Carbon catabolite repression correlates with the maintenance of near invariant molecular crowding in proliferating E. coli cells

Nonlethal deleterious mutation-induced stress accelerates bacterial aging

Random mutagenesis, including when it leads to loss of gene function, is a key mechanism enabling microorganisms' long-term adaptation to new environments. However, loss-of-function mutations are often deleterious, triggering, in turn, cellular stress and complex homeostatic stress responses, called "allostasis," to promote cell survival. Here, we characterize the differential impacts of 65 nonlethal, deleterious single-gene deletions on Escherichia coli growth in three different growth environments. Further assessments of select mutants, namely, those bearing single adenosine triphosphate (ATP) synthase subunit deletions, reveal that mutants display reorganized transcriptome profiles that reflect both the environment and the specific gene deletion. We also find that ATP synthase α-subunit deleted (ΔatpA) cells exhibit elevated metabolic rates while having slower growth compared to wild-type (wt) E. coli cells. At the single-cell level, compared to wt cells, individual ΔatpA cells display near normal proliferation profiles but enter a postreplicative state earlier and exhibit a distinct senescence phenotype. These results highlight the complex interplay between genomic diversity, adaptation, and stress response and uncover an "aging cost" to individual bacterial cells for maintaining population-level resilience to environmental and genetic stress; they also suggest potential bacteriostatic antibiotic targets and -as select human genetic diseases display highly similar phenotypes, - a bacterial origin of some human diseases.

Flux balance analysis of metabolic networks for efficient engineering of microbial cell factories

Metabolic engineering principles have long been applied to explore the metabolic networks of complex microbial cell factories under a variety of environmental constraints for effective deployment of the microorganisms in the optimal production of biochemicals like biofuels, polymers, amino acids, recombinant proteins. One of the methodologies used for analyzing microbial metabolic networks is the Flux Balance Analysis (FBA), which employs applications of optimization techniques for forecasting biomass growth and metabolic flux distribution of industrially important products under specified environmental conditions. The in silico flux simulations are instrumental for designing the production-specific microbial cell factories. However, FBA has some inherent limitations. The present review emphasizes how the incorporation of additional kinetic, thermodynamic, expression and regulatory constraints and integration of omics data into the classical FBA platform improve the prediction accuracy of FBA. A programmed comparison of the simulated data with the experimental observations is presented for supporting the claim. The review further accounts for the successful implementation of classical FBA in biotechnological applications and identifies areas in which classical FBA fails to make correct predictions. The analysis of the predictive capabilities of the different FBA strategies presented here is expected to help researchers in finding new avenues in engineering highly efficient microbial metabolic pathways and identify the key metabolic bottlenecks during the process. Based on the appropriate metabolic network design, fermentation engineers will be able to effectively design the bioreactors and optimize large-scale biochemical production through suitable pathway modifications.

Understanding and mathematical modelling of cellular resource allocation in microorganisms: a comparative synthesis

BACKGROUND

The rising consensus that the cell can dynamically allocate its resources provides an interesting angle for discovering the governing principles of cell growth and metabolism. Extensive efforts have been made in the past decade to elucidate the relationship between resource allocation and phenotypic patterns of microorganisms. Despite these exciting developments, there is still a lack of explicit comparison between potentially competing propositions and a lack of synthesis of inter-related proposals and findings.

RESULTS

In this work, we have reviewed resource allocation-derived principles, hypotheses and mathematical models to recapitulate important achievements in this area. In particular, the emergence of resource allocation phenomena is deciphered by the putative tug of war between the cellular objectives, demands and the supply capability. Competing hypotheses for explaining the most-studied phenomenon arising from resource allocation, i.e. the overflow metabolism, have been re-examined towards uncovering the potential physiological root cause. The possible link between proteome fractions and the partition of the ribosomal machinery has been analysed through mathematical derivations. Finally, open questions are highlighted and an outlook on the practical applications is provided. It is the authors' intention that this review contributes to a clearer understanding of the role of resource allocation in resolving bacterial growth strategies, one of the central questions in microbiology.

CONCLUSIONS

We have shown the importance of resource allocation in understanding various aspects of cellular systems. Several important questions such as the physiological root cause of overflow metabolism and the correct interpretation of 'protein costs' are shown to remain open. As the understanding of the mechanisms and utility of resource application in cellular systems further develops, we anticipate that mathematical modelling tools incorporating resource allocation will facilitate the circuit-host design in synthetic biology.

