Unravelling a 40 year gene mystery – and putting the solution in an app
Scientists have unravelled the 40 year mystery of how gene expression – the process by which the genetic blueprints in DNA are delivered to the cell’s protein-making machinery – is initiated. The research,published today in Nature, and conducted in Australia by Australian, German and Russian scientists, involved developing a new technique that takes snapshots of the first steps of protein synthesis from RNA in the cell. The first data was made freely available today with the release of an app for high-content data visualisation, calledTCP viewer.
Researcher on the study, Dr Traude Beilharz from the Monash Biomedicine Discovery institute, said the approach and its results will allow future researchers and clinicians to study the way gene-expression goes awry and causes diseases, such as cancer.
The research team, led by Professor Thomas Preiss at the Australian National University (ANU), have been working on the project for more than seven years. "A comparatively short period of time given the question of controlled translation has a 40 year history," Professor Preiss said.
Over the course of the project, Dr Stuart Archer and Dr Beilharz, from Monash University and Dr Nikolay Shirokikh, from the Moscow Regional State Institute, and now at the ANU, each brought a separate expertise to the team that made it possible to overcome previous technological barriers in the field.
Gene expression is one of the – if not the – most important processes in nature, and occurs via a go-between molecule known as RNA. The RNA is threaded through a complex nano-machine called the ribosome to decode it into protein. How cells actually initiate this process, so that RNA can then be translated into actual proteins to build muscle cells, octopus neurons or even plant wall cells has never been fully understood.
A turning point for the research came from a serendipitous collaboration that saw Dr Archer join the newly formed Monash Bioinformatics Platform, a facility that harnesses the power of high performance computing to decipher and collate millions of pieces of biological data. The core strength of this bioinformatics platform is in making this big data – now common in biology – accessible through user-friendly visualisation interfaces and apps.
The research team used existing Next Generation Sequencing technologies, to decipher the information they collected from ribosome nano-machines caught in the act of decoding RNA in yeast.
Dr Archer said: “it was extremely challenging, because of the transient nature of the interactions with RNA. Many thought it couldn’t be done.” It’s what Dr Beilharz called “deep sequencing of RNA-footprints”: analysing the hundreds of millions of RNA sequences collected, literally the footprints of the ribosomes, to explain how they initiate the translation of RNA into protein.
Not every lab has the expertise on hand to implement the technology. But, by simply putting their gene of choice into the app, Dr Beilharz said: “anyone can see how its expression works, how the ribosome travels along the gene's RNA. In this way we expect scientists will be able to see where this process fails in disease, and where to target drugs to rectify this.” Dr Beilharz added that the team are now applying the technique to the human translation process.