cells, which often requires large amounts of input material and harsh mechanical, chemical and temperature conditions. However, the availability of tissue material may be limited for small animals, specific organs, certain developmental stages or if samples need to be acquired from collected specimens. Therefore, we evaluated different dissociation protocols to obtain single cells from small tissue samples of Drosophila melanogaster eye-antennal imaginal discs.ResultsWe show that a combination of mechanical and chemical dissociation resulted in sufficient high-quality cells. As an alternative, we tested protocols for the isolation of single nuclei, which turned out to be highly efficient for fresh and frozen tissue samples. Eventually, we performed scRNAseq and single-nuclei RNA sequencing (snRNAseq) to show that the best protocols for both methods successfully identified relevant cell types. At the same time, snRNAseq resulted in less artificial gene expression that is caused by rather harsh dissociation conditions needed to obtain single cells for scRNAseq. A direct comparison of scRNAseq and snRNAseq data revealed that both datasets share biologically relevant genes among the most variable genes, and we showed differences in the relative contribution of the two approaches to identified cell types.ConclusionWe present two dissociation protocols that allow isolating single cells and single nuclei, respectively, from low input material. Both protocols resulted in extraction of high-quality RNA for subsequent scRNAseq or snRNAseq applications. If tissue availability is limited, we recommend the snRNAseq procedure of fresh or frozen tissue samples as it is perfectly suited to obtain thorough insights into cellular diversity of complex tissue.
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Project description:Single-cell RNA sequencing (scRNASeq) has advanced our understanding of lung biology, but its utility is limited by the need for fresh samples, loss of cell types by death or inadequate dissociation, and transcriptional stress responses induced during tissue digestion. Single-nucleus RNA sequencing (snRNASeq) has addressed these deficiencies in other tissues, but no protocol exists for lung tissue. We present a snRNASeq protocol and compare its results with those of scRNASeq. Two nuclear suspensions were prepared in lysis buffer on ice while one cell suspension was generated using enzymatic and mechanical dissociation. Cells and nuclei were processed using the 10× Genomics platform, and sequencing data were analyzed by Seurat. A total of 16,110 single-nucleus and 11,934 single-cell transcriptomes were generated. Gene detection rates were equivalent in snRNASeq and scRNASeq (∼1,700 genes and 3,000 unique molecular identifiers per cell) when mapping intronic and exonic reads. In the combined data, 89% of epithelial cells were identified by snRNASeq versus 22.2% of immune cells. snRNASeq transcriptomes are enriched for transcription factors and signaling proteins, with reduction in mitochondrial and stress-response genes. Both techniques improved mesenchymal cell detection over previous studies. Homeostatic signaling relationships among alveolar cell types were defined by receptor-ligand mapping using snRNASeq data, revealing interplay among epithelial, mesenchymal, and capillary endothelial cells. snRNASeq can be applied to archival murine lung samples, improves dissociation bias, eliminates artifactual gene expression, and provides similar gene detection compared with scRNASeq.
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Project description:We present an optimized dissociation protocol for preparing high-quality skin cell suspensions for in-depth single-cell RNA-sequencing (scRNA-seq) analysis of fresh and cultured human skin. Our protocol enabled the isolation of a consistently high number of highly viable skin cells from small freshly dissociated punch skin biopsies, which we use for scRNA-seq studies. We recapitulated not only the main cell populations of existing single-cell skin atlases, but also identified rare cell populations, such as mast cells. Furthermore, we effectively isolated highly viable single cells from ex vivo cultured skin biopsy fragments and generated a global single-cell map of the explanted human skin. The quality metrics of the generated scRNA-seq datasets were comparable between freshly dissociated and cultured skin. Overall, by enabling efficient cell isolation and comprehensive cell mapping, our skin dissociation-scRNA-seq workflow can greatly facilitate scRNA-seq discoveries across diverse human skin pathologies and ex vivo skin explant experimentations.
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Project description:In females with X-linked genetic disorders, wild-type and mutant cells coexist within brain tissue because of X-chromosome inactivation, posing challenges for interpreting the effects of X-linked mutant alleles on gene expression. We present a single-nucleus RNA sequencing approach that resolves mosaicism by using single-nucleotide polymorphisms in genes expressed in cis with the X-linked mutation to determine which nuclei express the mutant allele even when the mutant gene is not detected. This approach enables gene expression comparisons between mutant and wild-type cells within the same individual, eliminating variability introduced by comparisons to controls with different genetic backgrounds. We apply this approach to mosaic female mouse models and humans with Rett syndrome, an X-linked neurodevelopmental disorder caused by mutations in the gene encoding the methyl-DNA-binding protein MECP2, and observe that cell-type-specific DNA methylation predicts the degree of gene upregulation in MECP2-mutant neurons. This approach can be broadly applied to study gene expression in mosaic X-linked disorders.
