Metabolic engineering in the -omics era: elucidating and modulating regulatory networks

Comprehensive insights into herbicide resistance mechanisms in weeds: a synergistic integration of transcriptomic and metabolomic analyses

Omics techniques, including genomics, transcriptomics, proteomics, and metabolomics have smoothed the researcher's ability to generate hypotheses and discover various agronomically relevant functions and mechanisms, as well as their implications and associations. With a significant increase in the number of cases with resistance to multiple herbicide modes of action, studies on herbicide resistance are currently one of the predominant areas of research within the field of weed science. High-throughput technologies have already started revolutionizing the current molecular weed biology studies. The evolution of herbicide resistance in weeds (particularly via non-target site resistance mechanism) is a perfect example of a complex, multi-pathway integration-induced response. To date, functional genomics, including transcriptomic and metabolomic studies have been used separately in herbicide resistance research, however there is a substantial lack of integrated approach. Hence, despite the ability of omics technologies to provide significant insights into the molecular functioning of weeds, using a single omics can sometimes be misleading. This mini-review will aim to discuss the current progress of transcriptome-based and metabolome-based approaches in herbicide resistance research, along with their systematic integration.

Metabolic Engineering: Methodologies and Applications

Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.

Recent Advances, Challenges and Metabolic Engineering Strategies in the Biosynthesis of 3-Hydroxypropionic Acid

As an attractive and valuable platform chemical, 3-hydroxypropionic acid (3-HP) can be used to produce a variety of industrially important commodity chemicals and biodegradable polymers. Moreover, the biosynthesis of 3-HP has drawn much attention in recent years due to its sustainability and environmental friendliness. Here, we focus on recent advances, challenges and metabolic engineering strategies in the biosynthesis of 3-HP. While glucose and glycerol are major carbon sources for its production of 3-HP via microbial fermentation, other carbon sources have also been explored. To increase yield and titer, synthetic biology and metabolic engineering strategies have been explored, including modifying pathway enzymes, eliminating flux blockages due to byproduct synthesis, eliminating toxic byproducts, and optimizing via genome-scale models. This review also provides insights on future directions for 3-HP biosynthesis. This article is protected by copyright. All rights reserved.

Tackling Current Biomedical Challenges With Frontier Biofabrication and Organ-On-A-Chip Technologies

In the last decades, biomedical research has significantly boomed in the academia and industrial sectors, and it is expected to continue to grow at a rapid pace in the future. An in-depth analysis of such growth is not trivial, given the intrinsic multidisciplinary nature of biomedical research. Nevertheless, technological advances are among the main factors which have enabled such progress. In this review, we discuss the contribution of two state-of-the-art technologies-namely biofabrication and organ-on-a-chip-in a selection of biomedical research areas. We start by providing an overview of these technologies and their capacities in fabricating advanced in vitro tissue/organ models. We then analyze their impact on addressing a range of current biomedical challenges. Ultimately, we speculate about their future developments by integrating these technologies with other cutting-edge research fields such as artificial intelligence and big data analysis.

Rescaling Biology: Increasing Integration Across Biological Scales and Subdisciplines to Enhance Understanding and Prediction

The organization of the living world covers a vast range of spatiotemporal scales, from molecules to the biosphere, seconds to centuries. Biologists working within specialized subdisciplines tend to focus on different ranges of scales. Therefore, developing frameworks that enable testing questions and predictions of scaling require sufficient understanding of complex processes across biological subdisciplines and spatiotemporal scales. Frameworks that enable scaling across subdisciplines would ideally allow us to test hypotheses about the degree to which explicit integration across spatiotemporal scales is needed for predicting the outcome of biological processes. For instance, how does genomic variation within populations allow us to explain community structure? How do the dynamics of cellular metabolism translate to our understanding of whole-ecosystem metabolism? Do patterns and processes operate seamlessly across biological scales, or are there fundamental laws of biological scaling that limit our ability to make predictions from one scale to another? Similarly, can sub-organismal structures and processes be sufficiently understood in isolation of potential feedbacks from the population, community, or ecosystem levels? And can we infer the sub-organismal processes from data on the population, community, or ecosystem scale? Concerted efforts to develop more cross-disciplinary frameworks will open doors to a more fully integrated field of biology. In this paper we discuss how we might integrate across scales, specifically by 1. Identifying scales and boundaries, 2. Determining analogous units and processes across scales, 3. Developing frameworks to unite multiple scales, and 4. Extending frameworks to new empirical systems.

Acetate as a potential feedstock for the production of value-added chemicals: Metabolism and applications

Acetate is regarded as a promising carbon feedstock in biological production owing to its possible derivation from C₁ gases such as CO, CO₂ and methane. To best use of acetate, comprehensive understanding of acetate metabolisms from genes and enzymes to pathways and regulations is needed. This review aims to provide an overview on the potential of acetate as carbon feedstock for industrial biotechnology. Biochemical, microbial and biotechnological aspects of acetate metabolism are described. Especially, the current state-of-the art in the production of value-added chemicals from acetate is summarized. Challenges and future perspectives are also provided.

