Cellular perception of growth rate and the mechanistic origin of bacterial growth law.

Many cellular activities in bacteria are organized according to their growth rate. The notion that ppGpp measures the cell's growth rate is well accepted in the field of bacterial physiology. However, despite decades of interrogation and the identification of multiple molecular interactions that connects ppGpp to some aspects of cell growth, we lack a system-level, quantitative picture of how this alleged "measurement" is performed. Through quantitative experiments, we show that the ppGpp pool responds inversely to the rate of translational elongation in Escherichia coli. Together with its roles in inhibiting ribosome biogenesis and activity, ppGpp closes a key regulatory circuit that enables the cell to perceive and control the rate of its growth across conditions. The celebrated linear growth law relating the ribosome content and growth rate emerges as a consequence of keeping a supply of ribosome reserves while maintaining elongation rate in slow growth conditions. Further analysis suggests the elongation rate itself is detected by sensing the ratio of dwelling and translocating ribosomes, a strategy employed to collapse the complex, high-dimensional dynamics of the molecular processes underlying cell growth to perceive the physiological state of the whole.

Coordination of gene expression with cell size enables Escherichia coli to efficiently maintain motility across conditions.

To swim and navigate, motile bacteria synthesize a complex motility machinery involving flagella, motors, and a sensory system. A myriad of studies has elucidated the molecular processes involved, but less is known about the coordination of motility expression with cellular physiology: In Escherichia coli, motility genes are strongly up-regulated in nutrient-poor conditions compared to nutrient-replete conditions; yet a quantitative link to cellular motility has not been developed. Here, we systematically investigated gene expression, swimming behavior, cell growth, and available proteomics data across a broad spectrum of exponential growth conditions. Our results suggest that cells up-regulate the expression of motility genes at slow growth to compensate for reduction in cell size, such that the number of flagella per cell is maintained across conditions. The observed four or five flagella per cell is the minimum number needed to keep the majority of cells motile. This simple regulatory objective allows E. coli cells to remain motile across a broad range of growth conditions, while keeping the biosynthetic and energetic demands to establish and drive the motility machinery at the minimum needed. Given the strong reduction in flagella synthesis resulting from cell size increases at fast growth, our findings also provide a different physiological perspective on bacterial cell size control: A larger cell size at fast growth is an efficient strategy to increase the allocation of cellular resources to the synthesis of those proteins required for biomass synthesis and growth, while maintaining processes such as motility that are only needed on a per-cell basis.

Growth rate-dependent global effects on gene expression in bacteria.

Bacterial gene expression depends not only on specific regulatory mechanisms, but also on bacterial growth, because important global parameters such as the abundance of RNA polymerases and ribosomes are all growth-rate dependent. Understanding of these global effects is necessary for a quantitative understanding of gene regulation and for the design of synthetic genetic circuits. We find that the observed growth-rate dependence of constitutive gene expression can be explained by a simple model using the measured growth-rate dependence of the relevant cellular parameters. More complex growth dependencies for genetic circuits involving activators, repressors, and feedback control were analyzed and verified experimentally with synthetic circuits. Additional results suggest a feedback mechanism mediated by general growth-dependent effects that does not require explicit gene regulation if the expressed protein affects cell growth. This mechanism can lead to growth bistability and promote the acquisition of important physiological functions such as antibiotic resistance and tolerance (persistence).

Comprehensive Characterization of fucAO Operon Activation in Escherichia coli.

Wildtype Escherichia coli cells cannot grow on L-1,2-propanediol, as the fucAO operon within the fucose (fuc) regulon is thought to be silent in the absence of L-fucose. Little information is available concerning the transcriptional regulation of this operon. Here, we first confirm that fucAO operon expression is highly inducible by fucose and is primarily attributable to the upstream operon promoter, while the fucO promoter within the 3'-end of fucA is weak and uninducible. Using 5'RACE, we identify the actual transcriptional start site (TSS) of the main fucAO operon promoter, refuting the originally proposed TSS. Several lines of evidence are provided showing that the fucAO locus is within a transcriptionally repressed region on the chromosome. Operon activation is dependent on FucR and Crp but not SrsR. Two Crp-cAMP binding sites previously found in the regulatory region are validated, where the upstream site plays a more critical role than the downstream site in operon activation. Furthermore, two FucR binding sites are identified, where the downstream site near the first Crp site is more important than the upstream site. Operon transcription relies on Crp-cAMP to a greater degree than on FucR. Our data strongly suggest that FucR mainly functions to facilitate the binding of Crp to its upstream site, which in turn activates the fucAO promoter by efficiently recruiting RNA polymerase.

From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions.

Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric workflow based on data-independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in Escherichia coli for > 2,000 proteins over > 60 growth conditions, including nutrient limitations, non-metabolic stresses, and non-planktonic states. The resulting high-quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low-abundant proteins under various metabolic limitations, the non-specificity of catabolic enzymes upregulated under carbon limitation, the lack of large-scale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain-dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi-omics studies of gene regulation and metabolic control in E. coli.

