Researchers from the Leiden University Medical Center (LUMC) and the Delft University of Technology (TU Delft) have presented an interactive technique in the scientific journal, Nature Communications. The technique enables them to identify rare cell types among hundreds of other kinds. Professor Frits Koning of LUMC says, “You can find a needle in a haystack”.

In order to learn for example about how certain diseases occur, the trick is to get the precise information you want out of a huge amount of data. Since 2013, LUMC has been able to use CyTOF, a machine that can characterise millions of cells simultaneously in, for example, intestinal mucous or blood. CyTOF does this by measuring the presence per cell of approximately forty proteins on the cell wall. Using the new method developed by LUMC and TU Delft, researchers can now study this data in minute detail. 

Interesting cell types

“This kind of sample contains hundreds of different cell types”, explains Vincent van Unen, LUMC researcher at the department of Immunohematology and Blood Transfusion (IHB). “There were already methods available to analyse the CyTOF data, but these either gave a global picture of all cells, or a detailed picture of a random group of cells, say about 20 percent. But the most interesting cell types in a tissue sample, cell types that are related to being sick or healthy, are often scarce and you miss them if you only study a group of cells in detail.

Overview

The new analysis technique solves this problem. The user first gets a two-dimensional picture on the screen in which the cells from the tissue sample are grouped according to their underlying similarities. The cells are not shown individually: doing so would result in an cluttered mass of dots. Instead, they are shown as ‘landmarks’, small areas which represent cells similar to each other. “This overview leaves out the detail, but all available information is used to compute the landmarks”, says Nicola Pezzotti, doctoral candidate at TU Delft in Dr. Anna Vilanova’s Computer Graphics and Visualization group.  

Google Earth

The user can then zoom in on a group of cells of choice until individual cells with the relevant markers are visible. Pezzotti; “You can compare it to Google Earth, where you begin with the whole Earth and can then zoom right in to your own street.” This hierarchical visual methodology, Cytosplore^+HSNE, works easily, fast and well. “The landmarks represent known cell groups, such as certain T-cells and B-cells in the immune system”, explains Thomas Höllt, researcher at LUMC and TU Delft who helped develop the methodology.

 “By zooming in, it’s possible to find rare cell types which are either missing or indeed present in a particular disease such as the chronic bowel disorder, Crohn’s disease. That provides us with leads in the understanding of that disease, its diagnosis and targeted treatment”.

The article, ‘Visual analysis of mass cytometry data by hierarchical stochastic neighbor embedding reveals rare cell types’, appeared on 23 November in Nature Communications.

This research was made possible by the Technology Foundation, VANPIRE project (12721)

More information

See instructional film below.
Please read also 'Cells analysed at great speed' and 'Immune system much more complex than thought'.