A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition

How total mRNA influences cell growth

Experimental observations tracing back to the 1960s imply that ribosome quantities play a prominent role in determining a cell's growth. Nevertheless, in biologically relevant scenarios, growth can also be influenced by the levels of mRNA and RNA polymerase. Here, we construct a quantitative model of biosynthesis providing testable scenarios for these situations. The model explores a theoretically motivated regime where RNA polymerases compete for genes and ribosomes for transcripts and gives general expressions relating growth rate, mRNA concentrations, ribosome, and RNA polymerase levels. On general grounds, the model predicts how the fraction of ribosomes in the proteome depends on total mRNA concentration and inspects an underexplored regime in which the trade-off between transcript levels and ribosome abundances sets the cellular growth rate. In particular, we show that the model predicts and clarifies three important experimental observations, in budding yeast and Escherichia coli bacteria: i) that the growth-rate cost of unneeded protein expression can be affected by mRNA levels, ii) that resource optimization leads to decreasing trends in mRNA levels at slow growth, and iii) that ribosome allocation may increase, stay constant, or decrease, in response to transcription-inhibiting antibiotics. Since the data indicate that a regime of joint limitation may apply in physiological conditions and not only to perturbations, we speculate that this regime is likely self-imposed.

A Systems Biology Approach To Disentangle the Direct and Indirect Effects of Global Transcription Factors on Gene Expression in Escherichia coli

Delineating the pleiotropic effects of global transcriptional factors (TFs) is critical for understanding the system-wide regulatory response in a particular environment. Currently, with the availability of genome-wide TF binding and gene expression data for Escherichia coli, several gene targets can be assigned to the global TFs, albeit inconsistently. Here, using a systematic integrated approach with emphasis on metabolism, we characterized and quantified the direct effects as well as the growth rate-mediated indirect effects of global TFs using deletion mutants of FNR, ArcA, and IHF regulators (focal TFs) under glucose fermentative conditions. This categorization enabled us to disentangle the dense connections seen within the transcriptional regulatory network (TRN) and determine the exact nature of focal TF-driven epistatic interactions with other global and pathway-specific local regulators (iTFs). We extended our analysis to combinatorial deletions of these focal TFs to determine their cross talk effects as well as conserved patterns of regulatory interactions. Moreover, we predicted with high confidence several novel metabolite-iTF interactions using inferred iTF activity changes arising from the allosteric effects of the intracellular metabolites perturbed as a result of the absence of focal TFs. Further, using compendium level computational analyses, we revealed not only the coexpressed genes regulated by these focal TFs but also the coordination of the direct and indirect target expression in the context of the economy of intracellular metabolites. Overall, this study leverages the fundamentals of TF-driven regulation, which could serve as a better template for deciphering mechanisms underlying complex phenotypes. IMPORTANCE Understanding the pleiotropic effects of global TFs on gene expression and their relevance underlying a specific response in a particular environment has been challenging. Here, we distinguish the TF-driven direct effects and growth rate-mediated indirect effects on gene expression using single- and double-deletion mutants of FNR, ArcA, and IHF regulators under anaerobic glucose fermentation. Such dissection assists us in unraveling the precise nature of interactions existing between the focal TF(s) and several other TFs, including those altered by allosteric effects of intracellular metabolites. We were able to recapitulate the previously known metabolite-TF interactions and predict novel interactions with high confidence. Furthermore, we determined that the direct and indirect gene expression have a strong connection with each other when analyzed using the coexpressed- or coregulated-gene approach. Deciphering such regulatory patterns explicitly from the metabolism point of view would be valuable in understanding other unpredicted complex regulation existing in nature.

