Jurgen and Christoff contributed a kinetic modelling analysis to a publication that came out last month in Nucleic Acid Research. The paper describes improved measurements of globally quantify RNA processing rates and half-lives for mRNAs in the sleeping sickness parasite Trypanosoma brucei.

Christoff plugged those values into a kinetic model of gene expression. The modelling shows that RNA half-life is a stronger predictor of total mRNA levels than the RNA processing rates. However, none of the two processes alone was sufficient to fully predict total RNA levels. Instead, both processes exert control, and it is the combination of them that determines RNA total levels.

The paper is linked to other papers that our group published in collaboration with other groups: A previous model that Jurgen made in 2008, has now been used again to interpret improved datasets. For the modelling this is a follow up to analysis with versions of the model in 2014 and 2016.

How can you measure something that cannot be measured directly? Think of a rate: this must always be inferred from some other measurements. In the 6^th of Jan issue of Nature Metabolism the Springer lab describes a new mechanism by which cells can measure metabolic rates – in this case rates of the conversion of the sugar galactose in Baker’s yeast. They found that the key enzyme of the galactose pathway, galactose kinase, not only sets the metabolic rate, but also directly regulates the enzyme levels of the pathway. Bas Teusink, Bob Planqué and Frank Bruggeman wrote a News & Views piece about the relevance of the finding. The VU-AIMMS researchers propose that this mechanism provides a missing link in our understanding how cells can optimally distribute cellular resources to maximize fitness. Read about it here:

https://rdcu.be/d5q7Y