ABSTRACT
Defining the cellular factors that drive growth rate and proteome composition is essential for understanding and manipulating cellular systems. In bacteria, ribosome concentration is known to be a constraining factor of cell growth rate, while gene concentration is usually assumed not to be limiting. Here, using single-molecule tracking, quantitative single-cell microscopy, and modeling, we show that genome dilution in Escherichia coli cells arrested for DNA replication limits total RNA polymerase activity within physiological cell sizes across tested nutrient conditions. This rapid-onset limitation on bulk transcription results in sub-linear scaling of total active ribosomes with cell size and sub-exponential growth. Such downstream effects on bulk translation and cell growth are near-immediately detectable in a nutrient-rich medium, but delayed in nutrient-poor conditions, presumably due to cellular buffering activities. RNA sequencing and tandem-mass-tag mass spectrometry experiments further reveal that genome dilution remodels the relative abundance of mRNAs and proteins with cell size at a global level. Altogether, our findings indicate that chromosome concentration is a limiting factor of transcription and a global modulator of the transcriptome and proteome composition in E. coli. Experiments in Caulobacter crescentus and comparison with eukaryotic cell studies identify broadly conserved DNA concentration-dependent scaling principles of gene expression.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Data have been added in a new figure (Figure 4) to show the effects of genome dilution on the ribosomal RNA concentration; a new figure (Figure 6) has been created to help compare the effects of genome dilution in cells growing in nutrient-poor versus nutrient-rich media; former Figure 5 (now Figure 7) has been revised and a new supplementary figure (Figure 7 -- figure supplement 2) has been added to include correlations between the proteomic or transcriptomic data and previously published datasets of gene essentiality or expression statistics; the text has been revised to discuss new results or clarify points.
