Effect of Slow Growth on Metabolism of Escherichia coli, as Revealed by Global Metabolite Pool (“Metabolome”) Analysis

Escherichia coli growing on glucose in minimal medium controls its metabolite pools in response to environmental conditions. The extent of pool changes was followed through two-dimensional thin-layer chromatography of all ¹⁴C-glucose labelled compounds extracted from bacteria. The patterns of metabolites and spot intensities detected by phosphorimaging were found to reproducibly differ depending on culture conditions. Clear trends were apparent in the pool sizes of several of the 70 most abundant metabolites extracted from bacteria growing in glucose-limited chemostats at different growth rates. The pools of glutamate, aspartate, trehalose, and adenosine as well as UDP-sugars and putrescine changed markedly. The data on pools observed by two-dimensional thin-layer chromatography were confirmed for amino acids by independent analysis. Other unidentified metabolites also displayed different spot intensities under various conditions, with four trend patterns depending on growth rate. As RpoS controls a number of metabolic genes in response to nutrient limitation, an rpoS mutant was also analyzed for metabolite pools. The mutant had altered metabolite profiles, but only some of the changes at slow growth rates were ascribable to the known control of metabolic genes by RpoS. These results indicate that total metabolite pool (“metabolome”) analysis offers a means of revealing novel aspects of cellular metabolism and global regulation.     

Selection for Cell Yield Does Not Reduce Overflow Metabolism in Escherichia coli

Overflow metabolism is ubiquitous in nature, and it is often considered inefficient because it leads to a relatively low biomass yield per consumed carbon. This metabolic strategy has been described as advantageous because it supports high growth rates during nutrient competition.Here, we experimentally evolved bacteria without nutrient competition by repeatedly growing and mixing millions of parallel batch cultures of Escherichia coli. Each culture originated from a water-in-oil emulsion droplet seeded with a single cell. Unexpectedly we found that overflow metabolism (acetate production) did not change. Instead, the numerical cell yield during the consumption of the accumulated acetate increased as a consequence of a reduction in cell size. Our experiments and a mathematical model show that fast growth and overflow metabolism, followed by the consumption of the overflow metabolite, can lead to a higher numerical cell yield and therefore a higher fitness compared with full respiration of the substrate. This provides an evolutionary scenario where overflow metabolism can be favorable even in the absence of nutrient competition.     

Glycolysis/gluconeogenesis specialization in microbes is driven by biochemical constraints of flux sensing

Central carbon metabolism is highly conserved across microbial species, but can catalyze very different pathways depending on the organism and their ecological niche. Here, we study the dynamic reorganization of central metabolism after switches between the two major opposing pathway configurations of central carbon metabolism, glycolysis, and gluconeogenesis in Escherichia coli, Pseudomonas aeruginosa, and Pseudomonas putida. We combined growth dynamics and dynamic changes in intracellular metabolite levels with a coarse‐grained model that integrates fluxes, regulation, protein synthesis, and growth and uncovered fundamental limitations of the regulatory network: After nutrient shifts, metabolite concentrations collapse to their equilibrium, rendering the cell unable to sense which direction the flux is supposed to flow through the metabolic network. The cell can partially alleviate this by picking a preferred direction of regulation at the expense of increasing lag times in the opposite direction. Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. These three trade‐offs can explain why microorganisms specialize for either glycolytic or gluconeogenic substrates and can help elucidate the complex growth patterns exhibited by different microbial species.     

Adaptive laboratory evolution of microbial co‐cultures for improved metabolite secretion

Adaptive laboratory evolution has proven highly effective for obtaining microorganisms with enhanced capabilities. Yet, this method is inherently restricted to the traits that are positively linked to cell fitness, such as nutrient utilization. Here, we introduce coevolution of obligatory mutualistic communities for improving secretion of fitness‐costly metabolites through natural selection. In this strategy, metabolic cross‐feeding connects secretion of the target metabolite, despite its cost to the secretor, to the survival and proliferation of the entire community. We thus co‐evolved wild‐type lactic acid bacteria and engineered auxotrophic Saccharomyces cerevisiae in a synthetic growth medium leading to bacterial isolates with enhanced secretion of two B‐group vitamins, viz., riboflavin and folate. The increased production was specific to the targeted vitamin, and evident also in milk, a more complex nutrient environment that naturally contains vitamins. Genomic, proteomic and metabolomic analyses of the evolved lactic acid bacteria, in combination with flux balance analysis, showed altered metabolic regulation towards increased supply of the vitamin precursors. Together, our findings demonstrate how microbial metabolism adapts to mutualistic lifestyle through enhanced metabolite exchange.     

