Efficiency of protein synthesis inhibition depends on tRNA and codon compositions

Abstract

7Regulation and maintenance of protein synthesis are vital to all organisms and are thus key 8 targets of attack and defense at the cellular level. Here, we mathematically analyze protein synthesis 9 for its sensitivity to the inhibition of elongation factor EF-Tu and/or ribosomes in dependence of 10 the system's tRNA and codon compositions. We find that protein synthesis reacts ultrasensitively 11 to a decrease in the elongation factor's concentration for systems with an imbalance between codon 12 usages and tRNA concentrations. For well-balanced tRNA/codon compositions, protein synthesis 13 is impeded more effectively by the inhibition of ribosomes instead of EF-Tu. Our predictions are 14 supported by re-evaluated experimental data as well as by independent computer simulations. Not 15 only does the described ultrasensitivity render EF-Tu a distinguished target of protein synthesis 16 inhibiting antibiotics. It may also enable persister cell formation mediated by toxin-antitoxin systems. 17The strong impact of the tRNA/codon composition provides a basis for tissue-specificities of disorders 18 caused by mutations of human mitochondrial EF-Tu as well as for the potential use of EF-Tu targeting 19 drugs for tissue-specific treatments. 20Author Summary 21We predict and analyze the response of differently composed protein synthesis systems to the inhibition 22 of elongation factor EF-Tu and/or ribosomes. The study reveals a strong interdependency of a protein 23 synthesis system's composition and its susceptibility to inhibition. This interdependency defines a generic 24 mechanism that provides a common basis for a variety of seemingly unrelated phenomena including, for 25 example, persister cell formation and tissue-specificity of certain mitochondrial diseases. The described 26 mechanism applies to simple artificial translation systems as well as to complex protein synthesis in vivo.

ExtRamp Online: Enabling ramp sequence calculations via an intuitive web interface.

“…We anticipate that ExtRamp Online will help researchers understand how altered tRNA levels affect ramp sequences and contribute to disease development. Many diseases are associated with altered tRNA levels (Gingold, et al, 2014;Goodarzi, et al, 2016;Kirchner, et al, 2017;Kirchner and Ignatova, 2015;Mahlab, et al, 2012;Pavon-Eternod, et al, 2009;Pavon-Eternod, et al, 2013;Polte, et al, 2019;Rudorf, 2019;Torres, et al, 2014). For example, cancer cells increase expression of genes that promote cell proliferation and cancer progression by altering tRNA levels to match genic codon usage biases (Gingold, et al, 2014;Goodarzi, et al, 2016;Pavon-Eternod, et al, 2009;Pavon-Eternod, et al, 2013).…”