EMBO Conference on Protein Synthesis and Translational Control

HELENA FIRCZUK
13
Speaker Abstracts
Comprehensive rate control analysis of the eukaryotic translation pathway
John E.G. McCarthy, Helena Firczuk, Shichina Kannambath, Xi Wang, Helen Bryant, Hans
Westerhoff, Pedro Mendes
Manchester Interdisciplinary Biocentre, United Kingdom
Elucidation of the control principles governing a complex pathway like translation can only be
achieved via quantitative systems analysis. We have performed the first comprehensive in vivo
rate control analysis of the yeast translation machinery. Using the tet07 operator we have
progressively suppressed transcription of each translation factor gene and have determined
how this affects yeast growth rate and in vivo protein synthesis rate. The relationship between
the protein synthesis rate and cellular concentration of each factor enables us to estimate the
sensitivity coefficient CJ. The latter reflects how each individual translation factor contributes to
the steady state translation rate. For most of the proteins we also explored the CJ values at
cellular concentrations above wt levels (>100%). This in vivo analysis has been extended by
parallel in vitro experiments in a yeast cell-free system, allowing us to assess the effects of
ribosome:mRNA saturation on control. All three stages of translation (initiation, elongation and
termination) have been represented as a set of ordinary (and/or stochastic) differential
equations and simulated using the software COPASI.
Translational control is distributed over multiple components of the translation machinery.
Some components, for example eIF1, eIF3a and eIF4A, show strong control (large CJ). Others,
for example Pab1 and eIF5, show surprisingly low CJ values – indeed, these factors appear to
be present at levels in excess (~50%) to the requirements of translation. Generally, the value of
CJ shows no simple correlation with a factor’s intracellular concentration. These, and other,
results reveal many unexpected features of the system that could not have been predicted on
the basis of non-quantitative data.