A physicochemical perspective of aging from single-cell analysis of pH, macromolecular and organellar crowding in yeast

Cellular aging is a multifactorial process that is characterized by a decline in homeostatic capacity, best described at the molecular level. Physicochemical properties such as pH and macromolecular crowding are essential to all molecular processes in cells and require maintenance. Whether a drift in physicochemical properties contributes to the overall decline of homeostasis in aging is not known. Here, we show that the cytosol of yeast cells acidifies modestly in early aging and sharply after senescence. Using a macromolecular crowding sensor optimized for long-term FRET measurements, we show that crowding is rather stable and that the stability of crowding is a stronger predictor for lifespan than the absolute crowding levels. Additionally, in aged cells, we observe drastic changes in organellar volume, leading to crowding on the micrometer scale, which we term organellar crowding. Our measurements provide an initial framework of physicochemical parameters of replicatively aged yeast cells.

Mathematical modelling of microbes: metabolism, gene expression and growth

The growth of microorganisms involves the conversion of nutrients in the environment into biomass, mostly proteins and other macromolecules. This conversion is accomplished by networks of biochemical reactions cutting across cellular functions, such as metabolism, gene expression, transport and signalling. Mathematical modelling is a powerful tool for gaining an understanding of the functioning of this large and complex system and the role played by individual constituents and mechanisms. This requires models of microbial growth that provide an integrated view of the reaction networks and bridge the scale from individual reactions to the growth of a population. In this review, we derive a general framework for the kinetic modelling of microbial growth from basic hypotheses about the underlying reaction systems. Moreover, we show that several families of approximate models presented in the literature, notably flux balance models and coarse-grained whole-cell models, can be derived with the help of additional simplifying hypotheses. This perspective clearly brings out how apparently quite different modelling approaches are related on a deeper level, and suggests directions for further research.

Simultaneous saccharification and fermentation of hemicellulose to butanol by a non-sporulating Clostridium species

Production of lignocellulosic butanol has drawn increasing attention. However, currently few microorganisms can produce biofuels, particularly butanol, from lignocellulosic biomass via simultaneous saccharification and fermentation. Here we report discovery of a wild-type, mesophilic Clostridium sp. strain MF28 that ferments xylan to produce butanol (up to 3.2g/L) without the addition of saccharolytic enzymes and without any chemical pretreatments. Application of selective pressure from 2-deoxy-d-glucose facilitated isolation of strain MF28, which exhibits inactivation of genes (gid and ccp genes) responsible for carbon catabolite repression, thus allowing strain MF28 to simultaneously ferment a combination of glucose (30g/L), xylose (15g/L), and arabinose (15g/L) to produce 11.9g/L of butanol. Strain MF28 possesses several unique features: (i) non-sporulating, (ii) no acetone/ethanol, (iii) complete hemicellulose-binding enzymatic domain, and (iv) absence of carbon catabolite repression. These unique characteristics demonstrate the industrial potential of strain MF28 for cost-effective biofuel generation from lignocellulosic biomass.

Macromolecular crowding explains overflow metabolism in cells

Overflow metabolism is a metabolic phenotype of cells characterized by mixed oxidative phosphorylation (OxPhos) and fermentative glycolysis in the presence of oxygen. Recently, it was proposed that a combination of a protein allocation constraint and a higher proteome fraction cost of energy generation by OxPhos relative to fermentation form the basis of overflow metabolism in the bacterium, Escherichia coli. However, we argue that the existence of a maximum or optimal macromolecular density is another essential requirement. Here we re-evaluate our previous theory of overflow metabolism based on molecular crowding following the proteomic fractions formulation. We show that molecular crowding is a key factor in explaining the switch from OxPhos to overflow metabolism.

Metabolic Trade-offs in Yeast are Caused by F1F0-ATP synthase

Intermediary metabolism provides living cells with free energy and precursor metabolites required for synthesizing proteins, lipids, RNA and other cellular constituents, and it is highly conserved among living species. Only a fraction of cellular protein can, however, be allocated to enzymes of intermediary metabolism and consequently metabolic trade-offs may take place. One such trade-off, aerobic fermentation, occurs in both yeast (the Crabtree effect) and cancer cells (the Warburg effect) and has been a scientific challenge for decades. Here we show, using flux balance analysis combined with in vitro measured enzyme specific activities, that fermentation is more catalytically efficient than respiration, i.e. it produces more ATP per protein mass. And that the switch to fermentation at high growth rates therefore is a consequence of a high ATP production rate, provided by a limited pool of enzymes. The catalytic efficiency is also higher for cells grown on glucose compared to galactose and ethanol, which may explain the observed differences in their growth rates. The enzyme F1F0-ATP synthase (Complex V) was found to have flux control over respiration in the model, and since it is evolutionary conserved, we expect the trade-off to occur in organisms from all kingdoms of life.

