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Single-Cell, "Multi-Omics" Analysis Uncovers a New Stage in Immune Cell Formation

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Over recent years, advances in analytical technologies have enabled scientists to gain insight into cell biology at a whole new level of detail: the single-cell level. This approach recognizes that cells – even those in close proximity as part of the same tissue – are heterogenous in nature.

The cells of our immune system are particularly interesting. Despite being derived from a blood stem cell, each type of immune cell carries out a specific, individual function. How do these different types of immune cells develop?

A research team – led by Dr Shalin Naik – from The Walter and Eliza Hall Institute has adopted a single-cell, multi-omics approach to explore this question, focusing particularly on T and B lymphocyte formation.

Their results, recently published in Nature Immunology, outline their discovery of a new stage in lymphocyte development, information which the researchers say could "enrich future studies of the immune system".

Technology Networks spoke with Naik to learn more about the study findings and why a single-cell, multi-omics approach to studying the immune system helps us to capture "the full picture".

Molly Campbell (MC): For readers unfamiliar with the concept, can you tell us about the principle of a multi-omics single cell analysis approach?

Shalin Naik (SN):
Cells are the basic building blocks of all of our tissues. Analyzing each cell in an organ is akin to understanding individual player statistics in a football match rather than just the teams’ scores. Scientists measure many different aspects of cell biology – their proteins, their DNA, the genes that are switched on and off, etc. The more features of a cell that we can measure, the better a picture we can resolve. In this way we can get closer to the true nature of each cell, what it does and how that is relevant for our biology. “Multi-omics” is an approach that can get as much information per cell as possible to get the fullest picture possible.

MC: What was the rationale behind this study, particularly the decision to conduct a single-cell analysis in the context of immunology?

Our laboratory studies the immune system using new cutting-edge single cell technologies. We had previously found that stem and progenitor cells for the immune system were very diverse in which cell types they could make. However, we believed there was a lot of "hidden" types of stem and progenitor cells that no-one had previously had the means to unmask. If one can understand the diversity of immune cell types, and how they are born, then we can use that information for generating immune cells for cancer and immunity, but also to turn down cancers of the immune cell lineage called leukemias.

MC: Can you discuss the methods adopted to achieve the multi-omics analysis?

The method we developed is called single cell RNA-sequencing (scRNA-seq), used to understand the gene expression in individual cells. This was previously impossible because we were used to doing RNA-seq on millions of cells with billions of molecules to get a sufficient signal. To achieve a signal for one cell with only 20,000 molecules per cell, for large numbers of cells, was a huge challenge. However, we pioneered an approach to first analyze the proteins of cells (the proteome) using flow cytometry and then the RNA molecules of those same cells (transcriptome). Miniaturization of this technique allowed us to capture both of these "omes" (i.e. multi-omics) for stem and progenitor cells of the immune cell lineages.

Karen Steward (KS): What alerted you to the existence of this unexpected progenitor cell type?

We previously used a stem cell barcoding and tracking technique to discover that stem and progenitor cells were highly heterogeneous in which immune cells they made, but we didn’t know how they achieved this. We needed to unravel the cell-by-cell differences in that population to get some clues. That set us the task of developing the multi-omics scRNA-seq technique to get to the heart of that answer… and we found it!

MC: You have established the Single Cell Open Research Endeavour (SCORE). Please can you tell us more about this?

Having seen the power of scRNA-seq first-hand, we knew that this was a technology that was going to be fast moving and useful to many, many researchers. Rather than every lab reinventing the wheel, we believed that creating an integrated team that can cover the biology, molecular biology and bioinformatics analysis, could be agile to adopt new developments in the field so that researchers could focus on what they do best… the biological and clinical questions!

MC: What challenges are associated with single-cell analysis, and how did you overcome them in this research?

People have written entire PhD theses on just one small aspect of the many, many challenges that are faced with scRNA-seq analyses. There are so many ways you can look at the data, and as a result there has been an explosion in the number and types of analyses to find them. The challenges are first and foremost that, unlike RNA-seq data on millions of cells, data from single cells is very sparse – meaning there are lots of 0’s in gene count – it's kind of like looking at a blurry picture rather than a high-resolution one. However, there are many ways to still extract some information from this data by capturing enough cells, and then using some intelligent methods to separate the signal from the noise, as they say.

KS: How might this new information on the development of T and B cells be useful for targeting disfunctions of the immune system?

By understanding where T and B cells come from normally, like we have done in this study, we hope to use this information to think about how we might be able to boost numbers of these cell types; either in vaccination, to boost an ageing immune system, or to engineer cancer-fighting immunotherapies. Some leukemias are “lymphoid” in nature, meaning they have the same origin as progenitors that make T and B cells. Having discovered the earliest step of lymphoid development, we think this may represent the source of such cancers. By understanding the mechanisms of our newly discovered population, we might find clues as to the origins of such leukemias.

Dr Shalin Naik was speaking to Molly Campbell and Dr Karen Steward, Science Writers, Technology Networks.