ABSTRACT
Graph-theory-based pathway analysis is a commonly used method for pathway searching in genome-scale metabolic networks. However, such searching often results in many pathways biologically infeasible due to the presence of currency metabolites (e.g. H+, H2O, CO2, ATP etc.). Several methods have been proposed to address the problem but up to now there is no well-recognized methods for processing the currency metabolites. In this study, we proposed a new method based on the function of currency metabolites for transferring of functional groups such as phosphate. We processed most currency metabolites as pairs rather than individual metabolites, and ranked the pairs based on their importance in transferring functional groups, in order to make sure at least one main metabolite link exists for any reaction. The whole process can be done automatically by programming. Comparison with existing approaches indicates that more biologically infeasible pathways were removed by our method and the calculated pathways were more reliable, which may facilitate the graph-theory-based pathway design and visualization.
Subject(s)
Genome , Metabolic Networks and PathwaysABSTRACT
It is among the goals in metabolic engineering to construct microbial cell factories producing high-yield and high value-added target products, and an important solution is to design efficient synthetic pathway for the target products. However, due to the difference in metabolic capacity among microbial chassises, the available substrate and the yielded products are limited. Therefore, it is urgent to design related metabolic pathways to improve the production capacity. Existing metabolic engineering approaches to designing heterologous pathways are mainly based on biological experience, which are inefficient. Moreover, the yielded results are in no way comprehensive. However, systems biology provides new methods for heterologous pathway design, particularly the graph-based and constraint-based methods. Based on the databases containing rich metabolism information, they search for and uncover possible metabolic pathways with designated strategy (graph-based method) or algorithm (constraint-based method) and then screen out the optimal pathway to guide the modification of strains. In this paper, we reviewed the databases and algorithms for pathway design, and the applications in metabolic engineering and discussed the strengths and weaknesses of existing algorithms in practical application, hoping to provide a reference for the selection of optimal methods for the design of product synthesis pathway.
Subject(s)
Algorithms , Biosynthetic Pathways , Metabolic Engineering , Metabolic Networks and Pathways/genetics , Systems BiologyABSTRACT
Constraint-based genome-scale metabolic network models (genome-scale metabolic models, GEMs) have been widely used to predict metabolic phenotypes. In addition to stoichiometric constraints, other constraints such as enzyme availability and thermodynamic feasibility may also limit the cellular phenotype solution space. Recently, extended GEM models considering either enzymatic or thermodynamic constraints have been developed to improve model prediction accuracy. This review summarizes the recent progresses on metabolic models with multiple constraints (MCGEMs). We presented the construction methods and various applications of MCGEMs including the simulation of gene knockout, prediction of biologically feasible pathways and identification of bottleneck steps. By integrating multiple constraints in a consistent modeling framework, MCGEMs can predict the metabolic bottlenecks and key controlling and modification targets for pathway optimization more precisely, and thus may provide more reliable design results to guide metabolic engineering of industrially important microorganisms.
Subject(s)
Genome , Metabolic Engineering , Metabolic Networks and Pathways/genetics , Models, Biological , ThermodynamicsABSTRACT
Abstract The evolution of species is inevitably accompanied by the evolution of metabolic networks to adapt to different environments. The metabolic networks of different species were collected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) website, and some enzyme reactions with the highest occurrence frequency in all species were found and are reported in this paper. The correlation coefficients of whether the enzyme reactions appear in all species were calculated, and the corresponding evolutionary correlation connection networks were calculated according to different correlation coefficient thresholds. These studies show that, as the evolutionary correlation of enzyme reactions increases, the weighted average of the mean functional concentration ratios of the enzyme reactions also increases, indicating that the functional concentration ratio of enzyme reactions has a certain correlation with the evolutionary correlation. The work presented in this paper enhances our understanding of the characteristics and general rules of metabolic network evolution.
