Metabolic flux analysis of Escherichia coli MG1655 under octanoic acid (C8) stress

The Protective Effect of Octanoic Acid on Sepsis: A Review

Sepsis, a systemic inflammation that occurs in response to a bacterial infection, is a significant medical challenge. Research conducted over the past decade has indicated strong associations among a patient's nutritional status, the composition of their gut microbiome, and the risk, severity, and prognosis of sepsis. Octanoic acid (OA) plays a vital role in combating sepsis and has a protective effect on both animal models and human patients. In this discussion, the potential protective mechanisms of OA in sepsis, focusing on its regulation of the inflammatory response, immune system, oxidative stress, gastrointestinal microbiome and barrier function, metabolic disorders and malnutrition, as well as organ dysfunction are explored. A comprehensive understanding of the mechanisms by which OA act may pave the way for new preventive and therapeutic approaches to sepsis.

13C metabolic flux analysis: Classification and characterization from the perspective of mathematical modeling and application in physiological research of neural cell

¹³C metabolic flux analysis (¹³C-MFA) has emerged as a forceful tool for quantifying in vivo metabolic pathway activity of different biological systems. This technology plays an important role in understanding intracellular metabolism and revealing patho-physiology mechanism. Recently, it has evolved into a method family with great diversity in experiments, analytics, and mathematics. In this review, we classify and characterize the various branch of ¹³C-MFA from a unified perspective of mathematical modeling. By linking different parts in the model to each step of its workflow, the specific technologies of ¹³C-MFA are put into discussion, including the isotope labeling model (ILM), isotope pattern measuring technique, optimization algorithm and statistical method. Its application in physiological research in neural cell has also been reviewed.

Unraveling the expression of differentially expressed proteins and enzymatic activity in response to Phytophthora nicotianae across different flue-cured tobacco cultivars

BACKGROUND

Black shank disease caused by Phytophthora nicotianae is a serious threat to flue-cured tobacco production. Whole-plant resistance is characterized by the expression of a number of pathogenesis-related proteins, genes, and the activity of different defense-related enzymes. In this study, we investigated the activity of defense-related enzymes and expression of differentially expressed proteins through the iTRAQ technique across two flue-cured tobacco cultivars, i.e., K326 and Hongda, in response to the black shank pathogen.

RESULTS

Results showed that the highest disease incidence was recorded in flue-cured tobacco cultivar Hongda compared with K326, which shows that Hongda is more susceptible to P. nicotianae than K326. A total of 4274 differentially expressed proteins were detected at 0 h and after 24 h, 72 h of post-inoculation with P. nicotianae. We found that 17 proteins induced after inoculation with P. nicotianae, including pathogenesis (5), photosynthesis (3), oxidative phosphorylation (6), tricarboxylic acid cycle (1), heat shock (1), and 14-3-3 (1) and were involved in the resistance of flue-cured tobacco against black shank disease. The expression of 5 pathogenesis-related proteins and the activities of defense-related enzymes (PPO, POD, SOD, and MDA) were significantly higher in the leaves of K326 than Hongda after inoculation with P. nicotianae.

CONCLUSION

These results provide new molecular insights into flue-cured tobacco responses to P. nicotianae. It is concluded that differences in protein expressions and defense-related enzymes play an important role in developing resistance in flue-cured tobacco cultivars against black shank disease.

Global pleiotropic effects in adaptively evolved Escherichia coli lacking CRP reveal molecular mechanisms that define the growth physiology

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.

INCA 2.0: A tool for integrated, dynamic modeling of NMR- and MS-based isotopomer measurements and rigorous metabolic flux analysis

Metabolic flux analysis (MFA) combines experimental measurements and computational modeling to determine biochemical reaction rates in live biological systems. Advancements in analytical instrumentation, such as nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), have facilitated chemical separation and quantification of isotopically enriched metabolites. However, no software packages have been previously described that can integrate isotopomer measurements from both MS and NMR analytical platforms and have the flexibility to estimate metabolic fluxes from either isotopic steady-state or dynamic labeling experiments. By applying physiologically relevant cardiac and hepatic metabolic models to assess NMR isotopomer measurements, we herein test and validate new modeling capabilities of our enhanced flux analysis software tool, INCA 2.0. We demonstrate that INCA 2.0 can simulate and regress steady-state 13C NMR datasets from perfused hearts with an accuracy comparable to other established flux assessment tools. Furthermore, by simulating the infusion of three different 13C acetate tracers, we show that MFA based on dynamic 13C NMR measurements can more precisely resolve cardiac fluxes compared to isotopically steady-state flux analysis. Finally, we show that estimation of hepatic fluxes using combined 13C NMR and MS datasets improves the precision of estimated fluxes by up to 50%. Overall, our results illustrate how the recently added NMR data modeling capabilities of INCA 2.0 can enable entirely new experimental designs that lead to improved flux resolution and can be applied to a wide range of biological systems and measurement time courses.