Carbon Catabolite Repression and the Related Genes of ccpA, ptsH and hprK in Thermoanaerobacterium aotearoense

The strictly anaerobic, Gram-positive bacterium, Thermoanaerobacterium aotearoense SCUT27, is capable of producing ethanol, hydrogen and lactic acid by directly fermenting glucan, xylan and various lignocellulosically derived sugars. By using non-metabolizable and metabolizable sugars as substrates, we found that cellobiose, galactose, arabinose and starch utilization was strongly inhibited by the existence of 2-deoxyglucose (2-DG). However, the xylose and mannose consumptions were not markedly affected by 2-DG at the concentration of one-tenth of the metabolizable sugar. Accordingly, T. aotearoense SCUT27 could consume xylose and mannose in the presence of glucose. The carbon catabolite repression (CCR) related genes, ccpA, ptsH and hprK were confirmed to exist in T. aotearoense SCUT27 through gene cloning and protein characterization. The highly purified Histidine-containing Protein (HPr) could be specifically phosphorylated at Serine 46 by HPr kinase/phosphatase (HPrK/P) with no need to add fructose-1,6-bisphosphate (FBP) or glucose-6-phosphate (Glc-6-P) in the reaction mixture. The specific protein-interaction of catabolite control protein A (CcpA) and phosphorylated HPr was proved via affinity chromatography in the absence of formaldehyde. The equilibrium binding constant (K_D) of CcpA and HPrSerP was determined as 2.22 ± 0.36 nM by surface plasmon resonance (SPR) analysis, indicating the high affinity between these two proteins.

Acetate Exposure Determines the Diauxic Behavior of Escherichia coli during the Glucose-Acetate Transition

Growth of Escherichia coli on glucose in batch culture is accompanied by the excretion of acetate, which is consumed by the cells when glucose is exhausted. This glucose-acetate transition is classically described as a diauxie (two successive growth stages). Here, we investigated the physiological and metabolic properties of cells after glucose exhaustion through the analysis of growth parameters and gene expression. We found that E. coli cells grown on glucose in batch culture produce acetate and consume it after glucose exhaustion but do not grow on acetate. Acetate is catabolized, but key anabolic genes--such as the genes encoding enzymes of the glyoxylate shunt--are not upregulated, hence preventing growth. Both the induction of the latter anabolic genes and growth were observed only after prolonged exposure to low concentrations of acetate and could be accelerated by high acetate concentrations. We postulate that such decoupling between acetate catabolism and acetate anabolism might be an advantage for the survival of E. coli in the ever-changing environment of the intestine.

IMPORTANCE

The glucose-acetate transition is a valuable experimental model for comprehensive investigations of metabolic adaptation and a current paradigm for developing modeling approaches in systems microbiology. Yet, the work reported in our paper demonstrates that the metabolic behavior of Escherichia coli during the glucose-acetate transition is much more complex than what has been reported so far. A decoupling between acetate catabolism and acetate anabolism was observed after glucose exhaustion, which has not been reported previously. This phenomenon could represent a strategy for optimal utilization of carbon resources during colonization and persistence of E. coli in the gut and is also of significant interest for biotechnological applications.

Spatially-resolved metabolic cooperativity within dense bacterial colonies

Background

The exchange of metabolites and the reprogramming of metabolism in response to shifting microenvironmental conditions can drive subpopulations of cells within colonies toward divergent behaviors. Understanding the interactions of these subpopulations—their potential for competition as well as cooperation—requires both a metabolic model capable of accounting for a wide range of environmental conditions, and a detailed dynamic description of the cells’ shared extracellular space.

Results

Here we show that a cell’s position within an in silicoEscherichia coli colony grown on glucose minimal agar can drastically affect its metabolism: “pioneer” cells at the outer edge engage in rapid growth that expands the colony, while dormant cells in the interior separate two spatially distinct subpopulations linked by a cooperative form of acetate crossfeeding that has so far gone unnoticed. Our hybrid simulation technique integrates 3D reaction-diffusion modeling with genome-scale flux balance analysis (FBA) to describe the position-dependent metabolism and growth of cells within a colony. Our results are supported by imaging experiments involving strains of fluorescently-labeled E. coli. The spatial patterns of fluorescence within these experimental colonies identify cells with upregulated genes associated with acetate crossfeeding and are in excellent agreement with the predictions. Furthermore, the height-to-width ratios of both the experimental and simulated colonies are in good agreement over a growth period of 48 hours.

Conclusions

Our modeling paradigm can accurately reproduce a number of known features of E. coli colony growth, as well as predict a novel one that had until now gone unrecognized. The acetate crossfeeding we see has a direct analogue in a form of lactate crossfeeding observed in certain forms of cancer, and we anticipate future application of our methodology to models of tissues and tumors.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0155-1) contains supplementary material, which is available to authorized users.