Flux prediction using artificial neural network (ANN) for the upper part of glycolysis

The selection of optimal enzyme concentration in multienzyme cascade reactions for the highest product yield in practice is very expensive and time-consuming process. The modelling of biological pathways is a difficult process because of the complexity of the system. The mathematical modelling of the system using an analytical approach depends on the many parameters of enzymes which rely on tedious and expensive experiments. The artificial neural network (ANN) method has been successively applied in different fields of science to perform complex functions. In this study, ANN models were trained to predict the flux for the upper part of glycolysis as inferred by NADH consumption, using four enzyme concentrations i.e., phosphoglucoisomerase, phosphofructokinase, fructose-bisphosphate-aldolase, triose-phosphate-isomerase. Out of three ANN algorithms, the neuralnet package with two activation functions, “logistic” and “tanh” were implemented. The prediction of the flux was very efficient: RMSE and R² were 0.847, 0.93 and 0.804, 0.94 respectively for logistic and tanh functions using a cross validation procedure. This study showed that a systemic approach such as ANN could be used for accurate prediction of the flux through the metabolic pathway. This could help to save a lot of time and costs, particularly from an industrial perspective. The R-code is available at: https://github.com/DSIMB/ANN-Glycolysis-Flux-Prediction.

Comprehensive assessment of measurement uncertainty in 13C-based metabolic flux experiments

In the field of metabolic engineering ¹³C-based metabolic flux analysis experiments have proven successful in indicating points of action. As every step of this approach is affected by an inherent error, the aim of the present work is the comprehensive evaluation of factors contributing to the uncertainty of nonnaturally distributed C-isotopologue abundances as well as to the absolute flux value calculation. For this purpose, a previously published data set, analyzed in the course of a ¹³C labeling experiment studying glycolysis and the pentose phosphate pathway in a yeast cell factory, was used. Here, for isotopologue pattern analysis of these highly polar metabolites that occur in multiple isomeric forms, a gas chromatographic separation approach with preceding derivatization was used. This rendered a natural isotope interference correction step essential. Uncertainty estimation of the resulting C-isotopologue distribution was performed according to the EURACHEM guidelines with Monte Carlo simulation. It revealed a significant increase for low-abundance isotopologue fractions after application of the necessary correction step. For absolute flux value estimation, isotopologue fractions of various sugar phosphates, together with the assessed uncertainties, were used in a metabolic model describing the upper part of the central carbon metabolism. The findings pinpointed the influence of small isotopologue fractions as sources of error and highlight the need for improved model curation.

Graphical abstract

Promiscuous activities of heterologous enzymes lead to unintended metabolic rerouting in Saccharomyces cerevisiae engineered to assimilate various sugars from renewable biomass

BACKGROUND

Understanding the global metabolic network, significantly perturbed upon promiscuous activities of foreign enzymes and different carbon sources, is crucial for systematic optimization of metabolic engineering of yeast Saccharomyces cerevisiae. Here, we studied the effects of promiscuous activities of overexpressed enzymes encoded by foreign genes on rerouting of metabolic fluxes of an engineered yeast capable of assimilating sugars from renewable biomass by profiling intracellular and extracellular metabolites.

RESULTS

Unbiased metabolite profiling of the engineered S. cerevisiae strain EJ4 revealed promiscuous enzymatic activities of xylose reductase and xylitol dehydrogenase on galactose and galactitol, respectively, resulting in accumulation of galactitol and tagatose during galactose fermentation. Moreover, during glucose fermentation, a trisaccharide consisting of glucose accumulated outside of the cells probably owing to the promiscuous and transglycosylation activity of β-glucosidase expressed for hydrolyzing cellobiose. Meanwhile, higher accumulation of fatty acids and secondary metabolites was observed during xylose and cellobiose fermentations, respectively.

CONCLUSIONS

The heterologous enzymes functionally expressed in S. cerevisiae showed promiscuous activities that led to unintended metabolic rerouting in strain EJ4. Such metabolic rerouting could result in a low yield and productivity of a final product due to the formation of unexpected metabolites. Furthermore, the global metabolic network can be significantly regulated by carbon sources, thus yielding different patterns of metabolite production. This metabolomic study can provide useful information for yeast strain improvement and systematic optimization of yeast metabolism to manufacture bio-based products.

Recent Advances in the Recombinant Biosynthesis of Polyphenols

Plants are the source of various natural compounds with pharmaceutical and nutraceutical importance which have shown numerous health benefits with relatively fewer side effects. However, extraction of these compounds from native producers cannot meet the ever-increasing demands of the growing population due to, among other things, the limited production of the active compound(s). Their production depends upon the metabolic demands of the plant and is also subjected to environmental conditions, abundance of crop species and seasonal variations. Moreover, their extraction from plants requires complex downstream processing and can also lead to the extinction of many useful plant varieties. Microbial engineering is one of the alternative approaches which can meet the global demand for natural products in an eco-friendly manner. Metabolic engineering of microbes or pathway reconstruction using synthetic biology tools and novel enzymes lead to the generation of a diversity of compounds (like flavonoids, stilbenes, anthocyanins etc.) and their natural and non-natural derivatives. Strain and pathway optimization, pathway regulation and tolerance engineering have produced microbial cell factories into which the metabolic pathway of plants can be introduced for the production of compounds of interest on an industrial scale in an economical and eco-friendly way. While microbial production of phytochemicals needs to further increase product titer if it is ever to become a commercial success. The present review covers the advancements made for the improvement of microbial cell factories in order to increase the product titer of recombinant polyphenolic compounds.

