22/02/2018
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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 .
This technique, developed as a collaboration between the , the (EMBL-EBI) and the and reported today (22nd February 2018) 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 . How the genes are wrapped can affect – whether the gene is ‘on’ or ‘off’. Gene activity is also affected by epigenetic markers such as – 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 specialise 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 鶹Ƶ (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 鶹Ƶ, 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.”
, Head of the Epigenetics Laboratory at 鶹Ƶ 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 鶹Ƶ (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.”
Notes to Editors:
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Publication Reference Stephen J. Clark, Ricard Argelaguet, Chantriolnt-Andreas Kapourani, Thomas M. Stubbs, Heather J. Lee, Celia Alda-Catalinas, Felix Krueger, Guido Sanguinetti, Gavin Kelsey, John C. Marioni, Oliver Stegle, Wolf Reik; scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells; Nature Communications (2018) DOI:
Research Funding Work at 鶹Ƶ is possible thanks to the Biotechnology and Biological Sciences Research Council (BBSRC), in particular this work forms part of the Strategic Programme Grant for Epigenetics. This work also included funding from the Wellcome Trust, EU Blueprint, EpiGeneSys. Gavin Kelsey is supported by the Medical Research Council (MRC). Oliver Stegle is supported by the European Molecular Biology Laboratory (EMBL). Chantriolnt-Andreas Kapourani is supported by the EPSRC Centre for Doctoral Training in Data Science and the University of Edinburgh.
Press Contact Oana Stroe, European Bioinformatics 鶹Ƶ (EMBL-EBI), Communications Officer stroe@ebi.ac.uk
Image Credit 鶹Ƶ
Affiliated Authors (in author order): Stephen J. Clark, Thomas M. Stubbs, Heather J. Lee, Celia Alda-Catalinas – Epigenetics Laboratory, Babraham 鶹Ƶ Feliz Krueger - Bioinformatics Facility, Babraham 鶹Ƶ Gavin Kelsey - Group Leader, Epigenetics Laboratory, Babraham 鶹Ƶ Wolf Reik - Group Leader, Epigenetics Laboratory, Babraham 鶹Ƶ
About 鶹Ƶ: The receives strategic funding from the (BBSRC) to undertake world-class life sciences research. Its goal is to generate new knowledge of biological mechanisms underpinning ageing, development and the maintenance of health. Research focuses on signalling, gene regulation and the impact of epigenetic regulation at different stages of life. By determining how the body reacts to dietary and environmental stimuli and manages microbial and viral interactions, we aim to improve wellbeing and support healthier ageing.
About the European Bioinformatics 鶹Ƶ (EMBL-EBI): The (EMBL-EBI) is a global leader in the storage, analysis and dissemination of large biological datasets. We help scientists realise the potential of ‘big data’ by enhancing their ability to exploit complex information to make discoveries that benefit humankind.
We are at the forefront of computational biology research, with work spanning sequence analysis methods, multi-dimensional statistical analysis and data-driven biological discovery, from plant biology to mammalian development and disease.
We are part of and are located on the , one of the world’s largest concentrations of scientific and technical expertise in genomics.
22 February 2018