Global Transcriptional Regulators Fine-Tune the Translational and Metabolic Efficiency for Optimal Growth of Escherichia coli

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.

Fermentation of Organic Residues to Beneficial Chemicals: A Review of Medium-Chain Fatty Acid Production

Medium-chain fatty acids (MCFAs) have a variety of uses in the production of industrial chemicals, food, and personal care products. These compounds are often produced through palm refining, but recent work has demonstrated that MCFAs can also be produced through the fermentation of complex organic substrates, including organic waste streams. While “chain elongation” offers a renewable platform for producing MCFAs, there are several limitations that need to be addressed before full-scale implementation becomes widespread. Here, we review the history of work on MCFA production by both pure and mixed cultures of fermenting organisms, and the unique metabolic features that lead to MCFA production. We also offer approaches to address the remaining challenges and increase MCFA production from renewable feedstocks.

Metabolic Flux Analysis-Linking Isotope Labeling and Metabolic Fluxes

Metabolic flux analysis (MFA) is an increasingly important tool to study metabolism quantitatively. Unlike the concentrations of metabolites, the fluxes, which are the rates at which intracellular metabolites interconvert, are not directly measurable. MFA uses stable isotope labeled tracers to reveal information related to the fluxes. The conceptual idea of MFA is that in tracer experiments the isotope labeling patterns of intracellular metabolites are determined by the fluxes, therefore by measuring the labeling patterns we can infer the fluxes in the network. In this review, we will discuss the basic concept of MFA using a simplified upper glycolysis network as an example. We will show how the fluxes are reflected in the isotope labeling patterns. The central idea we wish to deliver is that under metabolic and isotopic steady-state the labeling pattern of a metabolite is the flux-weighted average of the substrates’ labeling patterns. As a result, MFA can tell the relative contributions of converging metabolic pathways only when these pathways make substrates in different labeling patterns for the shared product. This is the fundamental principle guiding the design of isotope labeling experiment for MFA including tracer selection. In addition, we will also discuss the basic biochemical assumptions of MFA, and we will show the flux-solving procedure and result evaluation. Finally, we will highlight the link between isotopically stationary and nonstationary flux analysis.

Characterization of non-radiolabeled Thyroxine (T4) uptake in cryopreserved rat hepatocyte suspensions: Pharmacokinetic implications for PFOA and PFOS chemical exposure

The alteration of thyroxine (T₄) cellular uptake by an environmental chemical can serve as a contributing factor in thyroid hormone (TH) disruption. Herein, we describe a non-radiolabeled (LC-MS/MS) oil-filtration technique designed to characterize the mechanism(s) responsible for T₄ cellular uptake in cryopreserved rat hepatocyte suspensions. The environmental chemicals perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) were evaluated for their effect on T₄ hepatic uptake. At 37 °C, hepatic assays demonstrated saturable kinetics with increasing T₄ concentrations, while a linear uptake rate consistent with passive diffusion was detected at 4 °C. Carrier-mediated (37-4 °C) transport of T₄ was the predominant hepatic uptake process versus passive diffusion. Cyclosporin A (CsA) chemically inhibited T₄ hepatic uptake, whereas PFOA/PFOS displayed no inhibition of T₄ translocation. Increasing PFOA/PFOS concentration levels with the T₄ serum carrier-protein transthyretin (TTR) present resulted in a dose-response increase in T₄ hepatic uptake rates, correlating with increased T₄ free fraction values. Hepatic assays conducted in the presence of PFOA/PFOS and TTR displayed an enhanced first-order T₄ hepatic uptake rate consistent with carrier-mediated transport. These in vitro findings characterizing increased T₄ hepatic uptake provides mechanistic insight regarding decreased T₄ serum levels (hypothyroxinemia) previously observed within in vivo rodent studies following perfluorinated chemical exposure.

Thermodynamic analysis of computed pathways integrated into the metabolic networks of E. coli and Synechocystis reveals contrasting expansion potential

Introducing biosynthetic pathways into an organism is both reliant on and challenged by endogenous biochemistry. Here we compared the expansion potential of the metabolic network in the photoautotroph Synechocystis with that of the heterotroph E. coli using the novel workflow POPPY (Prospecting Optimal Pathways with PYthon). First, E. coli and Synechocystis metabolomic and fluxomic data were combined with metabolic models to identify thermodynamic constraints on metabolite concentrations (NET analysis). Then, thousands of automatically constructed pathways were placed within each network and subjected to a network-embedded variant of the max-min driving force analysis (NEM). We found that the networks had different capabilities for imparting thermodynamic driving forces toward certain compounds. Key metabolites were constrained differently in Synechocystis due to opposing flux directions in glycolysis and carbon fixation, the forked tri-carboxylic acid cycle, and photorespiration. Furthermore, the lysine biosynthesis pathway in Synechocystis was identified as thermodynamically constrained, impacting both endogenous and heterologous reactions through low 2-oxoglutarate levels. Our study also identified important yet poorly covered areas in existing metabolomics data and provides a reference for future thermodynamics-based engineering in Synechocystis and beyond. The POPPY methodology represents a step in making optimal pathway-host matches, which is likely to become important as the practical range of host organisms is diversified.

