Global transcriptional regulators coordinate complex genetic interactions that bestow better adaptability for an organism against external and internal perturbations. These transcriptional regulators are known to control an enormous array of genes with diverse functionalities. However, regulator-driven molecular mechanisms that underpin precisely tuned translational and metabolic processes conducive for rapid exponential growth remain obscure. Here, we comprehensively reveal the fundamental role of global transcriptional regulators FNR, ArcA, and IHF in sustaining translational and metabolic efficiency under glucose fermentative conditions in Escherichia coli. By integrating high-throughput gene expression profiles and absolute intracellular metabolite concentrations, we illustrate that these regulators are crucial in maintaining nitrogen homeostasis, govern expression of otherwise unnecessary or hedging genes, and exert tight control on metabolic bottleneck steps. Furthermore, we characterize changes in expression and activity profiles of other coregulators associated with these dysregulated metabolic pathways, determining the regulatory interactions within the transcriptional regulatory network. Such systematic findings emphasize their importance in optimizing the proteome allocation toward metabolic enzymes as well as ribosomes, facilitating condition-specific phenotypic outcomes. Consequentially, we reveal that disruption of this inherent trade-off between ribosome and metabolic proteome economy due to the loss of regulators resulted in lowered growth rates. Moreover, our findings reinforce that the accumulations of intracellular metabolites in the event of proteome repartitions negatively affects the glucose uptake. Overall, by extending the three-partition proteome allocation theory concordant with multi-omics measurements, we elucidate the physiological consequences of loss of global regulators on central carbon metabolism restraining the organism to attain maximal biomass synthesis. IMPORTANCE Cellular proteome allocation in response to environmental or internal perturbations governs their eventual phenotypic outcome. This entails striking an effective balance between amino acid biosynthesis by metabolic proteins and its consumption by ribosomes. However, the global transcriptional regulator-driven molecular mechanisms that underpin their coordination remains unexplored. Here, we emphasize that global transcriptional regulators, known to control expression of a myriad of genes, are fundamental for precisely tuning the translational and metabolic efficiencies that define the growth optimality. Towards this, we systematically characterized the single deletion effect of FNR, ArcA, and IHF regulators of Escherichia coli on exponential growth under anaerobic glucose fermentative conditions. Their absence disrupts the stringency of proteome allocation, which manifests as impairment in key metabolic processes and an accumulation of intracellular metabolites. Furthermore, by incorporating an extension to the empirical growth laws, we quantitatively demonstrate the general design principles underlying the existence of these regulators in E. coli.

Conventional neural-network training algorithms often get stuck in local minima. To find the global optimum, training is conventionally repeated with ten, or so, random starting values for the weights. Here we develop an analytical procedure to determine how many times a neural network needs to be trained, with random starting weights, to ensure that the best of those is within a desirable lower percentile of all possible trainings, with a certain level of confidence. The theoretical developments are validated by experimental results. While applied to neural-network training, the method is generally applicable to nonlinear optimization.

Evolution facilitates emergence of fitter phenotypes by efficient allocation of cellular resources in conjunction with beneficial mutations. However, system-wide pleiotropic effects that redress the perturbations to the apex node of the transcriptional regulatory networks remain unclear. Here, we elucidate that absence of global transcriptional regulator CRP in Escherichia coli results in alterations in key metabolic pathways under glucose respiratory conditions, favouring stress- or hedging-related functions over growth-enhancing functions. Further, we disentangle the growth-mediated effects from the CRP regulation-specific effects on these metabolic pathways. We quantitatively illustrate that the loss of CRP perturbs proteome efficiency, as evident from metabolic as well as ribosomal proteome fractions, that corroborated with intracellular metabolite profiles. To address how E. coli copes with such systemic defect, we evolved Δcrp mutant in the presence of glucose. Besides acquiring mutations in the promoter of glucose transporter ptsG , the evolved populations recovered the metabolic pathways to their pre-perturbed state coupled with metabolite re-adjustments, which altogether enabled increased growth. By contrast to Δcrp mutant, the evolved strains remodelled their proteome efficiency towards biomass synthesis, albeit at the expense of carbon efficiency. Overall, we comprehensively illustrate the genetic and metabolic basis of pleiotropic effects, fundamental for understanding the growth physiology.

Bacterial gene expression is governed by two synergistic mechanismsgrowth-rate dependent global machinery (e.g. ribosomes, RNA polymerase, metabolites and cofactors) and transcription factors that work together for optimal growth. However, in presence of glucose, coordination of global transcriptional regulator cAMP-CRP with such physiological resources, remain elusive.Here, we reveal that the deletion of CRP results in metabolic dysregulation with significant perturbation in protein biosynthesis machinery coupled to impaired glucose import.Additionally, we quantitatively demonstrate that the loss of CRP unbalances proteome allocation, favouring stress or hedging related functions over growth-enhancing functions. To address how Escherichia coli can cope up with such a system-wide upset, we adaptively evolved Δcrp mutant in the presence of glucose. We explicitly show that adaptation to loss of CRP frequently occurs via mutations in the ptsG promoter. This causes higher glucose uptake, resulting in the restoration of the levels of the protein biosynthesis machinery and metabolic rewiring of ATP towards synthesis of costly amino acids along with reduction in unnecessary cAMP synthesis. Thus we elucidate the molecular events underlying growth optimality of the organism, driven by CRP.Here, using a multi-omics (genomics, transcriptomics, metabolomics and phenomics) approach, we illustrate the evolutionary importance of CRP in glucose minimal media conditions. First, we elucidate that evolution redress the loss of CRP by repeatedly accumulating mutations in the intergenic region of the ptsG gene, enabling increased glucose uptake rates and fitness benefit for the organism. Next, we unravel how such adaptation bring about system-wide changes by modulating the global gene expression states and the levels of several key intracellular metabolites that coordinate protein biosynthesis machinery and metabolism. Finally, restoration mechanism as a result of evolution involved fine tuning of proteome allocation in favour of growth and away from stress or hedging functions. Further, using a genome-scale model we were able to quantitatively detail the energetic inefficiencies of the evolved populations which explained their inability to grow optimally as wild-type. Overall, the evolution of Δcrp strain suggests an underlying paradigm which delineates the inherent constraints of genetic and metabolic networks in E. coli.An E. coli K-12 MG1655 (CGSC#6300), was used as the parent strain in this study. We constructed Δcrp knockout in this genetic background by -Red mediated recombination (21), using plasmids pKD46, pKD13 and pCP20. The generation of the knockout strain was confirmed by PCR with custom made oligo-nucleotides against the genomic DNA followed by Sanger sequencing. Generation of Δfis, Δmlc, ΔfisΔcrp and ΔmlcΔcrp strains for growth studies were also generated using the same procedure. Physiological CharacterizationFor transcriptome, metabolome and phenotype characterizations, experiments were performed in 500 mL bioreacto...

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