In the past decade there has been significant interest in studying the expression of our genetic code down to the level of single cells, to identify the functions and activities of any cell through the course of health or disease.
The identity of a cell, and the way that identity can go awry, is critical to its role in many of the biggest health challenges we face, including cancer, neurodegeneration, or genetic and developmental disorders. Zooming in on single cells allows us to tell the difference between variants which would otherwise be lost in the average of a region. This is essential for finding new medical solutions to diseases.
Most single cell gene expression experiments make use of a technology called single cell RNA sequencing (scRNA-seq), which produces a map of exactly which genes are being copied out into short 'transcripts' inside the nucleus. However, scRNA-seq only gives us a window into the intermediate step between the genetic code and the proteins which take care of (almost) all the tasks inside our bodies. Scientists have known for a while that levels of mRNA don't exactly match levels of their corresponding protein in cells. This can be influenced by many factors, including the complex ways that cells control mRNA stability and their translation into proteins, as well as how proteins are degraded, all in a context-dependent manner.
Overcoming this challenge
Scientists at the Finsen Laboratory at Rigshospitalet, the Biotech Research and Innovation Centre (University of Copenhagen), the Technical University of Denmark (DTU), and the Helmholtz Zentrum München, have used a new approach to analyse the complex population of proteins in individual cells, during the formation of blood cells. This single-cell proteomic analysis means bypassing the mRNA intermediates and building a map of the proteins present in cells during their differentiation from stem cells into mature blood cells.
One of the study's senior authors, Bo Porse, of Finsen Laboratory at Rigshospitalet and the Biotech Research and Innovation Centre (University of Copenhagen), says:
"The process of cell differentiation is immensely complex, and we need to fully understand the nuances of what's happening inside each cell at each stage of its life to address the cases when the process goes wrong. With this study we've shown the feasibility of using this technology to accurately model the exact stages of gene expression, covering both mRNA synthesis and decay, and subsequent protein synthesis and decay throughout cell differentiation."
This study, due to be published on 21st Aug in the journal Science, represents the first use of a technology, co-developed between DTU, Rigshospitalet and University of Copenhagen, namely single-cell proteomics by Mass Spectrometry (scp-MS) in a biologically relevant organ system - as opposed to in lab-grown cell cultures. Although it's not yet possible to detect every protein present in each cell, the researchers were able to compare the mRNA data from the traditional (well, ok, only a decade-old) scRNA-seq method and this new single-cell protein analysis, and found that in more differentiated blood cells the two datasets correlated strongly (i.e. changes in mRNA levels correlated to changes in the levels of their corresponding proteins) however in the stem cells and more immature cells the datasets correlated poorly. This suggests that the turnover of mRNA transcripts, their rate of translation or the stability of the proteins expressed in cells early in their differentiation might change as cells become more differentiated.
"This study is the culmination of many years of intense technology development. Not long ago, the idea of measuring thousands of proteins in single human stem cells from the bone marrow felt like science fiction. We never imagined we'd be able to apply scp-MS to something as complex and dynamic as the human blood system this soon. But here we are, finally able to access layers of biology that are completely invisible to RNA-based methods alone. It's a testament to the power of mass spectrometry, protein-level readouts, and data-driven systems biology to transform our understanding of how cells take fate decisions", says co-senior author Erwin Schoof, Associate Professor and Head of the Cell Diversity Lab at the Department for Biotechnology and Biomedicine at the Technical University of Denmark.
Findings and impact
The researchers went on to study some of the proteins which appeared to drop in abundance during cell differentiation, despite having stable mRNA levels throughout the process. By editing the genetic code to remove (or 'knock-out') these genes, the scientists showed that this resulted in a reduction in stem cell numbers. This suggests that these proteins are essential to maintain a healthy population of stem cells within the system, to ensure that there's a sufficient supply of blood cells in the body. Simply by analysing the scRNA-seq data alone, these functionally relevant proteins would never have been identified, and their roles in this important process would have remained hidden.
"By integrating RNA and protein measurements into a dynamic model, we can capture the full life cycle of gene expression in single cells. This helps us understand not just what's written in the genetic script, but how it's performed in real time. I'm excited about how these cell-resolved protein readouts are increasingly opening entirely new windows into cell biology" says Fabian Theis, Director at the Computational Health Center at Helmholtz Munich, and Professor for Mathematical Modeling of Biological Systems at the Technical University of Munich.
This work marks a turning point for single-cell biology: the ability to directly measure proteins at single-cell resolution in primary human tissue. It opens the door to discovering hidden layers of regulation in development, disease, and regeneration, layers that RNA alone could never reveal. As telescopes transform our understanding of the cosmos, single-cell proteomics is now doing the same for the inner workings of life.
