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A new, faster, more complete system of genetic analysis developed

By 17 de October de 2008November 18th, 2020No Comments
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A new, faster, more complete system of genetic analysis developed

An international team of researchers has developed a new system of combinatory analysis that offers faster, fuller information than classic genetic analysis can provide. The team's work, published in the latest issue of the journal Science, sets out a combinatory analysis of the activity of the JNK protein in cell culture. The JNK protein plays a role in processes of migration, cell death and stress response (DOI: 10.1126/science.1158739).

Enrique Martín Blanco, who is a researcher at the Barcelona Institute of Molecular Biology (IBMB-CSIC) and works at the Barcelona Science Park, took part in the research effort along with fellow researcher and team member Flora Llense, scientists at Harvard University (Boston, USA), the Institute of Cancer Research in London (UK) and the Mount Sinai Hospital of Toronto (Canada).

As Martín Blanco explains, the body’s cellular responses (e.g. when wounds heal or metastasis spreads) call into play complex, interconnected cell signalling networks. Until now, the systems of genetic analysis used by the scientific community to uncover how these processes unfold have not always defined the function of the genes involved. “Although the classic systems have succeeded in identifying the essential genes involved in signalling networks,” Martín Blanco notes, “they don’t normally provide a wealth of information on the functional relationships that exist between them”. In order to clarify the idea, he offered an example: “Classic genetic analyses can determine whether the deactivation of gene A will lead to a response from gene B. They cannot, however, explain why gene B responds as it does.”

The combinatory analysis described in the paper, according to Martín Blanco, represents “a real step forward using systems biology to study the genome”. Systems biology, unlike classic empirical methods, uses mathematical models to describe the behaviour of the object of study in terms of a complex network. Developments in the field, which began to take off at the beginning of this century, are hoped to give rise to applications in pharmacology and biomedicine.

The technique developed by Martín Blanco’s team follows the same line, successfully resulting in rapid and direct identification of the systems of functional connections regulating cell signalling. More specifically, the researchers have defined a combinatory network of signalling cascades at work in the activation of the JNK enzyme, which stands at the heart of the team’s research and concerns wound healing as well as cell invasion in some kinds of cancer.

To obtain their results, the team made use of a biosensor capable of detecting JNK activity and registering it through chromatic changes. Using RNA interference, the various colour changes within cells were analysed for 18,000 genetic combinations. Then the data were put together to create a mathematical algorithm enabling researchers to construct a network of functional connections controlling the JNK cascade.

As Martín Blanco (IBMB-CSIC) explains, the method can be extrapolated to other models. “We just have to develop the right biosensor to make it happen”, he said. The analytical results also have a high predictive value, eliminating the need to start from scratch when doing analyses of complex processes that include JNK as a key element.