New clues on the basis of Parkinson's disease and other "synucleinopathies"
Whitehead Institute for Biomedical Research News Jan 30, 2017
ParkinsonÂs disease (PD) and other Âsynucleinopathies are known to be linked to the misfolding of alpha–synuclein protein in neurons. Less clear is how this misfolding relates to the growing number of genes implicated in PD through analysis of human genetics. In two studies published in the advance online edition of the journal Cell Systems, researchers affiliated with Whitehead Institute and Massachusetts Institute of Technology (MIT) explain how they used a suite of novel biological and computational methods to shed light on the question.
To start, they created two ways to systematically map the footprint of alpha–synuclein within living cells. ÂIn the first paper, we used powerful and unbiased genetic tools in the simple BakerÂs yeast cell to identify 332 genes that impact the toxicity of alpha–synuclein, explained Vikram Khurana, first and co–corresponding author on the studies. ÂAmong them were multiple genes known to predispose individuals to ParkinsonÂs – so we show that various genetic forms of ParkinsonÂs are directly related to alpha–synuclein. Moreover, the results showed that many effects of alpha–synuclein have been conserved across a billion years of evolution from yeast to human, said Khurana, former Visiting Scientist at the Whitehead Institute.
ÂIn the second paper, we created a spatial map of alpha–synuclein, cataloging all the proteins in living neurons that were in close proximity to the protein, explained Chee Yeun Chung, former Whitehead Institute Senior Research Scientist, who co–led both studies with Khurana. The mapping was achieved without disturbing the native environment of the neuron, by tagging alpha–synuclein with an enzymeÂAPEXÂthat allowed proteins less than 10 nanometers away from synuclein to be marked with a trackable fingerprint. ÂAs a result, for the first time, we were able to visualize the proteinÂs location, at minute scale, under physiologic conditions in an intact brain cell, noted Chung, who is now Scientific Co–founder and Associate Director at Yumanity Therapeutics in Cambridge.
Remarkably, the maps derived from these two processes were closely related and converged on the same ParkinsonÂs genes and cellular processes. Whether in a yeast cell or in a neuron, alpha synuclein directly interfered with the rate of production of proteins in the cell, and the transport of proteins between cellular compartments. ÂIt turns out the mechanisms of toxicity of the misfolded protein are closely related to which proteins it directly interacts with, and that these interactions can explain connections between different ParkinsonÂs genetic risk factors, said Khurana, now a Principal Investigator within the Ann Romney Center for Neurologic Diseases at Brigham and WomenÂs Hospital and the Harvard Stem Cell Institute.
Finally, the authors addressed two major challenges for any study that generates large data–sets of individual genes and proteins in model organisms like yeast: How to assemble the data into coherent maps? And how to integrate information across species, in this case from yeast to human?
Enter computational biologist Jian Peng, former Visiting Scientist at Whitehead Institute and postdoctoral researcher at MIT. ÂFirst, we had to figure out much better methods to find human counterparts of yeast genes, and then we had to arrange the humanized set of genes in a meaningful way, explained Peng, now Assistant Professor of Computer Sciences at University of Illinois, Urbana–Champaign. ÂThe result was TransposeNet, a new suite of computational tools that uses machine learning algorithms to visualize patterns and interaction networks based on genes that are highly conserved from yeast to humansÂand then makes predictions about the additional genes that are part of the alpha–synuclein toxicity response in humans.Â
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To start, they created two ways to systematically map the footprint of alpha–synuclein within living cells. ÂIn the first paper, we used powerful and unbiased genetic tools in the simple BakerÂs yeast cell to identify 332 genes that impact the toxicity of alpha–synuclein, explained Vikram Khurana, first and co–corresponding author on the studies. ÂAmong them were multiple genes known to predispose individuals to ParkinsonÂs – so we show that various genetic forms of ParkinsonÂs are directly related to alpha–synuclein. Moreover, the results showed that many effects of alpha–synuclein have been conserved across a billion years of evolution from yeast to human, said Khurana, former Visiting Scientist at the Whitehead Institute.
ÂIn the second paper, we created a spatial map of alpha–synuclein, cataloging all the proteins in living neurons that were in close proximity to the protein, explained Chee Yeun Chung, former Whitehead Institute Senior Research Scientist, who co–led both studies with Khurana. The mapping was achieved without disturbing the native environment of the neuron, by tagging alpha–synuclein with an enzymeÂAPEXÂthat allowed proteins less than 10 nanometers away from synuclein to be marked with a trackable fingerprint. ÂAs a result, for the first time, we were able to visualize the proteinÂs location, at minute scale, under physiologic conditions in an intact brain cell, noted Chung, who is now Scientific Co–founder and Associate Director at Yumanity Therapeutics in Cambridge.
Remarkably, the maps derived from these two processes were closely related and converged on the same ParkinsonÂs genes and cellular processes. Whether in a yeast cell or in a neuron, alpha synuclein directly interfered with the rate of production of proteins in the cell, and the transport of proteins between cellular compartments. ÂIt turns out the mechanisms of toxicity of the misfolded protein are closely related to which proteins it directly interacts with, and that these interactions can explain connections between different ParkinsonÂs genetic risk factors, said Khurana, now a Principal Investigator within the Ann Romney Center for Neurologic Diseases at Brigham and WomenÂs Hospital and the Harvard Stem Cell Institute.
Finally, the authors addressed two major challenges for any study that generates large data–sets of individual genes and proteins in model organisms like yeast: How to assemble the data into coherent maps? And how to integrate information across species, in this case from yeast to human?
Enter computational biologist Jian Peng, former Visiting Scientist at Whitehead Institute and postdoctoral researcher at MIT. ÂFirst, we had to figure out much better methods to find human counterparts of yeast genes, and then we had to arrange the humanized set of genes in a meaningful way, explained Peng, now Assistant Professor of Computer Sciences at University of Illinois, Urbana–Champaign. ÂThe result was TransposeNet, a new suite of computational tools that uses machine learning algorithms to visualize patterns and interaction networks based on genes that are highly conserved from yeast to humansÂand then makes predictions about the additional genes that are part of the alpha–synuclein toxicity response in humans.Â
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