New technology enables us to "chart" all cells in the brain

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.

‘Junk’ DNA now center stage

The classes of RNA molecules encoded by DNA sequences previously considered non functional may play a vital role in cell stress responses, and could one day lead to cancer treatments. A*STAR researchers have identified a class of the long non-coding RNAs responding upon oxidation stress and characterized and specified their functions across stress stimuli and cell types. 

Human skin and lung cells were subjected to oxidative stress, by the research team, stimulating cellular pathways of repair and survival. While protein-coding genes were generally inhibited, stress caused noncoding genomic regions to produce thousands of RNA molecules called 'long noncoding RNAs (lncRNAs)’.

Author Igor Kurochkin says the role of lncRNAs is a mystery. “We don’t know their function, or even if they function at all.” They may act in the evolution of new genes; in helping cells respond to stress; in interaction with genes or proteins; or, says another author, Vladimir Kuznetsov, “all of these at once!”

Antonis Giannakakis et al. Contrasting expression patterns of coding and noncoding parts of the human genome upon oxidative stress, Scientific Reports (2015). DOI: 10.1038/srep09737

Skin cells were subjected to stress so the researchers could examine the cellular pathways of the stress response. Credit: vshivkova/iStock/Thinkstock

Three members of crew at work on the starboard engine gantry of a Royal Navy Air Service North Sea (N.S.) type non-rigid airship during an anti-submarine patrol off the British coast circa 1918. None appear to be wearing a safety line. On the upper level the mechanic is standing next to his compartment from which he controlled the 240HP Fiat engines. On the lower level a gunner mans his gun.

Small RNAs affect development of seeds. These are arabidopsis seeds three, four, five, six and seven days after pollination (left to right). First row: diploid seeds. Second row: seeds from a cross between a diploid mother and tetraploid father. Third row: seeds from a cross between a tetraploid mother and diploid father. Fourth row: tetraploid seeds. Note that seeds in the third row (five to six days after pollination) are much smaller than those in the second row as a result of increased maternally inherited small RNAs. (Credit: Z. Jeff Chen, The University of Texas at Austin)

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