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Project description:Cerebral blood vessels supply oxygen and nutrients, remove metabolic waste, and play a critical role in maintaining brain homeostasis. Cerebrovasculature is composed of heterogeneous populations of brain vascular cells (BVCs). A major challenge in effective cerebrovascular transcriptional profiling is high-quality BVC procurement, permitting high sequencing depth. Here, we establish cell isolation procedures for glio-vascular cell-enriched single-cell RNA sequencing enabling unbiased characterization of BVC transcriptional heterogeneity. Our approach can be used to address vascular-specific contribution to brain diseases. For complete details on the use and execution of this protocol, please refer to Yamazaki et al. (2021).
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Project description:Midbrain dopamine (mDA) neurons constitute a heterogenous group of cells that have been intensely studied, not least because their degeneration causes major symptoms in Parkinson's disease. Understanding the diversity of mDA neurons - previously well characterized anatomically - requires a systematic molecular classification at the genome-wide gene expression level. Here, we use single cell RNA sequencing of isolated mouse neurons expressing the transcription factor Pitx3, a marker for mDA neurons. Analyses include cells isolated during development up until adulthood and the results are validated by histological characterization of newly identified markers. This identifies seven neuron subgroups divided in two major branches of developing Pitx3-expressing neurons. Five of them express dopaminergic markers, while two express glutamatergic and GABAergic markers, respectively. Analysis also indicate evolutionary conservation of diversity in humans. This comprehensive molecular characterization will provide a valuable resource for elucidating mDA neuron subgroup development and function in the mammalian brain.
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Project description:In recent years, the number of obesity has increased rapidly around the world, and it has become a major public health problem endangering global health [1]. Obesity is caused by excessive calorie intake over a long period of time, and high-fat diet (HFD) is one of the important predisposing factors [2], [3], [4]. Adipose tissue (AT) is an important immune and endocrine organ in the body, and plays an important role in the body [5]. Obesity leads to AT dysfunction, AT dilation and cell hypertrophy. Dysfunctional fat cells are the main source of pro-inflammatory cytokines, which aggravate low-grade systemic inflammation and further promote the development of obesity-related diseases [6], [7], [8]. However, whether AT releases pro-inflammatory cytokines in the early stages of obesity development remains unknown. The AT microenvironment is composed of a variety of cells, including fat cells, immune cells, fibroblasts, and endothelial cells. The immune microenvironment (TIME) and its metabolic imbalance can lead to the secretion or regulation of related hormones, which causes inflammation AT [9]. TIME is very important for maintaining AT homeostasis, which is crucial for the occurrence of obesity [10,11]. This data use single-cell RNA sequencing (sNuc-Seq) to analyze the characteristics of TIME changes in the mouse epididymal adipose tissue during the development of obesity, and the changes of cell types and genes in the tissue.
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Project description:Tissue dissociation, a crucial step in single-cell sample preparation, can alter the transcriptional state of a sample through the intrinsic cellular stress response. Here we demonstrate a general approach for measuring transcriptional response during sample preparation. In our method, transcripts made during dissociation are labeled for later identification upon sequencing. We found general as well as cell-type-specific dissociation response programs in zebrafish larvae, and we observed sample-to-sample variation in the dissociation response of mouse cardiomyocytes despite well-controlled experimental conditions. Finally, we showed that dissociation of the mouse hippocampus can lead to the artificial activation of microglia. In summary, our approach facilitates experimental optimization of dissociation procedures as well as computational removal of transcriptional perturbation response.
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Project description:Vascular diseases are major causes of death, yet our understanding of the cellular constituents of blood vessels, including how differences in their gene expression profiles create diversity in vascular structure and function, is limited. In this paper, we describe a single-cell RNA sequencing (scRNA-seq) dataset that defines vascular and vessel-associated cell types and subtypes in mouse brain and lung. The dataset contains 3,436 single cell transcriptomes from mouse brain, which formed 15 distinct clusters corresponding to cell (sub)types, and another 1,504 single cell transcriptomes from mouse lung, which formed 17 cell clusters. In order to allow user-friendly access to our data, we constructed a searchable database (http://betsholtzlab.org/VascularSingleCells/database.html). Our dataset constitutes a comprehensive molecular atlas of vascular and vessel-associated cell types in the mouse brain and lung, and as such provides a strong foundation for future studies of vascular development and diseases.
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Project description:Spermatogenesis is an efficient and complex system of continuous cell differentiation. Previous studies investigating the transcriptomes of different cell populations in the testis relied either on sorting cells, cell depletion, or juvenile animals where not all stages of spermatogenesis have been completed. We present single-cell RNA sequencing (scRNA-Seq) data of 2,500 cells from the testes of two 8-week-old C57Bl/6J mice. Our dataset includes all spermatogenic stages from preleptotene to condensing spermatids as well as individual spermatogonia, Sertoli and Leydig cells. The data capture the full continuity of the meiotic and postmeiotic stages of spermatogenesis, and is thus ideally suited for marker discovery, network inference and similar analyses for which temporal ordering of differentiation processes can be exploited. Furthermore, it can serve as a reference for future studies involving single-cell RNA-Seq in mice where spermatogenesis is perturbed.
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