Effect of overall feedback inhibition in unbranched biosynthetic pathways

We have determined the effects of control by overall feedback inhibition on the systemic behavior of unbranched metabolic pathways with an arbitrary pattern of other feedback inhibitions by using a recently developed numerical generalization of Mathematically Controlled Comparisons, a method for comparing the function of alternative molecular designs. This method allows the rigorous determination of the changes in systemic properties that can be exclusively attributed to overall feedback inhibition. Analytical results show that the unbranched pathway can achieve the same steady-state flux, concentrations, and logarithmic gains with respect to changes in substrate, with or without overall feedback inhibition. The analytical approach also shows that control by overall feedback inhibition amplifies the regulation of flux by the demand for end product while attenuating the sensitivity of the concentrations to the same demand. This approach does not provide a clear answer regarding the effect of overall feedback inhibition on the robustness, stability, and transient time of the pathway. However, the generalized numerical method we have used does clarify the answers to these questions. On average, an unbranched pathway with control by overall feedback inhibition is less sensitive to perturbations in the values of the parameters that define the system. The difference in robustness can range from a few percent to fifty percent or more, depending on the length of the pathway and on the metabolite one considers. On average, overall feedback inhibition decreases the stability margins by a minimal amount (typically less than 5%). Finally, and again on average, stable systems with overall feedback inhibition respond faster to fluctuations in the metabolite concentrations. Taken together, these results show that control by overall feedback inhibition confers several functional advantages upon unbranched pathways. These advantages provide a rationale for the prevalence of this control mechanism in unbranched metabolic pathways in vivo.     

Stress eating and tuning out: Cancer cells re-wire metabolism to counter stress

Abstract

Cancer cells reprogram metabolism to maintain rapid proliferation under often stressful conditions. Glycolysis and glutaminolysis are two central pathways that fuel cancer metabolism. Allosteric regulation and metabolite driven post-translational modifications of key metabolic enzymes allow cancer cells glycolysis and glutaminolysis to respond to changes in nutrient availability and the tumor microenvironment. While increased aerobic glycolysis (the Warburg effect) has been a noted part of cancer metabolism for over 80 years, recent work has shown that the elevated levels of glycolytic intermediates are critical to cancer growth and metabolism due to their ability to feed into the anabolic pathways branching off glycolysis such as the pentose phosphate pathway and serine biosynthesis pathway. The key glycolytic enzymes phosphofructokinase-1 (PFK1), pyruvate kinase (PKM2) and phosphoglycerate mutase 1 (PGAM1) are regulated by upstream and downstream metabolites to balance glycolytic flux with flux through anabolic pathways. Glutamine regulation is tightly controlled by metabolic intermediates that allosterically inhibit and activate glutamate dehydrogenase, which fuels the tricarboxylic acid cycle by converting glutamine derived glutamate to α-ketoglutarate. The elucidation of these key allosteric regulatory hubs in cancer metabolism will be essential for understanding and predicting how cancer cells will respond to drugs that target metabolism. Additionally, identification of the structures involved in allosteric regulation will inform the design of anti-metabolism drugs which bypass the off-target effects of substrate mimics. Hence, this review aims to provide an overview of allosteric control of glycolysis and glutaminolysis.     

Generation of an atlas for commodity chemical production in Escherichia coli and a novel pathway prediction algorithm,GEM-Path

The production of 75% of the current drug molecules and 35% of all chemicals could be achieved through bioprocessing (Arundel and Sawaya, 2009). To accelerate the transition from a petroleum-based chemical industry to a sustainable bio-based industry, systems metabolic engineering has emerged to computationally design metabolic pathways for chemical production. Although algorithms able to provide specific metabolic interventions and heterologous production pathways are available, a systematic analysis for all possible production routes to commodity chemicals in Escherichia coli is lacking. Furthermore, a pathway prediction algorithm that combines direct integration of genome-scale models at each step of the search to reduce the search space does not exist. Previous work (Feist et al., 2010) performed a model-driven evaluation of the growth-coupled production potential for E. coli to produce multiple native compounds from different feedstocks. In this study, we extended this analysis for non-native compounds by using an integrated approach through heterologous pathway integration and growth-coupled metabolite production design. In addition to integration with genome-scale model integration, the GEM-Path algorithm developed in this work also contains a novel approach to address reaction promiscuity. In total, 245 unique synthetic pathways for 20 large volume compounds were predicted. Host metabolism with these synthetic pathways was then analyzed for feasible growth-coupled production and designs could be identified for 1271 of the 6615 conditions evaluated. This study characterizes the potential for E. coli to produce commodity chemicals, and outlines a generic strain design workflow to design production strains.     

