scNMT-seq Allows Analysis of Connections Between Nucleosomes, Methylation and Transcription
Credit: Babraham Institute
One of the great challenges in biology involves finding ways to study different biological systems in cells simultaneously to understand how they work together to sustain life. In cell biology, studying one system is now relatively easy but, for the first time, a team in Cambridge have found a way to simultaneously study three crucial aspects of cell biology inside the same cell.
This technique, developed as a collaboration between the Babraham Institute, the European Bioinformatics Institute (EMBL-EBI) and the University of Edinburgh and reported in Nature Communications, is called single-cell nucleosome, methylation, transcription sequencing or scNMT-seq. It provides detailed information about three closely linked, fundamental aspects of biology. Most excitingly, by comparing between individual cells, the team expect to reveal differences which could play key roles in both the early stages of life and the first stages of diseases such as cancer.
Our genes are packaged into cells by wrapping them around protein structures called nucleosomes. How the genes are wrapped can affect gene activity – whether the gene is ‘on’ or ‘off’. Gene activity is also affected by epigenetic markers such as DNA methylation – chemical changes to DNA that affect how genes are read. Active genes produce molecular messages called RNA through a process called transcription. Put simply, nucleosomes and methylation can affect transcription leading to changes in cells.
scNMT-seq uniquely allows scientists to directly examine the connections between nucleosomes, methylation and transcription. Differences in these systems allow cells to specialize to form all the different parts of the body and also helps our cells respond to the changing world around us. Using scNMT-seq to spot changes could also be critical to detecting the very early stages of genetic diseases, long before they can be found by conventional medicine.
Classic cell biology approaches study averaged results collected from many cells meaning that key cell-to-cell differences are lost. Yet, scientists think this variability between cells could hold the key to bigger differences. Each life starts out as a small number of cells and develops to produce hundreds of different cell types. scNMT-seq allows researchers to study the effects of changes in single cells and could provide conclusive evidence that they can develop into major differences both in development and disease.
Co-first author, Ricard Argelaguet, a PhD student at The European Bioinformatics Institute (EMBL-EBI), said: “This technique represents an important step towards a comprehensive characterisation of single-cell biology. Combined with the right computational approaches, scNMT-seq has the potential to reveal undiscovered mechanisms of gene regulation, both in development and disease.”
Co-first author, Dr Stephen Clark, a post-doctoral researcher at the Babraham Institute, said: “Methods for studying gene expression or epigenetic regulators in individual cells are quite established. Yet, this is the first time we have been able to measure multiple features at the same time as measuring which genes are being expressed. This technique will help us understand how different epigenetic mechanisms work together to determine how cells look and behave.”
Professor Wolf Reik, Head of the Epigenetics Laboratory at the Babraham Institute and co-lead scientist on this research, said: “Transcription in individual cells can vary between cell types but also between cells of the same type. Using our new technique, we will be able to understand how these changes occur and what they could mean for the future of each cell.”
Dr Oliver Stegle, Group Leader at The European Bioinformatics Institute (EMBL-EBI) and co-lead scientist on this research, said: “Our method combines precise biological studies and complex computational approaches to integrate multiple aspects of cell biology. This will offer us unique insights into the relationships between epigenetics and gene activity and will help us to better understand the processes that convert a single cell into the many different cell types in the body.”
Researchers Can Now Decode Information from 1 Million Neurons in Real TimeNews
New method manages and stores data from millions of nerve cells – in real timeREAD MORE