Systems Metabolic Engineering of Escherichia coli

Systems metabolic engineering, which recently emerged as metabolic engineering integrated with systems biology, synthetic biology, and evolutionary engineering, allows engineering of microorganisms on a systemic level for the production of valuable chemicals far beyond its native capabilities. Here, we review the strategies for systems metabolic engineering and particularly its applications in Escherichia coli. First, we cover the various tools developed for genetic manipulation in E. coli to increase the production titers of desired chemicals. Next, we detail the strategies for systems metabolic engineering in E. coli, covering the engineering of the native metabolism, the expansion of metabolism with synthetic pathways, and the process engineering aspects undertaken to achieve higher production titers of desired chemicals. Finally, we examine a couple of notable products as case studies produced in E. coli strains developed by systems metabolic engineering. The large portfolio of chemical products successfully produced by engineered E. coli listed here demonstrates the sheer capacity of what can be envisioned and achieved with respect to microbial production of chemicals. Systems metabolic engineering is no longer in its infancy; it is now widely employed and is also positioned to further embrace next-generation interdisciplinary principles and innovation for its upgrade. Systems metabolic engineering will play increasingly important roles in developing industrial strains including E. coli that are capable of efficiently producing natural and nonnatural chemicals and materials from renewable nonfood biomass.

BCL6 mediates the effects of Gastrodin on promoting M2-like macrophage polarization and protecting against oxidative stress-induced apoptosis and cell death in macrophages

Cerebral palsy (CP) is the most common childhood disability worldwide, yet biomarkers for predicting CP are lacking. By subjecting peripheral blood samples from 62 CP patients and 30 healthy controls to Affymetrix GeneChip^® PrimeView™ HumanGene Expression Microarray analysis, we identified the novel biomarker B-cell lymphoma 6 (BCL6) as the most upregulated gene in the CP samples. Gastrodin is a traditional Chinese medicine and bioactive compound that promotes adductor angle release, as well as gross and fine motor performance by increasing Gross Motor Function Measure-66 and Fine Motor Function Measure-45 scores. Gastrodin upregulates the mRNA expression of Mgl2 and Mrc1, M2 macrophage markers, and arginase activity, an M2 polarization indicator, in murine RAW264.7 macrophages. Moreover, these effects were blocked by BCL6 siRNA, which also abrogated the protective effects of Gastrodin against hydrogen peroxide-induced apoptosis and death in RAW264.7 cells. Our work identified BCL6 as a novel biomarker for early prediction of CP. Moreover, we demonstrated that Gastrodin not only stimulated polarization toward M2-like macrophages, which promote tissue repair, but also rescued macrophages from oxidative stress, apoptosis and death by inducing BCL6 expression. BCL6-targeted therapeutic strategies have promise for improving motor performance in CP patients.

Road to the future of systems biotechnology: CRISPR-Cas-mediated metabolic engineering for recombinant protein production

The rising potential for CRISPR-Cas-mediated genome editing has revolutionized our strategies in basic and practical bioengineering research. It provides a predictable and precise method for genome modification in a robust and reproducible fashion. Emergence of systems biotechnology and synthetic biology approaches coupled with CRISPR-Cas technology could change the future of cell factories to possess some new features which have not been found naturally. We have discussed the possibility and versatile potentials of CRISPR-Cas technology for metabolic engineering of a recombinant host for heterologous protein production. We describe the mechanisms involved in this metabolic engineering approach and present the diverse features of its application in biotechnology and protein production.

Elucidation of Cross-Talk and Specificity of Early Response Mechanisms to Salt and PEG-Simulated Drought Stresses in Brassica napus Using Comparative Proteomic Analysis

To understand the cross-talk and specificity of the early responses of plants to salt and drought, we performed physiological and proteome analyses of Brassica napus seedlings pretreated with 245 mM NaCl or 25% polyethylene glycol (PEG) 6000 under identical osmotic pressure (-1.0 MPa). Significant decreases in water content and photosynthetic rate and excessive accumulation of compatible osmolytes and oxidative damage were observed in response to both stresses. Unexpectedly, the drought response was more severe than the salt response. We further identified 45 common differentially expressed proteins (DEPs), 143 salt-specific DEPs and 160 drought-specific DEPs by isobaric tags for relative and absolute quantitation (iTRAQ) analysis. The proteome quantitative data were then confirmed by multiple reaction monitoring (MRM). The differences in the proteomic profiles between drought-treated and salt-treated seedlings exceeded the similarities in the early stress responses. Signal perception and transduction, transport and membrane trafficking, and photosynthesis-related proteins were enriched as part of the molecular cross-talk and specificity mechanism in the early responses to the two abiotic stresses. The Ca²⁺ signaling, G protein-related signaling, 14-3-3 signaling pathway and phosphorylation cascades were the common signal transduction pathways shared by both salt and drought stress responses; however, the proteins with executive functions varied. These results indicate functional specialization of family proteins in response to different stresses, i.e., CDPK21, TPR, and CTR1 specific to phosphorylation cascades under early salt stress, whereas STN7 and BSL were specific to phosphorylation cascades under early drought stress. Only the calcium-binding EF-hand family protein and ZKT were clearly identified as signaling proteins that acted as cross-talk nodes for salt and drought signaling pathways. Our study provides new clues and insights for developing strategies to improve the tolerance of crops to complex, multiple environmental stresses.