Reconstructing the transcription regulatory network to optimize resource allocation for robust biosynthesis

An ideal microbial cell factory (MCF) should deliver maximal resources to production, which conflicts with the microbe's native growth-oriented resource allocation strategy and can therefore lead to early termination of the high-yield period. Reallocating resources from growth to production has become a critical factor in constructing robust MCFs. Instead of strengthening specific biosynthetic pathways, emerging endeavors are focused on rearranging the gene regulatory network to fundamentally reprogram the resource allocation pattern. Combining this idea with transcriptional regulation within the hierarchical regulatory network, this review discusses recent engineering strategies targeting the transcription machinery, module networks, regulatory edges, and bottom network layer. This global view will help to construct a production-oriented phenotype that fully harnesses the potential of MCFs.

Fundamental limits on the rate of bacterial growth and their influence on proteomic composition

Despite abundant measurements of bacterial growth rate, cell size, and protein content, we lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we estimate the basic requirements and physical constraints on steady-state growth by considering key processes in cellular physiology across a collection of Escherichia coli proteomic data covering ≈4,000 proteins and 36 growth rates. Our analysis suggests that cells are predominantly tuned for the task of cell doubling across a continuum of growth rates; specific processes do not limit growth rate or dictate cell size. We present a model of proteomic regulation as a function of nutrient supply that reconciles observed interdependences between protein synthesis, cell size, and growth rate and propose that a theoretical inability to parallelize ribosomal synthesis places a firm limit on the achievable growth rate. A record of this paper's transparent peer review process is included in the supplemental information.

Threshold accumulation of a constitutive protein explains E. coli cell-division behavior in nutrient upshifts

Despite a boost of recent progress in dynamic single-cell measurements and analyses in Escherichia coli, we still lack a mechanistic understanding of the determinants of the decision to divide. Specifically, the debate is open regarding the processes linking growth and chromosome replication to division and on the molecular origin of the observed "adder correlations," whereby cells divide, adding roughly a constant volume independent of their initial volume. In order to gain insight into these questions, we interrogate dynamic size-growth behavior of single cells across nutrient upshifts with a high-precision microfluidic device. We find that the division rate changes quickly after nutrients change, much before growth rate goes to a steady state, and in a way that adder correlations are robustly conserved. Comparison of these data to simple mathematical models falsifies proposed mechanisms, where replication-segregation or septum completions are the limiting step for cell division. Instead, we show that the accumulation of a putative constitutively expressed "P-sector divisor" protein explains the behavior during the shift.

Cell Size Is Coordinated with Cell Cycle by Regulating Initiator Protein DnaA in E. coli

Sixty years ago, bacterial cell size was found to be an exponential function of growth rate. Fifty years ago, a more general relationship was proposed, in which cell mass was equal to the initiation mass multiplied by 2 to the power of the ratio of the total time of C and D periods to the doubling time. This relationship has recently been experimentally confirmed by perturbing doubling time, C period, D period, or initiation mass. However, the underlying molecular mechanism remains unclear. Here, we developed a theoretical model for initiator protein DnaA mediating DNA replication initiation in Escherichia coli. We introduced an initiation probability function for competitive binding of DnaA-ATP and DnaA-ADP at oriC. We established a kinetic description of regulatory processes (e.g., expression regulation, titration, inactivation, and reactivation) of DnaA. Cell size as a spatial constraint also participates in the regulation of DnaA. By simulating DnaA kinetics, we obtained a regular DnaA oscillation coordinated with cell cycle and a converged cell size that matches replication initiation frequency to the growth rate. The relationship between the simulated cell size and growth rate, C period, D period, or initiation mass reproduces experimental results. The model also predicts how DnaA number and initiation mass vary with perturbation parameters, comparable with experimental data. The results suggest that 1) when growth rate, C period, or D period changes, the regulation of DnaA determines the invariance of initiation mass; 2) ppGpp inhibition of replication initiation may be important for the growth rate independence of initiation mass because three possible mechanisms therein produce different DnaA dynamics, which is experimentally verifiable; and 3) perturbation of some DnaA regulatory process causes a changing initiation mass or even an abnormal cell cycle. This study may provide clues for concerted control of cell size and cell cycle in synthetic biology.