Synergizing 13C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production

Metabolic engineering of industrial microorganisms to produce chemicals, fuels, and drugs has attracted increasing interest as it provides an environment-friendly and renewable route that does not depend on depleting petroleum sources. However, the microbial metabolism is so complex that metabolic engineering efforts often have difficulty in achieving a satisfactory yield, titer, or productivity of the target chemical. To overcome this challenge, ¹³C Metabolic Flux Analysis (¹³C-MFA) has been developed to investigate rigorously the cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, ¹³C-MFA has been widely used in academic labs and the biotechnology industry to pinpoint the key issues related to microbial-based chemical production and to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this chapter we introduce the basics of ¹³C-MFA and illustrate how ¹³C-MFA has been applied to synergize with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production.

Activation of the Glutamic Acid-Dependent Acid Resistance System in Escherichia coli BL21(DE3) Leads to Increase of the Fatty Acid Biotransformation Activity

The biosynthesis of carboxylic acids including fatty acids from biomass is central in envisaged biorefinery concepts. The productivities are often, however, low due to product toxicity that hamper whole-cell biocatalyst performance. Here, we have investigated factors that influence the tolerance of Escherichia coli to medium chain carboxylic acid (i.e., n-heptanoic acid)-induced stress. The metabolic and genomic responses of E. coli BL21(DE3) and MG1655 grown in the presence of n-heptanoic acid indicated that the GadA/B-based glutamic acid-dependent acid resistance (GDAR) system might be critical for cellular tolerance. The GDAR system, which is responsible for scavenging intracellular protons by catalyzing decarboxylation of glutamic acid, was inactive in E. coli BL21(DE3). Activation of the GDAR system in this strain by overexpressing the rcsB and dsrA genes, of which the gene products are involved in the activation of GadE and RpoS, respectively, resulted in acid tolerance not only to HCl but also to n-heptanoic acid. Furthermore, activation of the GDAR system allowed the recombinant E. coli BL21(DE3) expressing the alcohol dehydrogenase of Micrococcus luteus and the Baeyer-Villiger monooxygenase of Pseudomonas putida to reach 60% greater product concentration in the biotransformation of ricinoleic acid (i.e., 12-hydroxyoctadec-9-enoic acid (1)) into n-heptanoic acid (5) and 11-hydroxyundec-9-enoic acid (4). This study may contribute to engineering E. coli-based biocatalysts for the production of carboxylic acids from renewable biomass.

Engineering membrane and cell-wall programs for tolerance to toxic chemicals: Beyond solo genes

Metabolite toxicity in microbes, particularly at the membrane, remains a bottleneck in the production of fuels and chemicals. Under chemical stress, native adaptation mechanisms combat hyper-fluidization by modifying the phospholipids in the membrane. Recent work in fluxomics reveals the mechanism of how membrane damage negatively affects energy metabolism while lipidomic and transcriptomic analyses show that strains evolved to be tolerant maintain membrane fluidity under stress through a variety of mechanisms such as incorporation of cyclopropanated fatty acids, trans-unsaturated fatty acids, and upregulation of cell wall biosynthesis genes. Engineered strains with modifications made in the biosynthesis of fatty acids, peptidoglycan, and lipopolysaccharide have shown increased tolerance to exogenous stress as well as increased production of desired metabolites of industrial importance. We review recent advances in elucidation of mechanisms or toxicity and tolerance as well as efforts to engineer the bacterial membrane and cell wall.

Production of FAME biodiesel in E. coli by direct methylation with an insect enzyme

Most biodiesel currently in use consists of fatty acid methyl esters (FAMEs) produced by transesterification of plant oils with methanol. To reduce competition with food supplies, it would be desirable to directly produce biodiesel in microorganisms. To date, the most effective pathway for the production of biodiesel in bacteria yields fatty acid ethyl esters (FAEEs) at up to ~1.5 g/L. A much simpler route to biodiesel produces FAMEs by direct S-adenosyl-L-methionine (SAM) dependent methylation of free fatty acids, but FAME production by this route has been limited to only ~16 mg/L. Here we employ an alternative, broad spectrum methyltransferase, Drosophila melanogaster Juvenile Hormone Acid O-Methyltransferase (DmJHAMT). By introducing DmJHAMT in E. coli engineered to produce medium chain fatty acids and overproduce SAM, we obtain medium chain FAMEs at titers of 0.56 g/L, a 35-fold increase over titers previously achieved. Although considerable improvements will be needed for viable bacterial production of FAMEs and FAEEs for biofuels, it may be easier to optimize and transport the FAME production pathway to other microorganisms because it involves fewer enzymes.