Regulation of ribulose-1,5-bisphosphate carboxylase activity in response to diurnal changes in irradiance

The regulation of ribulose-1,5-bisphosphate (RuBP) carboxylase (Rubisco) activity and metabolite pool sizes in response to natural diurnal changes in photon flux density (PFD) was examined in three species (Phaseolus vulgaris, Beta vulgaris, and Spinacia oleracea) known to differ in the mechanisms used for this regulation. Diurnal regulation of Rubisco activity in P. vulgaris was primarily the result of metabolism of the naturally occurring tight-binding inhibitor of Rubisco, 2-carboxyarabinitol 1-phosphate (CA1P). In B. vulgaris, the regulation of Rubisco activity was the result of both changes in activation state and CA1P metabolism. In S. oleracea, Rubisco activity was regulated by a combination of changes in activation state and the binding/release of another tight binding inhibitor, probably RuBP. Despite these different mechanisms for the light regulation of Rubisco activity, the relationship between the in vivo activity of Rubisco and the PFD was the same for all three species. Rates of CA1P metabolism were thus sufficient to allow this mechanism to participate in the diurnal regulation of Rubisco activity as PFD changed at its normal rate. Furthermore, under natural conditions this regulatory mechanism was found to be important in controlling Rubisco activity over approximately the same range of PFD as did changes in activation state of the enzyme. Finally, this regulation of Rubisco activity resulted in relatively similar and saturating RuBP pool sizes for photosynthesis at all but the lowest PFD values in all three species.     

Cancer metabolism: current perspectives and future directions

Cellular metabolism influences life and death decisions. An emerging theme in cancer biology is that metabolic regulation is intricately linked to cancer progression. In part, this is due to the fact that proliferation is tightly regulated by availability of nutrients. Mitogenic signals promote nutrient uptake and synthesis of DNA, RNA, proteins and lipids. Therefore, it seems straight-forward that oncogenes, that often promote proliferation, also promote metabolic changes. In this review we summarize our current understanding of how ‘metabolic transformation'' is linked to oncogenic transformation, and why inhibition of metabolism may prove a cancer′s ‘Achilles'' heel''. On one hand, mutation of metabolic enzymes and metabolic stress sensors confers synthetic lethality with inhibitors of metabolism. On the other hand, hyperactivation of oncogenic pathways makes tumors more susceptible to metabolic inhibition. Conversely, an adequate nutrient supply and active metabolism regulates Bcl-2 family proteins and inhibits susceptibility to apoptosis. Here, we provide an overview of the metabolic pathways that represent anti-cancer targets and the cell death pathways engaged by metabolic inhibitors. Additionally, we will detail the similarities between metabolism of cancer cells and metabolism of proliferating cells.     

Effect of acetate and octanoate on tricarboxylic acid cycle metabolite disposal during propionate oxidation in the perfused rat heart

Tricarboxylic acid cycle pool size is determined by anaplerosis and metabolite disposal. The regulation of the latter during propionate metabolism was studied in isolated perfused rat hearts in the light of the characteristics of NADP-linked malic enzyme, which is inhibited by acetyl-CoA. The acetyl-CoA concentration was varied by infusions of acetate and octanoate, and the rate of metabolite disposal was calculated from a metabolic balance sheet compiled from the relevant metabolic fluxes. Propionate addition increased the tricarboxylic acid cycle pool size 4-fold and co-infusion of acetate or octanoate did not change it further. Propionate caused a decrease in the CoA-SH concentration and a 10-fold increase in the propionyl-CoA concentration. A paradoxical increase in the CoA-SH concentration was observed upon co-infusion of acetate in the presence of propionate, an effect probably caused by competitive inhibition of propionate activation. A more pronounced decline in the propionyl-CoA concentration was observed upon the co-infusion of octanoate. In a metabolic steady state, acetate and octanoate reduced propionate disposal only slightly, but did not increase the tricarboxylic acid cycle pool size. The results are in accord with the notion that the tricarboxylic acid pool size is mainly regulated by the anaplerotic mechanisms.     

Proteome-Wide Identification of Lysine Succinylation in the Proteins of Tomato (Solanum lycopersicum)

Post-translational modification of proteins through lysine succinylation plays important regulatory roles in living cells. Lysine succinylation was recently identified as a novel post-translational modification in Escherichia coli, yeast, Toxoplasma gondii, HeLa cells, and mouse liver. Interestingly, only a few sites of lysine succinylation have been detected in plants to date. In this study, we identified 347 sites of lysine succinylation in 202 proteins in tomato by using high-resolution mass spectrometry. Succinylated proteins are implicated in the regulation of diverse metabolic processes, including chloroplast and mitochondrial metabolism. Bioinformatic analysis showed that succinylated proteins are evolutionarily conserved and involved in various cellular functions such as metabolism and epigenetic regulation. Moreover, succinylated proteins exhibit diverse subcellular localizations. We also defined six types of definitively conserved succinylation motifs. These results provide the first in-depth analysis of the lysine succinylome and novel insights into the role of succinylation in tomato, thereby elucidating lysine succinylation in the context of cellular physiology and metabolite biosynthesis in plants.     

Identifying All Moiety Conservation Laws in Genome-Scale Metabolic Networks

The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell''s metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.