Dataset Information

Single-cell transcriptional analysis reveals ILC-like cells in zebrafish.

ABSTRACT: Innate lymphoid cells (ILCs) are important mediators of the immune response and homeostasis in barrier tissues of mammals. However, the existence and function of ILCs in other vertebrates are poorly understood. Here, we use single-cell RNA sequencing to generate a comprehensive atlas of zebrafish lymphocytes during tissue homeostasis and after immune challenge. We profiled 14,080 individual cells from the gut of wild-type zebrafish, as well as of rag1-deficient zebrafish that lack T and B cells, and discovered populations of ILC-like cells. We uncovered a rorc-positive subset of ILCs that could express cytokines associated with type 1, 2, and 3 responses upon immune challenge. Specifically, these ILC-like cells expressed il22 and tnfa after exposure to inactivated bacteria or il13 after exposure to helminth extract. Cytokine-producing ILC-like cells express a specific repertoire of novel immune-type receptors, likely involved in recognition of environmental cues. We identified additional novel markers of zebrafish ILCs and generated a cloud repository for their in-depth exploration.

SUBMITTER: Hernandez PP

PROVIDER: S-EPMC6258902 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Single-cell transcriptional analysis reveals ILC-like cells in zebrafish.

Hernández Pedro P PP Strzelecka Paulina M PM Athanasiadis Emmanouil I EI Hall Dominic D Robalo Ana F AF Collins Catherine M CM Boudinot Pierre P Levraud Jean-Pierre JP Cvejic Ana A

Science immunology 20181101 29

Innate lymphoid cells (ILCs) are important mediators of the immune response and homeostasis in barrier tissues of mammals. However, the existence and function of ILCs in other vertebrates are poorly understood. Here, we use single-cell RNA sequencing to generate a comprehensive atlas of zebrafish lymphocytes during tissue homeostasis and after immune challenge. We profiled 14,080 individual cells from the gut of wild-type zebrafish, as well as of <i>rag1</i>-deficient zebrafish that lack T and B ...[more]

PMID: 30446505

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Project description:Single-cell analysis has the potential to provide us with a host of new knowledge about biological systems, but it comes with the challenge of correctly interpreting the biological information. While emerging techniques have made it possible to measure inter-cellular variability at the transcriptome level, no consensus yet exists on the most appropriate method of data analysis of such single cell data. Methods for analysis of transcriptional data at the population level are well established but are not well suited to single cell analysis due to their dependence on population averages. In order to address this question, we have systematically tested combinations of methods for primary data analysis on single cell transcription data generated from two types of primary immune cells, neutrophils and T lymphocytes. Cells were obtained from healthy individuals, and single cell transcript expression data was obtained by a combination of single cell sorting and nanoscale quantitative real time PCR (qRT-PCR) for markers of cell type, intracellular signaling, and immune functionality. Gene expression analysis was focused on hierarchical clustering to determine the existence of cellular subgroups within the populations. Nine combinations of criteria for data exclusion and normalization were tested and evaluated. Bimodality in gene expression indicated the presence of cellular subgroups which were also revealed by data clustering. We observed evidence for two clearly defined cellular subtypes in the neutrophil populations and at least two in the T lymphocyte populations. When normalizing the data by different methods, we observed varying outcomes with corresponding interpretations of the biological characteristics of the cell populations. Normalization of the data by linear standardization taking into account technical effects such as plate effects, resulted in interpretations that most closely matched biological expectations. Single cell transcription profiling provides evidence of cellular subclasses in neutrophils and leukocytes that may be independent of traditional classifications based on cell surface markers. The choice of primary data analysis method had a substantial effect on the interpretation of the data. Adjustment for technical effects is critical to prevent misinterpretation of single cell transcript data.

Dataset Information

Single-cell transcriptional analysis reveals ILC-like cells in zebrafish.

Publications

Single-cell transcriptional analysis reveals ILC-like cells in zebrafish.

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