Modelling and measuring intracellular competition for finite resources during gene expression

Abstract

Dissecting the competition between genes for shared expressional resources is of fundamental importance for understanding the interplay between cellular components. Owing to the relationship between gene expression and cellular fitness, genomes are shaped by evolution to improve resource allocation. Whereas experimental approaches to investigate intracellular competition require technical resources and human expertise, computational models and in silico simulations allow vast numbers of experiments to be carried out and controlled easily, and with significantly reduced costs. Thus, modelling competition has a pivotal role in understanding the effects of competition on the biophysics of the cell. In this article, we review various computational models proposed to describe the different types of competition during gene expression. We also present relevant synthetic biology experiments and their biotechnological implications, and discuss the open questions in the field.

An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells

“…To date, much effort has gone into identifying and engineering gene regulators with unique binding specificity, e.g., between TFs and their DNA-binding sites, with the goal of finding gene regulators that work orthogonally 7 , 14 – 18 . Nevertheless, even if subsystems are entirely composed of putatively orthogonal regulators, their gene expression levels can still become coupled to each other via competition for shared cellular resources 2 , 12 , 13 , 19 , 20 . For example, it has been demonstrated in prokaryotes that genes compete for ribosomes, such that increased expression from one gene decreases expression from others by sequestering, i.e., loading, ribosomes 12 , 13 .…”

Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics

“…The importance of studying supply and demand of tRNA has already been demonstrated before [ 1 , 10 , 19 ]. The relation between tRNA abundance and codon decoding rates was previously modeled [ 41 , 42 ] and various aspects of tRNA aminoacylation and recycling dynamics [ 19 , 43 – 45 ].…”

“…Dozens of studies in recent years have demonstrated the advantages of using computational models of mRNA translation in basic science and biotechnology (see, for example, [1][2][3][4][5][6][7][8][9][10][11]). Whole cell modelling of translation is a fundamental component of synthetic and systems biology, with implications in various fields, such as biotechnology and biomedical engineering.…”

Molecules to Microbes

“…Despite this obvious difference between cellular and viral entities, it is the expression of informational chemical systems (i.e., gene expression) that connects the inanimate genetic elements to the chemical processes and the phenotypes. In his oral presentation Tuller demonstrated the computational models that could predict various aspects of the biophysics of gene expression and evaluated the understanding of the evolution of cellular organisms and viruses further-further information on this interesting topic can be found in his papers [39][40][41].…”