New technology enables us to "chart" all cells in the brain
(Vienna, 21 December 2015) The human brain is made up of hundreds of millions of cells. Many of these cells and their functions are as yet unknown. This is about to change with a new technology that is being used for the first time at the Center for Brain Research at MedUni Vienna and Karolinska Institutet in Stockholm. By combining traditional methods of identifying cells under a microscope and so-called "single-cell RNA sequencing", it is possible to identify every building block of any given excitable cell. "We are well on the way to being able to map many, if not all, neurons and their functions before too long," explains lead investigator Tibor Harkany, Head of the Department of Molecular Neurosciences at MedUni Vienna.
So far, we have only been able to study neurons based on a set of scientific premises and to determine or "search for" their function on the basis of a priori knowledge on their morphology (what does the cell look like?), biochemistry (what does it contain?) and what partners a cell might communicate with. "This has hindered the analysis of new types of neurons for which we do not have any anatomical, biochemical or electrophysiological markers. Neuroscience therefore needs radically new approaches to chart the identity of all neurons and other types of non-neuronal cells in the brain," explains Harkany. "Any new method that helps us to gain a better understanding of the brain and its cellular components has direct relevance to our search for new therapies to treat neuropsychiatric and age-related diseases."
Catalogue and family tree of all mRNAs
Using the new technology, which is being jointly applied for the first time in the world in a collaboration between MedUni Vienna and Karolinska Institutet, it is now possible to screen each cell and to compile an exact list of its constituents without any prior knowledge – and at the same time to assess its activity and function in the brain in relation to specific behaviors. Thousands of genes are active at any given time in a single neuron. "This will enable us to compile a representative catalogue of mRNA molecules in the neurons and we can use this, for example, to differentiate various neuronal subtypes and to compare healthy and diseased cells or young neurons with old. This technology is a revolutionary breakthrough, because it enables us to record molecular determinants of neuronal identity," says Harkany. mRNA molecules are single-stranded ribonucleic acids that carry the code for all proteins that a cell produces.
"It was an enormous challenge to overcome existing technical difficulties, especially to preserve RNA in a state that allows high-quality and reproducible quantitative and qualitative analyses even when first assessing more than hundred parameters of neuronal activity" adds Janos Fuzik, the study’s lead author. As such, the novel technology allows to categorise how neurons might be related to each other, which subsets function in a similar way, what essentially differentiates them, and to predict their roles in neuronal networks and response patterns at unprecedented precision.
Harkany: "Then we will be able to compile a family tree for individual neurons and have a better understanding of their specific contributions to their networks, for example during emotional or learning processes or in memory formation." Initial study findings included the discovery of five subtypes of neurons that have previously been impossible to research because of their diverse nature. The study also offers another important potential for analysing other types of brain cells, such as astrocytes or microglia (parts of the immune system) in greater detail than was previously possible.
The successful application of the new technology opens up new possibilities for research and clinical practice: entry points for new drugs can be identified more quickly, thus speeding up the development of medicines. At the same time, the new method can also be used for identifying and analysing excitable cells in pancreatic and cardiac tissues, or even in brain tumours. "In this way we will be able to detect both accurately and relatively quickly which cell is not working correctly or is damaged and, more specifically, what is going wrong in the cell," say the MedUni Vienna brain researchers.
Service Nature Biotechnology
Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes. János Fuzik, Amit Zeisel, Zoltán Máté, Daniela Calvigioni, Yuchio Yanagawa, Gábor Szabó, Sten Linnarsson, Tibor Harkany. December 21st, 2015.
Five research clusters at MedUni Vienna
In total, five research clusters have been established at MedUni Vienna. In these clusters, MedUni Vienna is increasingly focusing on fundamental and clinical research. The research clusters include medical imaging, cancer research/oncology, cardiovascular medicine, medical neurosciences and immunology. The present work at MedUni Vienna falls within the remit of the medical neuroscience cluster.