Marine metagenomics as a source for bioprospecting

This review summarizes usage of genome-editing technologies for metagenomic studies; these studies are used to retrieve and modify valuable microorganisms for production, particularly in marine metagenomics. Organisms may be cultivable or uncultivable. Metagenomics is providing especially valuable information for uncultivable samples. The novel genes, pathways and genomes can be deducted. Therefore, metagenomics, particularly genome engineering and system biology, allows for the enhancement of biological and chemical producers and the creation of novel bioresources. With natural resources rapidly depleting, genomics may be an effective way to efficiently produce quantities of known and novel foods, livestock feed, fuels, pharmaceuticals and fine or bulk chemicals.

Metabolic engineering of Escherichia coli to minimize byproduct formate and improving succinate productivity through increasing NADH availability by heterologous expression of NAD(+)-dependent formate dehydrogenase

Succinic acid is a specialty chemical having numerous applications in industrial, pharmaceutical and food uses. One of the major challenges in the succinate fermentation process is eliminating the formation of byproducts. In this study, we describe eliminating byproduct formate and improving succinate productivity by reengineering a high succinate producing E. coli strain SBS550MG-Cms243(pHL413Km). The NAD(+)-dependent formate dehydrogenase gene (fdh1) of Candida boidinii was coexpressed with Lactococcus lactis pyruvate carboxylase (pycA) under the control of Ptrc and PpycA promoters in plasmid pHL413KF1. The newly introduced fdh1 converts 1 mol of formate into 1 mol of NADH and CO2. The reengineered strain SBS550MG-Cms243(pHL413KF1) retains the reducing power of formate through an increase in NADH availability. In anaerobic shake flask fermentations, the parent strain SBS550MG-Cms243(pHL413Km) consumed 99.86 mM glucose and produced 172.38 mM succinate, 16.16 mM formate and 4.42 mM acetate. The FDH bearing strain, SBS550MG-Cms243(pHL413KF1) consumed 98.43 mM glucose and produced 171.80 mM succinate, 1mM formate and 5.78 mM acetate. Furthermore, external formate supplementation to SBS550MG(pHL413KF1) fermentations resulted in about 6% increase in succinate yields as compared to SBS550MG(pHL413Km). In an anaerobic fed-batch bioreactor process, the average glucose consumption rate, succinate productivity, and byproduct formate concentration of SBS550MG(pHL413Km) was 1.40 g/L/h, 1g/L/h, and 17 mM, respectively. Whereas, the average glucose consumption rate, succinate productivity and byproduct formate concentration of SBS550MG(pHL413KF1) was 2 g/L/h, 2 g/L/h, 0-3 mM respectively. A high cell density culture of SBS550MG(pHL413KF1) showed further improvement in succinate productivity with a higher glucose consumption rate. Reduced levels of byproduct formate in succinate fermentation broth would provide an opportunity for reducing the cost associated with downstream processing, purification, and waste disposal.

A closed-loop control scheme for steering steady states of glycolysis and glycogenolysis pathway

Biochemical networks normally operate in the neighborhood of one of its multiple steady states. It may reach from one steady state to other within a finite time span. In this paper, a closed-loop control scheme is proposed to steer states of the glycolysis and glycogenolysis (GG) pathway from one of its steady states to other. The GG pathway is modeled in the synergism and saturation system formalism, known as S-system. This S-system model is linearized into the controllable Brunovsky canonical form using a feedback linearization technique. For closed-loop control, the linear-quadratic regulator (LQR) and the linear-quadratic gaussian (LQG) regulator are invoked to design a controller for tracking prespecified steady states. In the feedback linearization technique, a global diffeomorphism function is proposed that facilitates in achieving the regulation requirement. The robustness of the regulated GG pathway is studied considering input perturbation and with measurement noise.

Flux analysis and metabolomics for systematic metabolic engineering of microorganisms

Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and (13)C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering.

Combined effect of loss of the caa3 oxidase and Crp regulation drives Shewanella to thrive in redox-stratified environments

Shewanella species are a group of facultative Gram-negative microorganisms with remarkable respiration abilities that allow the use of a diverse array of terminal electron acceptors (EA). Like most bacteria, S. oneidensis possesses multiple terminal oxidases, including two heme-copper oxidases (caa3- and cbb3-type) and a bd-type quinol oxidase. As aerobic respiration is energetically favored, mechanisms underlying the fact that these microorganisms thrive in redox-stratified environments remain vastly unexplored. In this work, we discovered that the cbb3-type oxidase is the predominant system for respiration of oxygen (O2), especially when O2 is abundant. Under microaerobic conditions, the bd-type quinol oxidase has a significant role in addition to the cbb3-type oxidase. In contrast, multiple lines of evidence suggest that under test conditions the caa3-type oxidase, an analog to the mitochondrial enzyme, has no physiological significance, likely because of its extremely low expression. In addition, expression of both cbb3- and bd-type oxidases is under direct control of Crp (cAMP receptor protein) but not the well-established redox regulator Fnr (fumarate nitrate regulator) of canonical systems typified in Escherichia coli. These data, collectively, suggest that adaptation of S. oneidensis to redox-stratified environments is likely due to functional loss of the caa3-type oxidase and switch of the regulatory system for respiration.

