We are developing new models for gene expression, which account for the coupling between mRNA and protein production and cell growth. Within these models the numbers of RNA polymerases and ribosomes are explicitly considered as dynamic variables, leading to important consequences regarding the growth dynamics. The models predict a regime where cells grow exponentially with mRNA and protein levels scaling with cell volume, and another with growth linear in time. We have also shown that by analyzing the time trajectory of the protein levels one can infer the relative fractions of the intrinsic and extrinsic noise in gene expression.
We developed models accounting for the action of transcription factors leading to interactions between the various genes and have shown that the gene regulatory network will become unstable at a critical size. Analyzing the structure of biological networks, we found global motifs that stabilize the network dramatically.
Relevant publications:
[1] Homeostasis of protein and mRNA concentrations in growing cells, Jie Lin and Ariel Amir, Nature Communications 9, 4496 (2018).
[2] Disentangling intrinsic and extrinsic gene expression noise in growing cells, Lin, J. and Amir, A., Physical review letters, 126(7), p.078101 (2021).
[3] Exploring the effect of network topology, mRNA and protein dynamics on gene regulatory network stability, Guo, Y. and Amir, A., Nature communications, 12(1), p.130 (2021).