Subject(s)
Enzyme Activation , Metabolic Networks and Pathways , Adaptation, Biological , MetabolismABSTRACT
Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) was used to investigate the metabolites of maackiain in rats based on the prediction function of UNIFI data processing system and liver microsomal incubation in vitro. Ten metabolites of maackiain after oral absorption were reasonably deduced and characterized. It was found that the biotransformation of maackiain mainly included phase Ⅰ oxidation, dehydrogenation, phase Ⅱ sulfate conjugation, glucosylation conjugation, and glucuronic acid conjugation. Among them, the product of glucosylation conjugation, trifolirhizin, was identified by comparison with the reference for the first time. Liver microsomal incubation in vitro further confirmed the metabolites and metabolic pathways of maackiain in rats. The metabolites in the blood, urine, and feces complemented each other, which revealed the migration, metabolism, and excretion modes of maackiain in rats. This study lays a foundation for the further investigation of the metabolic mechanism of maackiain in vivo and the in-depth research on the mechanism of pharmacodynamics and toxicity.
Subject(s)
Animals , Chromatography, High Pressure Liquid , Chromatography, Liquid , Metabolic Networks and Pathways , Pterocarpans , Rats , Rats, Sprague-DawleyABSTRACT
Cancer development is a complicated process controlled by the interplay of multiple signaling pathways and restrained by oxygen and nutrient accessibility in the tumor microenvironment. High plasticity in using diverse nutrients to adapt to metabolic stress is one of the hallmarks of cancer cells. To respond to nutrient stress and to meet the requirements for rapid cell proliferation, cancer cells reprogram metabolic pathways to take up more glucose and coordinate the production of energy and intermediates for biosynthesis. Such actions involve gene expression and activity regulation by the moonlighting function of oncoproteins and metabolic enzymes. The signal - moonlighting protein - metabolism axis facilitates the adaptation of tumor cells under varying environment conditions and can be therapeutically targeted for cancer treatment.
Subject(s)
Energy Metabolism , Epigenesis, Genetic , Humans , Metabolic Networks and Pathways , Neoplasms/genetics , Tumor MicroenvironmentABSTRACT
Synthetic biology and metabolic engineering have been widely used to construct microbial cell factories for efficient production of bio-based chemicals, which mainly focus on the modification and regulation of metabolic pathways. The characteristics of microorganisms themselves, e.g. morphology, have rarely been taken into consideration in the biotechnological production processes. Morphology engineering aims to control cell shapes and cell division patterns by manipulating the genes related to cell morphology, providing a new strategy for developing efficient microbial cell factories. This review summarized the proteins related to cell morphology, followed by illustrating a few examples of using morphology engineering strategies for improving production of bio-based chemicals. This includes increasing intracellular product accumulation by regulating cell size, enhancing extracellular secretion of target products by improving cell permeability, reducing production cost by achieving high cell density, and improving product performance by controlling the degree of product hydrolysis. Finally, challenges and perspectives for the development of morphology engineering were discussed.
Subject(s)
Biotechnology , Metabolic Engineering , Metabolic Networks and Pathways , Synthetic BiologyABSTRACT
As an important model industrial microorganism, Escherichia coli has been widely used in pharmaceutical, chemical industry and agriculture. In the past 30 years, a variety of new strategies and techniques, including artificial intelligence, gene editing, metabolic pathway assembly, and dynamic regulation have been used to design, construct, and optimize E. coli cell factories, which remarkably improved the efficiency for biotechnological production of chemicals. In this review, three key aspects for constructing E. coli cell factories, including pathway design, pathway assembly and regulation, and optimization of global cellular performance, are summarized. The technologies that have played important roles in metabolic engineering of E. coli, as well as their future applications, are discussed.
Subject(s)
Artificial Intelligence , Escherichia coli/genetics , Gene Editing , Metabolic Engineering , Metabolic Networks and Pathways/geneticsABSTRACT
The regulation of the expression of genes involved in metabolic pathways, termed as metabolic regulation, is vital to construct efficient microbial cell factories. With the continuous breakthroughs in synthetic biology, the mining and artificial design of high-quality regulatory elements have substantially improved our ability to modify and regulate cellular metabolic networks and its activities. The research on metabolic regulation has also evolved from the static regulation of single genes to the intelligent and precise dynamic regulation at the systems level. This review briefly summarizes the advances of metabolic regulation technologies in the past 30 years.
Subject(s)
Metabolic Engineering , Metabolic Networks and Pathways/genetics , Synthetic BiologyABSTRACT
Genome-scale metabolic network model (GSMM) is becoming an important tool for studying cellular metabolic characteristics, and remarkable advances in relevant theories and methods have been made. Recently, various constraint-based GSMMs that integrated genomic, transcriptomic, proteomic, and thermodynamic data have been developed. These developments, together with the theoretical breakthroughs, have greatly contributed to identification of target genes, systems metabolic engineering, drug discovery, understanding disease mechanism, and many others. This review summarizes how to incorporate transcriptomic, proteomic, and thermodynamic-constraints into GSMM, and illustrates the shortcomings and challenges of applying each of these methods. Finally, we illustrate how to develop and refine a fully integrated GSMM by incorporating transcriptomic, proteomic, and thermodynamic constraints, and discuss future perspectives of constraint-based GSMM.
Subject(s)
Genome/genetics , Metabolic Engineering , Metabolic Networks and Pathways/genetics , Models, Biological , ProteomicsABSTRACT
In 1990s, Bailey and Stephanopoulos put forward the concept of classic metabolic engineering, aiming to use DNA recombination technology to rewire metabolic network to achieve improved cell performance and increased target products. In the last 30 years since the birth of metabolic engineering, life science have flourished, and new disciplines such as genomics, systems biology and synthetic biology have emerged, injecting new connotations and vitality into the development of metabolic engineering. Classic metabolic engineering research has entered into an unprecedented stage of systems metabolic engineering. The application of synthetic biology tools and strategies, such as omics technology, genomic-scale metabolic model, parts assembly, circuits design, dynamic control, genome editing and many others, have greatly improved the design, build, and rewiring capabilities of complex metabolism. The intervention of machine learning and the combination of evolutionary engineering and metabolic engineering will further promote the development of systems metabolic engineering. This paper analyzes the development of metabolic engineering in the past 30 years and summarizes the novel theories, techniques, strategies, and applications of metabolic engineering that have emerged over the past 30 years.
Subject(s)
Gene Editing , Metabolic Engineering , Metabolic Networks and Pathways/genetics , Synthetic Biology , Systems BiologyABSTRACT
Microbial cell factories capable of producing valuable chemicals from renewable feedstocks provide a promising alternative towards sustainability. However, environmental stress remarkably affects the performance of microbial cell factories. By extending the chronological lifespan of microbial cells, the performance of microbial cell factories can be greatly improved. Firstly, an evaluation system for chronological lifespan and semi-chronological lifespan was established based on the changes in survival rates. Secondly, the addition of anti-aging drugs such as cysteine, carnosine, aminoguanidine and glucosamine increased the chronological lifespan of E. coli by 80%, 80%, 50% and 120%, respectively. Finally, we demonstrated that extending the chronological lifespan of E. coli increased the yield of metabolites produced by E. coli cell factories with endogenous (lactic acid and pyruvic acid) or exogenous (malic acid) metabolic pathway by 30.0%, 25.0%, and 27.0%, respectively. The strategy of extending chronological lifespan of E. coli provides a potential approach for enhancing the performance of microbial cell factories.
Subject(s)
Escherichia coli/genetics , Lactic Acid , Longevity , Metabolic Engineering , Metabolic Networks and PathwaysABSTRACT
Genome-scale metabolic network model (GSMM) is an extremely important guiding tool in the targeted modification of industrial microbial strains, which helps researchers to quickly obtain industrial microbes with specific traits and has attracted increasing attention. Here we reviewe the development history of GSMM and summarized the construction method of GSMM. Furthermore, the development and application of GSMM in industrial microorganisms are elaborated by using four typical industrial microorganisms (Bacillus subtilis, Escherichia coli, Corynebacterium glutamicum, and Saccharomyces cerevisiae) as examples. In addition, prospects in the development trend of GSMM are proposed.