Genome-wide analysis of redox reactions reveals metabolic engineering targets for D-lactate overproduction in Escherichia coli

Most current metabolic engineering applications rely on the inactivation of unwanted reactions and the amplification of product-oriented reactions. All of the biochemical reactions involved with cellular metabolism are tightly coordinated with the electron flow, which depends on the cellular energy status. Thus, the cellular metabolic flux can be controlled either by modulation of the electron flow or the regulation of redox reactions. This study analyzed the genome-wide anaerobic fermentation products of 472 Escherichia coli single gene knockouts, which comprised mainly of dehydrogenases, oxidoreductases, and redox-related proteins. Many metabolic pathways that were located far from anaerobic mixed-acid fermentation significantly affected the profiles of lactic acid, succinic acid, acetic acid, formic acid, and ethanol. Unexpectedly, D-lactate overproduction was determined by a single gene deletion in dehydrogenases (e.g., guaB, pyrD, and serA) involved with nucleotide and amino acid metabolism. Furthermore, the combined knockouts of guaB, pyrD, serA, fnr, arcA, or arcB genes, which are involved with anaerobic transcription regulation, enhanced D-lactate overproduction. These results suggest that the anaerobic fermentation profiles of E. coli can be tuned via the disruption of peripheral dehydrogenases in anaerobic conditions.

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.

Metabolic regulation analysis of wild-type and arcA mutant Escherichia coli under nitrate conditions using different levels of omics data

It is of practical interest to investigate the effect of nitrates on bacterial metabolic regulation of both fermentation and energy generation, as compared to aerobic and anaerobic growth without nitrates. Although gene level regulation has previously been studied for nitrate assimilation, it is important to understand this metabolic regulation in terms of global regulators. In the present study, therefore, we measured gene expression using DNA microarrays, intracellular metabolite concentrations using CE-TOFMS, and metabolic fluxes using the (13)C-labeling technique for wild-type E. coli and the ΔarcA (a global regulatory gene for anoxic response control, ArcA) mutant to compare the metabolic state under nitrate conditions to that under aerobic and anaerobic conditions without nitrates in continuous culture conditions at a dilution rate of 0.2 h(-1). In wild-type, although the measured metabolite concentrations changed very little among the three culture conditions, the TCA cycle and the pentose phosphate pathway fluxes were significantly different under each condition. These results suggested that the ATP production rate was 29% higher under nitrate conditions than that under anaerobic conditions, whereas the ATP production rate was 10% lower than that under aerobic conditions. The flux changes in the TCA cycle were caused by changes in control at the gene expression level. In ΔarcA mutant, the TCA cycle flux was significantly increased (4.4 times higher than that of the wild type) under nitrate conditions. Similarly, the intracellular ATP/ADP ratio increased approximately two-fold compared to that of the wild-type strain.

Quantitative iTRAQ LC-MS/MS proteomics reveals metabolic responses to biofuel ethanol in cyanobacterial Synechocystis sp. PCC 6803

Recent progress in metabolic engineering has led to autotrophic production of ethanol in various cyanobacterial hosts. However, cyanobacteria are known to be sensitive to ethanol, which restricts further efforts to increase ethanol production levels in these renewable host systems. To understand the mechanisms of ethanol tolerance so that engineering more robust cyanobacterial hosts can be possible, in this study, the responses of model cyanobacterial Synechocystis sp. PCC 6803 to ethanol were determined using a quantitative proteomics approach with iTRAQ LC-MS/MS technologies. The resulting high-quality proteomic data set consisted of 24,887 unique peptides corresponding to 1509 identified proteins, a coverage of approximately 42% of the predicted proteins in the Synechocystis genome. Using a cutoff of 1.5-fold change and a p-value less than 0.05, 135 and 293 unique proteins with differential abundance levels were identified between control and ethanol-treated samples at 24 and 48 h, respectively. Functional analysis showed that the Synechocystis cells employed a combination of induced common stress response, modifications of cell membrane and envelope, and induction of multiple transporters and cell mobility-related proteins as protection mechanisms against ethanol toxicity. Interestingly, our proteomic analysis revealed that proteins related to multiple aspects of photosynthesis were up-regulated in the ethanol-treated Synechocystis cells, consistent with increased chlorophyll a concentration in the cells upon ethanol exposure. The study provided the first comprehensive view of the complicated molecular mechanisms against ethanol stress and also provided a list of potential gene targets for further engineering ethanol tolerance in Synechocystis PCC 6803.

