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The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes.
Lo, Teresa W; Choi, Han Kyou James; Huang, Dean; Wiggins, Paul A.
Afiliación
  • Lo TW; Department of Physics, University of Washington, Seattle, Washington 98195, USA.
  • Choi HKJ; Department of Physics, University of Washington, Seattle, Washington 98195, USA.
  • Huang D; Department of Physics, University of Washington, Seattle, Washington 98195, USA.
  • Wiggins PA; Department of Physics, University of Washington, Seattle, Washington 98195, USA.
bioRxiv ; 2023 Jul 07.
Article en En | MEDLINE | ID: mdl-37461493
ABSTRACT
The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In this paper, we revisit the noise model and identify the number of messages transcribed per cell cycle as the critical determinant of noise. In yeast, we demonstrate that this quantity predicts the non-canonical scaling of noise with protein abundance, as well as quantitatively predicting its magnitude. We then hypothesize that growth robustness requires an upper ceiling on noise for the expression of essential genes, corresponding to a lower floor on the transcription level. We show that just such a floor exists a minimum transcription level of one message per cell cycle is conserved between three model organisms Escherichia coli, yeast, and human. Furthermore, all three organisms transcribe the same number of messages per gene, per cell cycle. This common transcriptional program reveals that robustness to noise plays a central role in determining the expression level of a large fraction of essential genes, and that this fundamental optimal strategy is conserved from E. coli to human cells.

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos