The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes

Area of Science:

• Molecular Biology
• Systems Biology
• Genetics

Background:

• Cellular processes exhibit inherent stochasticity, leading to cell-to-cell variation in protein abundance, commonly referred to as noise.
• While noise has been modeled, its functional significance and implications for cellular robustness remain largely unexplored.

Approach:

• Revisited existing noise models to identify the number of messages transcribed per cell cycle as a critical determinant.
• Utilized yeast as a model organism to demonstrate the predictive power of transcription levels on noise scaling and magnitude.
• Extended the investigation to other model organisms, including Escherichia coli and human cells, for comparative analysis.

Key Points:

• The number of messages transcribed per cell cycle quantitatively predicts noise in protein abundance in yeast.
• A minimum transcription level of one message per cell cycle acts as a conserved lower floor for essential gene expression.
• This minimum transcription level is conserved across Escherichia coli, yeast, and human cells.

Conclusions:

• Robustness to transcriptional noise is a key factor in determining expression levels for essential genes.
• A conserved transcriptional program, with a minimum of one message per cell cycle, ensures noise robustness from bacteria to humans.
• This fundamental strategy highlights the evolutionary importance of noise control in gene expression for cellular function.