By using innovative labeling methods, Max Planck researchers develop a technique to measure newly synthesized proteins in the active mouse brain.
The complexity of living things is driven, in large part, by the huge diversity of cell types. Since all cells of an organism share the same genes, the diversity of cells must come from the particular proteins that are expressed. Cells in the brain are generally divided into neurons and glia. Within these two categories, however, lies a large diversity of cell types that we are only beginning to discover.
The diversity of cell types in brain and other tissues has recently been expanded by new techniques, like RNA-sequencing, that identify and measure the mRNAs present in a cell (“the transcriptome”). Although mRNAs are the template for proteins, the transcriptome is a poor proxy for proteins that a cell actually makes (“the proteome”). Alvarez-Castelao et al. now developed new methods to detect real-time changes in the proteome. They report their findings in the latest edition of Nature Biotechnology.
Building on prior technology, developed by the Schuman Lab and collaborators David Tirrell from Caltech and Daniela Dieterich (Magdeburg University), Beatriz Alvarez-Castelao and colleagues took advantage of a protein “metabolic” labeling system in which proteins during synthesis are “tagged” with a modified building block (amino acid), which is, under normal conditions, not present in these cells.
In order to label proteins in a particular cell type exclusively, the research team used a mutant methionyl tRNA synthetase (MetRS) that recognizes the modified amino acid. They then created a mouse line in which the MetRS can be expressed in specific cell types. When the non-canonical amino acid is administered to the mutant MetRS mice via the drinking water, only proteins in cells expressing the mutant metRS are labeled.
The proteins labeled in cells can be visualized and recognized with antibodies or can be extracted and identified using mass spectrometry. Alvarez-Castelao: “We used the technique to identify two different sets of brain proteins, those present in excitatory neurons in the hippocampus, a brain structure important for animal navigation and learning and memory, and inhibitory neurons in the cerebellum, a structure involved in motor behavior.”.
A particularly striking feature of this technology is that one can detect directly changes in brain proteins in response to a modified environment. Mice that were raised in an enriched sensory environment with a labyrinth, running wheel, and toys of varied textures showed significant changes in the proteome in the hippocampus, particularly in proteins that work at neuronal synapses. Schuman:
“We think that, by combining this mouse with other “disease” mouse models, this method can be used to discover the proteins in particular cell-types and how proteomes change during brain development, learning, memory and disease.”.
Publication: Alvarez-Castelao, B., Schanzenbächer, C.T., Hanus,C., Glock, C., tom Dieck, S., Dörrbaum, A.R., Bartnik, I., Nassim-Assir, B., Ciirdaeva, E., Mueller, A., Dieterich, D., Tirrell, D.A., Langer, J.D. and Schuman, E.M. (2017). Cell-type-specific metabolic labeling of nascent proteomes in vivo Nature Biotechnology advanced online publication.
Dr. Arjan Vink | Max-Planck-Institut für Hirnforschung
For bacteria, the neighbors co-determine which cell dies first: The physiology of survival
17.07.2019 | Technische Universität München
Atacama Desert: Some lichens can meet their need for water from air humidity
17.07.2019 | Technische Universität Kaiserslautern
Scientists at the University Würzburg and University Hospital of Würzburg found that megakaryocytes act as “bouncers” and thus modulate bone marrow niche properties and cell migration dynamics. The study was published in July in the Journal “Haematologica”.
Hematopoiesis is the process of forming blood cells, which occurs predominantly in the bone marrow. The bone marrow produces all types of blood cells: red...
For some phenomena in quantum many-body physics several competing theories exist. But which of them describes a quantum phenomenon best? A team of researchers from the Technical University of Munich (TUM) and Harvard University in the United States has now successfully deployed artificial neural networks for image analysis of quantum systems.
Is that a dog or a cat? Such a classification is a prime example of machine learning: artificial neural networks can be trained to analyze images by looking...
An international research group led by scientists from the University of Bayreuth has produced a previously unknown material: Rhenium nitride pernitride. Thanks to combining properties that were previously considered incompatible, it looks set to become highly attractive for technological applications. Indeed, it is a super-hard metallic conductor that can withstand extremely high pressures like a diamond. A process now developed in Bayreuth opens up the possibility of producing rhenium nitride pernitride and other technologically interesting materials in sufficiently large quantity for their properties characterisation. The new findings are presented in "Nature Communications".
The possibility of finding a compound that was metallically conductive, super-hard, and ultra-incompressible was long considered unlikely in science. It was...
An interdisciplinary research team at the Technical University of Munich (TUM) has built platinum nanoparticles for catalysis in fuel cells: The new size-optimized catalysts are twice as good as the best process commercially available today.
Fuel cells may well replace batteries as the power source for electric cars. They consume hydrogen, a gas which could be produced for example using surplus...
The fly agaric with its red hat is perhaps the most evocative of the diverse and variously colored mushroom species. Hitherto, the purpose of these colors was...
24.06.2019 | Event News
29.04.2019 | Event News
17.04.2019 | Event News
17.07.2019 | Life Sciences
17.07.2019 | Physics and Astronomy
17.07.2019 | Physics and Astronomy