New subgroups of ILC immune cells discovered through single-cell RNA sequencing
Reporter: Stephen J Williams, PhD
UPDATED on 8/8/2020
A Hybrid Deep Clustering Approach for Robust Cell Type Profiling Using Single-cell RNA-seq Data
+Author Affiliations
- ↵* Corresponding author; email: korkin@korkinlab.org
Abstract
Single-cell RNA sequencing (scRNA-seq) is a recent technology that enables fine-grained discovery of cellular subtypes and specific cell states. It routinely uses machine learning methods, such as feature learning, clustering, and classification, to assist in uncovering novel information from scRNA-seq data. However, current methods are not well suited to deal with the substantial amounts of noise that is created by the experiments or the variation that occurs due to differences in the cells of the same type. Here, we develop a new hybrid approach, Deep Unsupervised Single-cell Clustering (DUSC), that integrates feature generation based on a deep learning architecture with a model-based clustering algorithm, to find a compact and informative representation of the single-cell transcriptomic data generating robust clusters. We also include a technique to estimate an efficient number of latent features in the deep learning model. Our method outperforms both classical and state-of-the-art feature learning and clustering methods, approaching the accuracy of supervised learning. We applied DUSC to single-cell transcriptomics dataset obtained from a triple-negative breast cancer tumor to identify potential cancer subclones accentuated by copy-number variation and investigate the role of clonal heterogeneity. Our method is freely available to the community and will hopefully facilitate our understanding of the cellular atlas of living organisms as well as provide the means to improve patient diagnostics and treatment.
Keywords
- Received January 3, 2020.
- Accepted May 22, 2020.
- Published by Cold Spring Harbor Laboratory Press for the RNA Society
This article is distributed exclusively by the RNA Society for the first 12 months after the full-issue publication date (see http://rnajournal.cshlp.org/site/misc/terms.xhtml). After 12 months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
New subgroups of ILC immune cells discovered through single-cell RNA sequencing
SOURCE
Jenny Mjösberg and Rickard Sandberg are principal investigators at Karolinska Institutet’s Department of Medicine, Huddinge and Department of Cell and Molecular Biology, respectively. Credit: Stefan Zimmerman.
A relatively newly discovered group of immune cells known as ILCs have been examined in detail in a new study published in the journal Nature Immunology. By analysing the gene expression in individual tonsil cells, scientists at Karolinska Institutet have found three previously unknown subgroups of ILCs, and revealed more about how these cells function in the human body.
Innate lymphoid cells (ILCs) are a group of immune cells that have only relatively recently been discovered in humans. Most of current knowledge about ILCs stems from animal studies of e.g. inflammation or infection in the gastrointestinal tract. There is therefore an urgent need to learn more about these cells in humans.
Previous studies have shown that ILCs are important for maintaining the barrier function of the mucosa, which serves as a first line of defence against microorganisms in the lungs, intestines and elsewhere. However, while there is growing evidence to suggest that ILCs are involved in diseases such as inflammatory bowel disease, asthma and intestinal cancer, basic research still needs to be done to ascertain exactly what part they play.
Two research groups, led by Rickard Sandberg and Jenny Mjösberg, collaborated on a study of ILCs from human tonsils. To date, three main groups of human ILCs are characterized. In this present study, the teams used a novel approach that enabled them to sort individual tonsil cells and measure their expression across thousands of genes. This way, the researchers managed to categorise hundreds of cells, one by one, to define the types of ILCs found in the human tonsils.
Unique gene expression profiles
Rickard Sandberg, credit: Stefan Zimmerman,
“We used cluster analyses to demonstrate that ILCs congregate into ILC1, ILC2, ILC3 and NK cells, based on their unique gene expression profiles,” says Professor Sandberg at Karolinska Institutet’sDepartment of Cell and Molecular Biology, and the Stockholm branch of Ludwig Cancer Research. “Our analyses also discovered the expression of numerous genes of previously unknown function in ILCs, highlighting that these cells are likely doing more than what we previously knew.”
By analysing the gene expression profiles (or transcriptome) of individual cells, the researchers found that one of the formerly known main groups could be subdivided.
Jenny Mjösberg, credit: Stefan Zimmerman.
“We’ve identified three new subgroups of ILC3s that evince different gene expression patterns and that differ in how they react to signalling molecules and in their ability to secrete proteins,” says Dr Mjösberg at Karolinska Institutet’s Department of Medicine in Huddinge, South Stockholm. “All in all, our study has taught us a lot about this relatively uncharacterised family of cells and our data will serve as an important resource for other researchers.”
The study was financed by grants from a number of bodies, including the Swedish Research Council, the Swedish Cancer Society, the EU Framework Programme for Research and Innovation, the Swedish Society for Medical Research, the Swedish Foundation for Strategic Research and Karolinska Institutet.
Publication
The heterogeneity of human CD127+ innate lymphoid cells revealed by single-cell RNA sequencing
Åsa K. Björklund, Marianne Forkel, Simone Picelli, Viktoria Konya, Jakob Theorell, Danielle Friberg, Rickard Sandberg, Jenny Mjösberg
Nature Immunology, online 15 February 2016, doi:10.1038/ni.3368
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