Subject(s)
Corynebacterium glutamicum/genetics , Escherichia coli/genetics , Metabolic Engineering , Metabolic Networks and Pathways/geneticsABSTRACT
Based on observing the cytological characteristics of the flower buds of the functional male sterile line (S13) and the fertile line (F142) in eggplant, it was found that the disintegration period of the annular cell clusters in S13 anther was 2 days later than that of F142, and the cells of stomiun tissue and tapetum in F142 disintegrated on the blooming day, while it did not happen in S13. The comparative transcriptomic analysis showed that there were 1 436 differential expression genes (DEGs) (651 up-regulated and 785 down-regulated) in anthers of F142 and S13 at 8, 5 days before flowering and flowering day. The significance analysis of GO enrichment indicated that there were more unigene clusters involved in single cell biological process, metabolism process and cell process, and more catalytic activity and binding function were involved in molecular functions. Through KEGG annotation we found that the common DEGs were mainly enriched in the biosynthesis of secondary metabolites, metabolic pathway, protein processing in endoplasmic reticulum, biosynthesis of amino acids, carbon metabolism and plant hormone signal transduction. The fifteen genes co-expression modules were identified from 16 465 selected genes by weighted gene co-expression network analysis (WGCNA), three of which (Plum2, Royalblue and Bisque4 modules) were highly related to S13 during flower development. KEGG enrichment showed that the specific modules could be enriched in phenylpropanoid biosynthesis, photosynthesis, porphyrin and chlorophyll metabolism, α-linolenic acid metabolism, polysaccharide biosynthesis and metabolism, fatty acid degradation and the mutual transformation of pentose and glucuronic acid. These genes might play important roles during flower development of S13. It provided a reference for further study on the mechanism of anther dehiscence in eggplant.
Subject(s)
Flowers/genetics , Gene Expression Profiling , Gene Expression Regulation, Plant , Humans , Infertility, Male , Male , Metabolic Networks and Pathways/genetics , Solanum melongena/genetics , Transcriptome/geneticsABSTRACT
Numerous studies showed that the growth of medicinal plants in their native areas was simultaneously affected by abiotic stress combinations. Compared with single stress, plants have unique responses to a combination of different abiotic stresses and cannot be inferred directly from plants' responses to each individual stress. The effect of combined stresses on plants usually has three types of synergistic antagonism or independence. The secondary metabolism in the process of medicinal plant stress combination response also played a vital role, and environmental stresses can spur the accumulation of secondary metabolites, but under the stress combination, plants induce specific gene expression of key enzymes on secondary metabolic pathways, in turn, the accumulation of secondary metabolites against stress is formed. When plants are subjected to stress combination, the interaction of multiple signaling pathways makes it highly complex for plants to respond to stress combination. This paper summarized the effects of stress combination on physiological and secondary metabolism of medicinal plants, and discussed the related physiological, biochemical and molecular mechanisms. It provides theoretical basis for improving the adaptability of medicinal plants to adversity, improving the quality of Chinese medicinal materials, and further optimizing the cultivation of medicinal plants.
Subject(s)
Gene Expression Regulation, Plant , Metabolic Networks and Pathways , Plants, Medicinal , Secondary Metabolism , Stress, PhysiologicalABSTRACT
As an important platform compound, 3-hydroxypropionic acid (3-HP) can be used as a substrate to synthesize a variety of biological products with commercial potential. The titer of 3-HP by wild-type bacteria is low, which severely limits the large-scale application and production of 3-HP. By modifying the genes related to the metabolic pathway, engineered bacteria using cheap substrates as carbon sources are constructed, the aim of reducing production cost and increasing output is realized. In this paper, the recent progress in the synthesis of 3-HP by metabolic engineering at home and abroad is reviewed. The advantages and disadvantages of glycerol pathway, malonyl-CoA pathway and beta-alanine pathway for synthesis of 3-HP are also summarized and analyzed, and the future development of 3-HP is prospected.
Subject(s)
Glycerol , Metabolism , Industrial Microbiology , Lactic Acid , Metabolic Engineering , Metabolic Networks and Pathways , GeneticsABSTRACT
Glutamic acid is an important amino acid with wide range of applications and huge market demand. Therefore, by performing transcriptome sequencing and re-sequencing analysis on Corynebacterium glutamicum E01 and high glutamate-producing strain C. glutamicum G01, we identified and selected genes with significant differences in transcription and gene levels in the central metabolic pathway that may have greatly influenced glutamate synthesis and further increased glutamic acid yield. The oxaloacetate node and α-ketoglutarate node play an important role in glutamate synthesis. The oxaloacetate node and α-ketoglutarate node were studied to explore effect on glutamate production. Based on the integrated strain constructed from the above experimental results, the growth rate in a 5-L fermenter was slightly lower than that of the original strain, but the glutamic acid yield after 48 h reached (136.1±5.53) g/L, higher than the original strain (93.53±4.52) g/L, an increase by 45.5%; sugar-acid conversion rate reached 58.9%, an increase of 13.7% compared to 45.2% of the original strain. The application of the above experimental strategy improved the glutamic acid yield and the sugar-acid conversion rate, and provided a theoretical basis for the metabolic engineering of Corynebacterium glutamicum.