Examining Escherichia coli glycolytic pathways, catabolite repression, and metabolite channeling using Δpfk mutants

BACKGROUND

Glycolysis breakdowns glucose into essential building blocks and ATP/NAD(P)H for the cell, occupying a central role in its growth and bio-production. Among glycolytic pathways, the Entner Doudoroff pathway (EDP) is a more thermodynamically favorable pathway with fewer enzymatic steps than either the Embden-Meyerhof-Parnas pathway (EMPP) or the oxidative pentose phosphate pathway (OPPP). However, Escherichia coli do not use their native EDP for glucose metabolism.

RESULTS

Overexpression of edd and eda in E. coli to enhance EDP activity resulted in only a small shift in the flux directed through the EDP (~20 % of glycolysis flux). Disrupting the EMPP by phosphofructokinase I (pfkA) knockout increased flux through OPPP (~60 % of glycolysis flux) and the native EDP (~14 % of glycolysis flux), while overexpressing edd and eda in this ΔpfkA mutant directed ~70 % of glycolytic flux through the EDP. The downregulation of EMPP via the pfkA deletion significantly decreased the growth rate, while EDP overexpression in the ΔpfkA mutant failed to improve its growth rates due to metabolic burden. However, the reorganization of E. coli glycolytic strategies did reduce glucose catabolite repression. The ΔpfkA mutant in glucose medium was able to cometabolize acetate via the citric acid cycle and gluconeogenesis, while EDP overexpression in the ΔpfkA mutant repressed acetate flux toward gluconeogenesis. Moreover, ¹³C-pulse experiments in the ΔpfkA mutants showed unsequential labeling dynamics in glycolysis intermediates, possibly suggesting metabolite channeling (metabolites in glycolysis are pass from enzyme to enzyme without fully equilibrating within the cytosol medium).

CONCLUSIONS

We engineered E. coli to redistribute its native glycolytic flux. The replacement of EMPP by EDP did not improve E. coli glucose utilization or biomass growth, but alleviated catabolite repression. More importantly, our results supported the hypothesis of channeling in the glycolytic pathways, a potentially overlooked mechanism for regulating glucose catabolism and coutilization of other substrates. The presence of channeling in native pathways, if proven true, would affect synthetic biology applications and metabolic modeling.

13C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production

Metabolic engineering of various industrial microorganisms to produce chemicals, fuels, and drugs has raised interest since it is environmentally friendly, sustainable, and independent of nonrenewable resources. However, microbial metabolism is so complex that only a few metabolic engineering efforts have been able to achieve a satisfactory yield, titer or productivity of the target chemicals for industrial commercialization. In order to overcome this challenge, ¹³C Metabolic Flux Analysis (¹³C-MFA) has been continuously developed and widely applied to rigorously investigate cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, many ¹³C-MFA studies have been performed in academic labs and biotechnology industries to pinpoint key issues related to microbe-based chemical production. Insightful information about the metabolic rewiring has been provided to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this review, we will introduce the basics of ¹³C-MFA and illustrate how ¹³C-MFA has been applied via integration with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production for various host microorganisms

Transcriptional analysis of the effect of exogenous decanoic acid stress on Streptomyces roseosporus

BACKGROUND

Daptomycin is an important antibiotic against infections caused by drug-resistant pathogens. Its production critically depends on the addition of decanoic acid during fermentation. Unfortunately, decanoic acid (>2.5 mM) is toxic to daptomycin producer, Streptomyces roseosporus.

RESULTS

To understand the mechanism underlying decanoic tolerance or toxicity, the responses of S. roseosporus was determined by a combination of phospholipid fatty acid analysis, reactive oxygen species (ROS) measurement and RNA sequencing. Assays using fluorescent dyes indicated a sharp increase in reactive oxygen species during decanoic acid stress; fatty acid analysis revealed a marked increase in the composition of branched-chain fatty acids by approximately 10%, with a corresponding decrease in straight-chain fatty acids; functional analysis indicated decanoic acid stress has components common to other stress response, including perturbation of respiratory functions (nuo and cyd operons), oxidative stress, and heat shock. Interestingly, our transcriptomic analysis revealed that genes coding for components of proteasome and related to treholase synthesis were up-regulated in the decanoic acid -treated cells.

CONCLUSION

These findings represent an important first step in understanding mechanism of decanoic acid toxicity and provide a basis for engineering microbial tolerance.