Current trends in trichloroethylene biodegradation: a review

Over the past few years biodegradation of trichloroethylene (TCE) using different microorganisms has been investigated by several researchers. In this review article, an attempt has been made to present a critical summary of the recent results related to two major processes--reductive dechlorination and aerobic co-metabolism used for TCE biodegradation. It has been shown that mainly Clostridium sp. DC-1, KYT-1, Dehalobacter, Dehalococcoides, Desulfuromonas, Desulfitobacterium, Propionibacterium sp. HK-1, and Sulfurospirillum bacterial communities are responsible for the reductive dechlorination of TCE. Efficacy of bacterial communities like Nitrosomonas, Pseudomonas, Rhodococcus, and Xanthobacter sp. etc. for TCE biodegradation under aerobic conditions has also been examined. Mixed cultures of diazotrophs and methanotrophs have been used for TCE degradation in batch and continuous cultures (biofilter) under aerobic conditions. In addition, some fungi (Trametes versicolor, Phanerochaete chrysosporium ME-446) and Actinomycetes have also been used for aerobic biodegradation of TCE. The available information on kinetics of biofiltration of TCE and its degradation end-products such as CO2 are discussed along with the available results on the diversity of bacterial community obtained using molecular biological approaches. It has emerged that there is a need to use metabolic engineering and molecular biological tools more intensively to improve the robustness of TCE degrading microbial species and assess their diversity.

Proteomic analysis reveals resistance mechanism against biofuel hexane in Synechocystis sp. PCC 6803

BACKGROUND

Recent studies have demonstrated that photosynthetic cyanobacteria could be an excellent cell factory to produce renewable biofuels and chemicals due to their capability to utilize solar energy and CO2 as the sole energy and carbon sources. Biosynthesis of carbon-neutral biofuel alkanes with good chemical and physical properties has been proposed. However, to make the process economically feasible, one major hurdle to improve the low cell tolerance to alkanes needed to be overcome.

RESULTS

Towards the goal to develop robust and high-alkane-tolerant hosts, in this study, the responses of model cyanobacterial Synechocystis PCC 6803 to hexane, a representative of alkane, were investigated using a quantitative proteomics approach with iTRAQ - LC-MS/MS technologies. In total, 1,492 unique proteins were identified, representing about 42% of all predicted protein in the Synechocystis genome. Among all proteins identified, a total of 164 and 77 proteins were found up- and down-regulated, respectively. Functional annotation and KEGG pathway enrichment analyses showed that common stress responses were induced by hexane in Synechocystis. Notably, a large number of transporters and membrane-bound proteins, proteins against oxidative stress and proteins related to sulfur relay system and photosynthesis were induced, suggesting that they are possibly the major protection mechanisms against hexane toxicity.

CONCLUSION

The study provided the first comprehensive view of the complicated molecular mechanism employed by cyanobacterial model species, Synechocystis to defend against hexane stress. The study also provided a list of potential targets to engineer Synechocystis against hexane stress.

Microbial metabolomics

Microbial metabolomics constitutes an integrated component of systems biology. By studying the complete set of metabolites within a microorganism and monitoring the global outcome of interactions between its development processes and the environment, metabolomics can potentially provide a more accurate snap shot of the actual physiological state of the cell. Recent advancement of technologies and post-genomic developments enable the study and analysis of metabolome. This unique contribution resulted in many scientific disciplines incorporating metabolomics as one of their “omics” platforms. This review focuses on metabolomics in microorganisms and utilizes selected topics to illustrate its impact on the understanding of systems microbiology.

A modified Cre-lox genetic switch to dynamically control metabolic flow in Saccharomyces cerevisiae

The control of metabolic flow is a prerequisite for efficient chemical production in transgenic microorganisms. Exogenous genes required for the biosynthesis of target chemicals are expressed under strong promoters, while the endogenous genes of the original metabolic pathway are repressed by disruption or mutation. These genetic manipulations occasionally cause harmful effects to the host. In the lactate-producing yeast Saccharomyces cerevisiae, where endogenous pyruvate decarboxylase (PDC) is disrupted and exogenous lactate dehydrogenase (LDH) is introduced, PDC deletion is extremely detrimental to cell growth but is required for efficient production of lactate. A suitable means to dynamically control the metabolic flow from ethanol fermentation during the growth phase to lactate fermentation during the production phase is needed. Here, we demonstrated that this flow can be controlled by the exclusive expression of PDC and LDH with a Cre-lox genetic switch. This switch was evaluated with a gene cassette that encoded two different fluorescence proteins and enabled changes in genotype and phenotype within 2 and 10 h, respectively. Transgenic yeast harboring this switch and the PDC-LDH cassette showed a specific growth rate (0.45 h (-1)) that was almost the same as that of wild-type (0.47 h (-1)). Upon induction of the genetic switch, the transgenic yeast produced lactate from up to 85.4% of the glucose substrate, while 91.7% of glucose went to ethanol before induction. We thus propose a "metabolic shift" concept that can serve as an alternative means to obtain gene products that are currently difficult to obtain by using conventional methodologies.

Truncated branch and bound achieves efficient constraint-based genetic design

MOTIVATION

Computer-aided genetic design is a promising approach to a core problem of metabolic engineering-that of identifying genetic manipulation strategies that result in engineered strains with favorable product accumulation. This approach has proved to be effective for organisms including Escherichia coli and Saccharomyces cerevisiae, allowing for rapid, rational design of engineered strains. Finding optimal genetic manipulation strategies, however, is a complex computational problem in which running time grows exponentially with the number of manipulations (i.e. knockouts, knock-ins or regulation changes) in the strategy. Thus, computer-aided gene identification has to date been limited in the complexity or optimality of the strategies it finds or in the size and level of detail of the metabolic networks under consideration.

