Revolution in medicine and biology
Breakthrough protein sequencing method will make cancer diagnosis easier
Georgy Golovanov, Hi-tech+
The method developed within the walls of the University of Texas at Austin, will allow biologists to sequence protein as DNA, with millions of molecules simultaneously.
"In fact, we have created a protein study technology that resembles DNA sequencing," says Professor Edward Marcotte, one of the inventors. Work on this project began six years ago, when Marcotte and his colleagues first thought about adapting gene sequencing to study proteins.
The technology will reveal complete information about the functions of tens of thousands of proteins that play an important role in the functioning of the body.
Modern laboratory standards for protein sequencing using spectrometry are not sensitive enough – they can detect a protein only if it is represented by about a million copies. They also have low throughput, that is, existing methods notice only a few thousand individual types of proteins in a sample, according to a press release from the University of Texas at Austin New Protein Sequencing Method Could Transform Biological Research.
The new method, called monomolecular fluorosequencing, opens up the possibility for scientists to sequence millions of individual protein molecules simultaneously. And if you optimize the process, then billions.
A number of diseases – cancer, Alzheimer's disease, heart failure, diabetes – are accompanied by the production of proteins by cells that serve as unique biomarkers. Their detection helps researchers understand the causes of disorders or diagnose diseases at an early stage. For example, scientists could observe a cancerous tumor cell by cell to understand how it develops from a mass of the same type of cells to a mixture of divergent ones, each with its own strengths and weaknesses.
Article by Swaminathan et al. Highly parallel single-molecule identification of proteins in zeptomole-scale mixtures is published in the journal Nature Biotechnology – VM.
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