New technologies enable scientists to study molecules at a single cell level. The field of Immunology was the first to perform single cell studies and other fields are now rapidly following. Professor Frits Koning and Dr Ahmed Mahfouz of LUMC share the latest developments in this hot topic.
Frits Koning is Professor of Immunology at Leiden University Medical Centre (LUMC). He explains: “In the past twenty years, we have come to realise that the immune system is far more complex than we previously thought. There are many subsets of immune cells with specialised functions. Immunologists try to characterise these subsets in blood and tissue samples from healthy and sick people. This helps us understand how the immune system protects our bodies from pathogens and why it fails to do so in patients. In addition, it is relevant to our understanding of the development of autoimmune diseases such as rheumatoid arthritis, Crohn’s disease, or type 1 diabetes. Ultimately, this knowledge may enable us to prevent diseases and treat them better.”
Immunologists have been using flow cytometry to characterise immune subsets on a single cell basis for several decades now. Flow cytometry exploits antibodies with fluorescent dyes to sort cells based on the presence of cell surface molecules (‘markers’). Immunologists use the technique to assess the number of cells of a specific type in a sample. In addition, the composition of cell surface molecules provides insight in the function of the cells. Koning: “However, flow cytometry has a limitation: you can only incorporate a maximum of sixteen markers in one experiment. This means that we can only distinguish coarse subsets of immune cells in a sample. In 2011, a new technique entered the arena: mass cytometry. It uses metal-labelled ‘mass tags’, which can be identified by a mass spectroscopic readout. At present, we can simultaneously analyse 39 markers and this will rise to 100 in the near future. This is a gigantic leap forward. It allows us to characterise the immune system at a much greater resolution, meaning that we can identify subsets within the coarse subgroups.”
The power of mass cytometry becomes evident when Koning gives an example: “We recently initiated a large study of the immune cell composition of the intestines of patients with inflammatory intestinal diseases. When comparing intestinal biopsies of patients and controls, we discovered that the intestinal immune cell composition was far more complex than we had anticipated: we identified as many as 120 subsets of cells! We could identify subsets of immune cells that distinguished celiac disease patients from controls. And patients with Crohn’s disease in turn had another immune cell composition. It is our hope that, with a little tuning, we will be able to use this technique to reliably diagnose patients with a single mass cytometric analysis. Ultimately, we look like to be able to do this in blood because blood samples are obviously less intrusive than intestinal biopsies.”
Studies such as Koning’s intestinal disease project produce immense datasets. “We measured 32 markers in 102 biological samples, each consisting of many cells. To analyse the data, we collaborated intensively with computational biologists from TU Delft, including Marcel Reinders, Boudewijn Lelieveldt, and Thomas Höllt. They developed an algorithm to analyse complex multidimensional data. Before this tool existed, we applied so-called ‘gating’ in our analyses. This means that we would start by grouping cells in four categories based on the presence or absence of two markers (e.g., cells with only marker A, only marker B, A and B, and neither A nor B). Next, we would further subdivide these four cell populations based on additional markers. This method obviously creates bias because there are many different ways to do it. The Delft algorithm can simultaneously analyse all markers for millions of cells, resulting in an unbiased analysis and system-wide data-driven conclusions.”
Dr Ahmed Mahfouz is an assistant professor at the Computational Biology Center of LUMC and a guest researcher at the Delft Bioinformatics Lab. He explains: “The field of Immunology has a frontrunner position in single cell studies because they use cell surface markers to characterise cells. Many other fields are more interested in intracellular molecules such as RNA (i.e., gene expression). Early experiments used microarrays to measure gene expression in single cells. The advent of high-throughput next-generation sequencing technologies has changed the situation. In the last five years, we have been able to scale up our gene expression experiments to measure hundreds of thousands of cells at the single cell level at a reduced cost. Hence, fields such as neurology, oncology, and developmental biology have now also picked up single cell studies.”
Mahfouz: “My scientific interest is in how we can characterise disease effects on the brain, for example: how are different cell populations affected in Alzheimer’s disease? This can ultimately help us develop targeted treatments. We typically obtain RNA sequencing data of up to 25k genes for thousands of cells. So, we really encounter problems with the scale and dimensionality of the data. Very basic data handling steps such as visualisation are already difficult. In Delft, we have developed a unique tool that allows you to truly interact with your data. We can now easily handle mass cytometry data sets of ~40 markers measured in millions of cells. Ultimately, we want to scale these methods to 25k genes. This really is a team effort of LUMC and TU Delft.”
The popularity of the single cell field is demonstrated by the enthusiasm for the recent BioSB Hot Topics meeting that Mahfouz organised. “Around 80 people attended the meeting; they were from LUMC, AMC, VUmc, NKI, Hubrecht Institute, TU Delft, Radboud University, Erasmus MC, and UMCG. The meeting included presentations on exciting technical developments. For instance, people are trying to scale the number of cells that can be measured, especially in transcriptomics. Enabling multiple measurements from the same cell is also a hot topic. People from the Hubrecht Institute are working with genomic markers that they trace through development. And the upcoming techniques for imaging mass cytometry on histology sections allow scientists to perform single cell measurements while knowing a cell’s original location in the tissue. So, there are many exciting developments in the Netherlands. And of course, there are big players abroad as well. For instance, I am intrigued by the Human Cell Atlas Project, which aims to build a collection of maps that will describe and define the cellular basis of health and disease. Projects like this are likely to impact biology and medicine, leading to a richer understanding of life’s most fundamental principles.”