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Transcriptional landscape of epithelial and immune cell populations revealed through FACS-seq of healthy human skin

ABSTRACT: Transcriptional landscape of epithelial and immune cell populations revealed through FACS-seq of healthy human skin

PROVIDER: PRJNA476386 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR10416984_1.fastq.gz	Fastqsanger.gz
	SRR10416984_2.fastq.gz	Fastqsanger.gz
	SRR10416985_1.fastq.gz	Fastqsanger.gz
	SRR10416985_2.fastq.gz	Fastqsanger.gz
	SRR10416986_1.fastq.gz	Fastqsanger.gz

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Transcriptional landscape of epithelial and immune cell populations revealed through FACS-seq of healthy human skin

Project description:Human skin consists of multiple cell types, including epithelial, immune, and stromal cells. Transcriptomic analyses have previously been performed from bulk skin samples or from epithelial and immune cells expanded in cell culture. However, transcriptomic analysis of bulk skin tends to drown out expression signals from relatively rare cells while cell culture methods may significantly alter cellular phenotypes and gene expression profiles. To identify distinct transcriptomic profiles of multiple cell populations without substantially altering cell phenotypes, we employed a fluorescence activated cell sorting method to isolate keratinocytes, dendritic cells, CD4+ T effector cells, CD4+ Treg cells, and CD8+ T effector cells from healthy skin samples, followed by RNA-seq of each cell population. Principal components analysis revealed distinct clustering of cell types across samples, while differential expression and coexpression network analyses revealed transcriptional profiles of individual cell populations distinct from bulk skin, most strikingly in the least abundant CD8+ T effector population. Our work provides a high resolution view of cutaneous cellular gene expression and suggests that transcriptomic profiling of bulk skin may inadequately capture the contribution of less abundant cell types.

2018-06-16 | GSE115898 | GEO

Transcriptional landscape of epithelial and immune cell populations revealed through FACS-seq of healthy human skin.

Project description:Human skin consists of multiple cell types, including epithelial, immune, and stromal cells. Transcriptomic analyses have previously been performed from bulk skin samples or from epithelial and immune cells expanded in cell culture. However, transcriptomic analysis of bulk skin tends to drown out expression signals from relatively rare cells while cell culture methods may significantly alter cellular phenotypes and gene expression profiles. To identify distinct transcriptomic profiles of multiple cell populations without substantially altering cell phenotypes, we employed a fluorescence activated cell sorting method to isolate keratinocytes, dendritic cells, CD4+ T effector cells, and CD8+ T effector cells from healthy skin samples, followed by RNA-seq of each cell population. Principal components analysis revealed distinct clustering of cell types across samples, while differential expression and coexpression network analyses revealed transcriptional profiles of individual cell populations distinct from bulk skin, most strikingly in the least abundant CD8+ T effector population. Our work provides a high resolution view of cutaneous cellular gene expression and suggests that transcriptomic profiling of bulk skin may inadequately capture the contribution of less abundant cell types.

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Author Correction: Transcriptional landscape of epithelial and immune cell populations revealed through FACS-seq of healthy human skin.

Project description: Not available

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Project description:The metabolic status of individual cells in microbial cultures can differ being relevant for biotechnology, environmental and medical microbiology. However, it is hardly understood in molecular detail due to limitations of current analytical tools. Here, we demonstrate that FACS in combination with proteomics can be used to sort and analyze cell populations based on their metabolic state. A previously established GFP reporter system was used to detect and sort single Corynebacterium glutamicum cells based on the concentration of branched chain amino acids (BCAA) using FACS. A proteomics workflow optimized for small cell numbers was used to quantitatively compare proteomes of a ?aceE mutant, lacking functional pyruvate dehydrogenase (PD), and the wild type. About 800 proteins could be quantified from 1,000,000 cells. In the ?aceE mutant BCAA production was coordinated with upregulation of the glyoxylate cycle and TCA cycle to counter the lack of acetyl CoA resulting from the deletion of aceE.

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