Thaindian News

London, February 23 (ANI): American researchers at the Whitehead Institute and Massachusetts Institute of Technology say that they have developed a novel approach to analyse cellular data, and have been gaining new understanding of Parkinsons diseases destructive pathways.
Thus far, the researchers have used the new computational technique to analyse alpha-synuclein, a mysterious protein that is associated with Parkinson’’s disease.
Cells are constantly adapting to various stimuli, including changes in their environment and mutations, through an intricate web of molecular interactions. Knowledge of these changes is crucial for developing new treatments for diseases.
Scientists across the world have been turning to new technologies to gain more and more information about how a cell responds to various stimuli.
Such information generally exists in two major forms: genetic screen data (the results from deleting a gene from a cell’’s genome and seeing what observable traits appear in the cell) and information on the cellular levels of messenger RNA (mRNA, which is the template for proteins).
Each type of data is actually biased toward identifying different aspects of cellular response, and thus they have largely been analysed independently of each other.
However, the new algorithm, known as ResponseNet, exploits these biases and allows for combined analysis in which both data types are integrated with molecular interactions data into a diagram that connects the experimentally identified proteins and genes.
Esti Yeger-Lotem, a postdoctoral researcher in the laboratories of Whitehead Member Susan Lindquist and of Ernest Fraenkel at MIT’’s Biological Engineering department, says that analysing such probable pathways leads to the emergence of a systems view of the cellular response.
“This allows for a more complete understanding of cellular response and can reveal hidden components of the response that may be targeted by drugs,” Nature magazine quoted her as saying.
Laura Riva, a postdoctoral researcher in MIT’’s biological engineering department and one of the designers of the algorithm, said that ResponseNet could prove very useful for researchers.
“It is a powerful approach for interpreting experimental data because it can efficiently analyse tens of thousands of nodes and interactions. The output of ResponseNet is a sparse network connecting some of the genetic data to some of the transcriptional data via intermediate proteins. Biologists can look at the network and understand which pathways are perturbed, and they can use it to generate testable hypotheses,” says Riva, who is also a co-author on the article.
With an eye on showing ResponseNet’’s capabilities, Yeger-Lotem entered the data from screens of 5,500 yeast strains (Saccharomyces cerevisiae), which are based on a yeast model that creates large amounts of the protein alpha-synuclein, thereby mimicking the toxic effects of alpha-synuclein accumulation in Parkinson’’s disease patients” brain cells.
Ernest Fraenkel, Assistant Professor of Biological Engineering at MIT, says that the alpha-synuclein data are an excellent test case for the algorithm, which has lead to new insights from existing data.
“The connection between alpha-synuclein and Parkinson’’s disease is enigmatic. We have wonderful data from the yeast model, but despite this richness of data, so little is known about what alpha-synuclein really does in the cell,” says Fraenkel.
The researchers revealed that ResponseNet used that data to identify several links between alpha-synuclein toxicity and basic cell processes, including those used to recycle proteins and to usher the cell through its normal life cycle.
They also found that ResponseNet tied alpha-synuclein toxicity to a highly-conserved pathway targeted by cholesterol-lowering statin drugs, and another pathway targeted by the immunosuppressing drug rapamycin.
“Some of the things we have found offer a promise to speed the development of new therapeutic strategies for Parkinson’’s disease. For the sake of the patients involved, let’’s hope they hold true in a human brain,” says Lindquist. (ANI)