RESULTS

Here, we present an efficient computational solution to the gene identification problem. Our approach significantly outperforms previous approaches--in seconds or minutes, we find strategies that previously required running times of days or more.

AVAILABILITY AND IMPLEMENTATION

GDBB is implemented using MATLAB and is freely available for non-profit use at http://crab.rutgers.edu/~dslun/gdbb.

A quantitative comparison of Calvin-Benson cycle models

The Calvin-Benson cycle (CBC) provides the precursors for biomass synthesis necessary for plant growth. The dynamic behavior and yield of the CBC depend on the environmental conditions and regulation of the cellular state. Accurate quantitative models hold the promise of identifying the key determinants of the tightly regulated CBC function and their effects on the responses in future climates. We provide an integrative analysis of the largest compendium of existing models for photosynthetic processes. Based on the proposed ranking, our framework facilitates the discovery of best-performing models with regard to metabolomics data and of candidates for metabolic engineering.

Regulatory and metabolic network of rhamnolipid biosynthesis: traditional and advanced engineering towards biotechnological production

During the last decade, the demand for economical and sustainable bioprocesses replacing petrochemical-derived products has significantly increased. Rhamnolipids are interesting biosurfactants that might possess a broad industrial application range. However, despite of 60 years of research in the area of rhamnolipid production, the economic feasibility of these glycolipids is pending. Although the biosynthesis and regulatory network are in a big part known, the actual incidents on the cellular and process level during bioreactor cultivation are not mastered. Traditional engineering by random and targeted genetic alteration, process design, and recombinant strategies did not succeed by now. For enhanced process development, there is an urgent need of in-depth information about the rhamnolipid production regulation during bioreactor cultivation to design knowledge-based genetic and process engineering strategies. Rhamnolipids are structurally comparable, simple secondary metabolites and thus have the potential to become instrumental in future secondary metabolite engineering by systems biotechnology. This review summarizes current knowledge about the regulatory and metabolic network of rhamnolipid synthesis and discusses traditional and advanced engineering strategies performed for rhamnolipid production improvement focusing on Pseudomonas aeruginosa. Finally, the opportunities of applying the systems biotechnology toolbox on the whole-cell biocatalyst and bioprocess level for further rhamnolipid production optimization are discussed.

Physiological roles of ArcA, Crp, and EtrA and their interactive control on aerobic and anaerobic respiration in Shewanella oneidensis

In the genome of Shewanella oneidensis, genes encoding the global regulators ArcA, Crp, and EtrA have been identified. All these proteins deviate from their counterparts in E. coli significantly in terms of functionality and regulon. It is worth investigating the involvement and relationship of these global regulators in aerobic and anaerobic respiration in S. oneidensis. In this study, the impact of the transcriptional factors ArcA, Crp, and EtrA on aerobic and anaerobic respiration in S. oneidensis were assessed. While all these proteins appeared to be functional in vivo, the importance of individual proteins in these two major biological processes differed. The ArcA transcriptional factor was critical in aerobic respiration while the Crp protein was indispensible in anaerobic respiration. Using a newly developed reporter system, it was found that expression of arcA and etrA was not influenced by growth conditions but transcription of crp was induced by removal of oxygen. An analysis of the impact of each protein on transcription of the others revealed that Crp expression was independent of the other factors whereas ArcA repressed both etrA and its own transcription while EtrA also repressed arcA transcription. Transcriptional levels of arcA in the wild type, crp, and etrA strains under either aerobic or anaerobic conditions were further validated by quantitative immunoblotting with a polyclonal antibody against ArcA. This extensive survey demonstrated that all these three global regulators are functional in S. oneidensis. In addition, the reporter system constructed in this study will facilitate in vivo transcriptional analysis of targeted promoters.

Metabolic engineering of Escherichia coli for biotechnological production of high-value organic acids and alcohols

Confronted with the gradual and inescapable exhaustion of the earth's fossil energy resources, the bio-based process to produce platform chemicals from renewable carbohydrates is attracting growing interest. Escherichia coli has been chosen as a workhouse for the production of many valuable chemicals due to its clear genetic background, convenient to be genetically modified and good growth properties with low nutrient requirements. Rational strain development of E. coli achieved by metabolic engineering strategies has provided new processes for efficiently biotechnological production of various high-value chemical building blocks. Compared to previous reviews, this review focuses on recent advances in metabolic engineering of the industrial model bacteria E. coli that lead to efficient recombinant biocatalysts for the production of high-value organic acids like succinic acid, lactic acid, 3-hydroxypropanoic acid and glucaric acid as well as alcohols like 1,3-propanediol, xylitol, mannitol, and glycerol with the discussion of the future research in this area. Besides, this review also discusses several platform chemicals, including fumaric acid, aspartic acid, glutamic acid, sorbitol, itaconic acid, and 2,5-furan dicarboxylic acid, which have not been produced by E. coli until now.

