For a good understanding of the development and function of an organ, it is essential to understand all characteristics of its cell types. To distinguish between different cell types, the gene expression levels of cells are measured. With the emergence of advanced single cell mRNA sequencing thousands of gene expression levels in an individual cell can be measured. This way a fingerprint of cell can be made, called a transcriptome, which reveals the identity of a cell.
However, the expression of a gene in a given cell type can be highly variable and the experimental procedure to sequence the transcriptome of a cell introduces additional variability. This makes it very challenging to identify cell types, in particular rare cell types that occur at very low frequency within an organ. Identifying rare cell types is crucial to acquire a better understanding of normal or diseased tissue biology, because they can carry out important functions in an organ. Stem cells, for example, which give rise to all other cell types of an organ are typically rare and characterizing these cells could be the basis for regenerative medicine.
The scientists of the Hubrecht Institute, led by Alexander van Oudenaarden, Professor of Quantitative biology of gene regulation and director if the Hubrecht Institute, developed an algorithm for rare cell type identification in complex populations of single cells. This algorithm, called RaceID, was used to analyse cultured mini-intestines (organoids). In these organoids the scientists discovered a new subpopulation of hormone producing intestinal cells. These so called enteroendocrine cells are important for gut homeostasis and are therefore crucial for the digestive function of the intestine.
a, Intestinal crypts were isolated from mice and grown into intestinal organoids as described previously. Organoids were dissociated and single cells, collected by fluorescence-activated cell sorting (FACS), were sequenced by a modified version of the CEL-seq method. b, Heat map indicating similarities between 238 single cells measured by Euclidean distances of the transcriptome correlation matrix (unitless; see Methods). k-means clustering identified six major groups of cells colour coded along the axes. c, t-SNE map representation of transcriptome similarities between individual cells. Clusters identified in b were highlighted with different colours and corresponding intestinal cell types identified on the basis of known marker genes are indicated.
In the future RaceID can be used to discover rare cell types and their marker genes. Knowing the full repertoire of cell types in various systems such as developing embryos or adult organs will lead to a better understanding of these systems and can provide basis for disease therapies.
This study is closely related to Utrecht University’s strategic research theme Life Sciences, under the sub-theme of Regenerative Medicine & Stem Cells, which focuses on repairing and replacing tissue.
Source – Utrecht University