Pathological processes are usually characterised by altered gene activity in the cells affected. So, gaining an accurate picture of gene activity can provide the key to the development of new, targeted therapies. Whether these therapies then work as we would want them to can also be verified by looking at genes and the processes they initiate.
It is no wonder that research is focused on methods and techniques that provide detailed information about the genetic activity of individual cells. A research team at the University of Würzburg (JMU) has now developed a technique that is a significant improvement on the methods used to date. Scientists from the Institute for Molecular Infection Biology (IMIB) and the Helmholtz Institute for RNA-based Infection Research (HIRI) were involved. They have presented the results of their work in the current issue of the journal Nucleic Acids Research.
Analysis of a synthetic transcriptome
“We have developed a technique that can be used to analyse the translational landscape of a fully customisable synthetic transcriptome, in other words one outside the cell,” is how Jörg Vogel explains the central outcome of the study. Vogel heads the Institute for Molecular Infection Biology at JMU and is also the Director of HIRI as well as the principal author of the study. The new technique has been given the scientific name INRI-seq, which is short for in vitro Ribo-seq.
A transcriptome is a collection of all the genes that are active in a cell at a given point in time. It consists of the sum of the existing mRNA — the transporters of the blueprints for proteins from the cell nucleus to the ribosomes. Ribosomes are the “protein factories” of the cell; this is where translation of the nucleotide sequence of the mRNA into the amino acid sequence of a protein takes place.
Refinement of comparable methods
In principle, INRI-seq is a refinement of comparable methods that pursue the same goal but provide less accurate results or have other disadvantages. For example, RNA sequencing (RNA-seq) determines the concentration of mRNA in cells, allowing conclusions to be drawn about their active genes. However, the final protein abundance does not always correlate with the respective mRNA concentrations.
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