Use of genome-scale metabolic models for understanding microbial physiology

The exploitation of microorganisms in industrial, medical, food and environmental biotechnology requires a comprehensive understanding of their physiology. The availability of genome sequences and accumulation of high-throughput data allows gaining understanding of microbial physiology at the systems level, and genome-scale metabolic models represent a valuable framework for integrative analysis of metabolism of microorganisms. Genome-scale metabolic models are reconstructed based on a combination of genome sequence information and detailed biochemical information, and these reconstructed models can be used for analyzing and simulating the operation of metabolism in response to different stimuli. Here we discuss the requirement for having detailed physiological insight in order to exploit microorganisms for production of fuels, chemicals and pharmaceuticals. We further describe the reconstruction process of genome-scale metabolic models and different algorithms that can be used to apply these models to gain improved insight into microbial physiology.

Metabolic and transcriptional response to cofactor perturbations in Escherichia coli

Metabolic cofactors such as NADH and ATP play important roles in a large number of cellular reactions, and it is of great interest to dissect the role of these cofactors in different aspects of metabolism. Toward this goal, we overexpressed NADH oxidase and the soluble F1-ATPase in Escherichia coli to lower the level of NADH and ATP, respectively. We used a global interaction network, comprising of protein interactions, transcriptional regulation, and metabolic networks, to integrate data from transcription profiles, metabolic fluxes, and the metabolite levels. We identified high-scoring networks for the two strains. The results revealed a smaller, but denser network for perturbations of ATP level, compared with that of NADH level. The action of many global transcription factors such as ArcA, Fnr, CRP, and IHF commonly involved both NADH and ATP, whereas others responded to either ATP or NADH. Overexpressing NADH oxidase invokes response in widespread aspects of metabolism involving the redox cofactors (NADH and NADPH), whereas ATPase has a more focused response to restore ATP level by enhancing proton translocation mechanisms and repressing biosynthesis. Interestingly, NADPH played a key role in restoring redox homeostasis through the concerted activity of isocitrate dehydrogenase and UdhA transhydrogenase. We present a reconciled network of regulation that illustrates the overlapping and distinct aspects of metabolism controlled by NADH and ATP. Our study contributes to the general understanding of redox and energy metabolism and should help in developing metabolic engineering strategies in E. coli.

Industrial systems biology

The chemical industry is currently undergoing a dramatic change driven by demand for developing more sustainable processes for the production of fuels, chemicals, and materials. In biotechnological processes different microorganisms can be exploited, and the large diversity of metabolic reactions represents a rich repository for the design of chemical conversion processes that lead to efficient production of desirable products. However, often microorganisms that produce a desirable product, either naturally or because they have been engineered through insertion of heterologous pathways, have low yields and productivities, and in order to establish an economically viable process it is necessary to improve the performance of the microorganism. Here metabolic engineering is the enabling technology. Through metabolic engineering the metabolic landscape of the microorganism is engineered such that there is an efficient conversion of the raw material, typically glucose, to the product of interest. This process may involve both insertion of new enzymes activities, deletion of existing enzyme activities, but often also deregulation of existing regulatory structures operating in the cell. In order to rapidly identify the optimal metabolic engineering strategy the industry is to an increasing extent looking into the use of tools from systems biology. This involves both x-ome technologies such as transcriptome, proteome, metabolome, and fluxome analysis, and advanced mathematical modeling tools such as genome-scale metabolic modeling. Here we look into the history of these different techniques and review how they find application in industrial biotechnology, which will lead to what we here define as industrial systems biology.

Ethanol synthesis from glycerol by Escherichia coli redox mutants expressing adhE from Leuconostoc mesenteroides

AIMS

Analysis of the physiology and metabolism of Escherichia coli arcA and creC mutants expressing a bifunctional alcohol-acetaldehyde dehydrogenase from Leuconostoc mesenteroides growing on glycerol under oxygen-restricted conditions. The effect of an ldhA mutation and different growth medium modifications was also assessed.

METHODS AND RESULTS

Expression of adhE in E. coli CT1061 [arcA creC(Con)] resulted in a 1.4-fold enhancement in ethanol synthesis. Significant amounts of lactate were produced during micro-oxic cultures and strain CT1061LE, in which fermentative lactate dehydrogenase was deleted, produced up to 6.5 +/- 0.3 g l(-1) ethanol in 48 h. Escherichia coli CT1061LE derivatives resistant to >25 g l(-1) ethanol were obtained by metabolic evolution. Pyruvate and acetaldehyde addition significantly increased both biomass and ethanol concentrations, probably by overcoming acetyl-coenzyme A (CoA) shortage. Yeast extract also promoted growth and ethanol synthesis, and this positive effect was mainly attributable to its vitamin content. Two-stage bioreactor cultures were conducted in a minimal medium containing 100 microg l(-1) calcium d-pantothenate to evaluate oxic acetyl-CoA synthesis followed by a switch into fermentative conditions. Ethanol reached 15.4 +/- 0.9 g l(-1) with a volumetric productivity of 0.34 +/- 0.02 g l(-1) h(-1).

CONCLUSIONS

Escherichia coli responded to adhE over-expression by funnelling carbon and reducing equivalents into a highly reduced metabolite, ethanol. Acetyl-CoA played a key role in micro-oxic ethanol synthesis and growth.

SIGNIFICANCE AND IMPACT OF THE STUDY

Insight into the micro-oxic metabolism of E. coli growing on glycerol is essential for the development of efficient industrial processes for reduced biochemicals production from this substrate, with special relevance to biofuels synthesis.