Subject(s)
Citric Acid Cycle , Corynebacterium glutamicum/metabolism , Glutamic Acid/metabolism , Metabolic Engineering , Metabolic Networks and Pathways/geneticsABSTRACT
Objective@#To explore potential serum biomarkers of children with Kashin-Beck Disease (KBD) and the metabolic pathways to which the biomarkers belong.@*Methods@#A two-stage metabolomic study was employed. The discovery cohort included 56 patients, 51 internal controls, and 50 external controls. The metabolites were determined by HPLC-(Q-TOF)-MS and confirmed by Human Metabolome Databases (HMDB) and Metlin databases. MetaboAnalyst 3.0 and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were used to analyze the metabolic pathways of the candidate metabolites. The use of HPLC-(Q-TRAP)-MS enabled quantitative detection of the target metabolites which were chosen using the discovery study and verified in another independent verification cohort of 31 patients, 41 internal controls, and 50 external controls.@*Results@#Eight candidate metabolites were identified out in the discovery study, namely kynurenic acid, N-α-acetylarginine, 6-hydroxymelatonin, sphinganine, ceramide, sphingosine-1P, spermidine, and glycine. These metabolites exist in sphingolipid, glutathione, and tryptophan metabolic pathways. In the second-stage study, five candidate metabolites were validated, including kynurenic acid, N-α-acetylarginine, sphinganine, spermidine, and sphingosine-1P. Except for spermidine, all substances exhibited low expression in the case group compared with the external control group, and the difference in levels of sphinganine, spermidine, and sphingosine-1P was statistically significant.@*Conclusion@#The direction of change of levels of sphinganine, spermidine, and sphingosine-1P in the two-stage study cohorts was completely consistent, and the differences were statistically significant. Therefore, these substances can be used as potential biomarkers of KBD. Furthermore, these results raise the possibility that sphingolipid metabolic pathways may be closely related to KBD.
Subject(s)
Adolescent , Biomarkers/blood , Child , China , Cohort Studies , Female , Humans , Kashin-Beck Disease/blood , Male , Metabolic Networks and Pathways , MetabolomeABSTRACT
Ferroptosis is a newly discovered non-apoptotic form of regulated cell death driven by iron-dependent lipid peroxidation. The present studies have shown that many metabolic processes and homeostasis are affected by ferroptosis. It is related to many lung diseases, including acute lung injury, chronic obstructive pulmonary disease and pulmonary fibrosis, etc. Currently, the research on ferroptosis is still in its infancy. Previous studies have confirmed that ferroptosis is regulated by a variety of genes, and the mechanism is complex, mainly involving iron homeostasis and lipid peroxidation metabolism. This review summarizes some regulation networks of metabolic processes associated with ferroptosis and discusses the roles of ferroptosis in the pathophysiological progression of many lung diseases. We expected to provide new ideas and references for the treatment of these diseases.
Subject(s)
Ferroptosis , Humans , Iron , Lipid Peroxidation , Metabolic Networks and Pathways , Pulmonary Disease, Chronic ObstructiveABSTRACT
ABSTRACT Growth hormone (GH) is best known for its effect stimulating tissue and somatic growth through the regulation of cell division, regeneration and proliferation. However, GH-responsive neurons are spread over the entire central nervous system, suggesting that they have important roles in the brain. The objective of the present review is to summarize and discuss the potential physiological importance of GH action in the central nervous system. We provide evidence that GH signaling in the brain regulates the physiology of numerous functions such as cognition, behavior, neuroendocrine changes and metabolism. Data obtained from experimental animal models have shown that disruptions in GH signaling in specific neuronal populations can affect the reproductive axis and impair food intake during glucoprivic conditions, neuroendocrine adaptions during food restriction, and counter-regulatory responses to hypoglycemia, and they can modify gestational metabolic adaptions. Therefore, the brain is an important target tissue of GH, and changes in GH action in the central nervous system can explain some dysfunctions presented by individuals with excessive or deficient GH secretion. Furthermore, GH acts in specific neuronal populations during situations of metabolic stress to promote appropriate physiological adjustments that restore homeostasis. Arch Endocrinol Metab. 2019;63(6):549-56