Insertion Sequence (IS) Element-Mediated Activating Mutations of the Cryptic Aromatic ß-Glucoside Utilization (BglGFB) Operon Are Promoted by the Anti-Terminator Protein (BglG) in Escherichia coli.

The cryptic ß-glucoside GFB (bglGFB) operon in Escherichia coli (E. coli) can be activated by mutations arising under starvation conditions in the presence of an aromatic ß-glucoside. This may involve the insertion of an insertion sequence (IS) element into a "stress-induced DNA duplex destabilization" (SIDD) region upstream of the operon promoter, although other types of mutations can also activate the bgl operon. Here, we show that increased expression of the bglG gene, encoding a well-characterized transcriptional antiterminator, dramatically increases the frequency of both IS-mediated and IS-independent Bgl+ mutations occurring on salicin- and arbutin-containing agar plates. Both mutation rates increased with increasing levels of bglG expression but IS-mediated mutations were more prevalent at lower BglG levels. Mutations depended on the presence of both BglG and an aromatic ß-glucoside, and bglG expression did not influence IS insertion in other IS-activated operons tested. The N-terminal mRNA-binding domain of BglG was essential for mutational activation, and alteration of BglG's binding site in the mRNA nearly abolished Bgl+ mutant appearances. Increased bglG expression promoted residual bgl operon expression in parallel with the increases in mutation rates. Possible mechanisms are proposed explaining how BglG enhances the frequencies of bgl operon activating mutations.

Effects of Global and Specific DNA-Binding Proteins on Transcriptional Regulation of the E. coli bgl Operon.

Using reporter gene (lacZ) transcriptional fusions, we examined the transcriptional dependencies of the bgl promoter (Pbgl) and the entire operon regulatory region (Pbgl-bglG) on eight transcription factors as well as the inducer, salicin, and an IS5 insertion upstream of Pbgl. Crp-cAMP is the primary activator of both Pbgl and the bgl operon, while H-NS is a strong dominant operon repressor but only a weak repressor of Pbgl. H-NS may exert its repressive effect by looping the DNA at two binding sites. StpA is a relatively weak repressor in the absence of H-NS, while Fis also has a weak repressive effect. Salicin has no effect on Pbgl activity but causes a 30-fold induction of bgl operon expression. Induction depends on the activity of the BglF transporter/kinase. IS5 insertion has only a moderate effect on Pbgl but causes a much greater activation of the bgl operon expression by preventing the full repressive effects of H-NS and StpA. While several other transcription factors (BglJ, RcsB, and LeuO) have been reported to influence bgl operon transcription when overexpressed, they had little or no effect when present at wild type levels. These results indicate the important transcriptional regulatory mechanisms operative on the bgl operon in E. coli.

Overflow metabolism in Escherichia coli results from efficient proteome allocation.

Overflow metabolism refers to the seemingly wasteful strategy in which cells use fermentation instead of the more efficient respiration to generate energy, despite the availability of oxygen. Known as the Warburg effect in the context of cancer growth, this phenomenon occurs ubiquitously for fast-growing cells, including bacteria, fungi and mammalian cells, but its origin has remained unclear despite decades of research. Here we study metabolic overflow in Escherichia coli, and show that it is a global physiological response used to cope with changing proteomic demands of energy biogenesis and biomass synthesis under different growth conditions. A simple model of proteomic resource allocation can quantitatively account for all of the observed behaviours, and accurately predict responses to new perturbations. The key hypothesis of the model, that the proteome cost of energy biogenesis by respiration exceeds that by fermentation, is quantitatively confirmed by direct measurement of protein abundances via quantitative mass spectrometry.

Coordination of bacterial proteome with metabolism by cyclic AMP signalling.

The cyclic AMP (cAMP)-dependent catabolite repression effect in Escherichia coli is among the most intensely studied regulatory processes in biology. However, the physiological function(s) of cAMP signalling and its molecular triggers remain elusive. Here we use a quantitative physiological approach to show that cAMP signalling tightly coordinates the expression of catabolic proteins with biosynthetic and ribosomal proteins, in accordance with the cellular metabolic needs during exponential growth. The expression of carbon catabolic genes increased linearly with decreasing growth rates upon limitation of carbon influx, but decreased linearly with decreasing growth rate upon limitation of nitrogen or sulphur influx. In contrast, the expression of biosynthetic genes showed the opposite linear growth-rate dependence as the catabolic genes. A coarse-grained mathematical model provides a quantitative framework for understanding and predicting gene expression responses to catabolic and anabolic limitations. A scheme of integral feedback control featuring the inhibition of cAMP signalling by metabolic precursors is proposed and validated. These results reveal a key physiological role of cAMP-dependent catabolite repression: to ensure that proteomic resources are spent on distinct metabolic sectors as needed in different nutrient environments. Our findings underscore the power of quantitative physiology in unravelling the underlying functions of complex molecular signalling networks.