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The establishment of brain metabolic network is based on 18fluoro-deoxyglucose positron emission computed tomography ( 18F-FDG PET) analysis, which reflect the brain functional network connectivity in normal physiological state or disease state. It is now applied to basic and clinical brain functional network research. In this paper, we constructed a metabolic network for the cerebral cortex firstly according to 18F-FDG PET image data from patients with temporal lobe epilepsy (TLE).Then, a statistical analysis to the network properties of patients with left or right TLE and controls was performed. It is shown that the connectivity of the brain metabolic network is weakened in patients with TLE, the topology of the network is changed and the transmission efficiency of the network is reduced, which means the brain metabolic network connectivity is extensively impaired in patients with TLE. It is confirmed that the brain metabolic network analysis based on 18F-FDG PET can provide a new perspective for the diagnose and therapy of epilepsy by utilizing PET images.
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Encéfalo , Epilepsia del Lóbulo Temporal , Fluorodesoxiglucosa F18 , Tomografía de Emisión de Positrones , Humanos , Epilepsia del Lóbulo Temporal/diagnóstico por imagen , Epilepsia del Lóbulo Temporal/metabolismo , Tomografía de Emisión de Positrones/métodos , Encéfalo/metabolismo , Encéfalo/diagnóstico por imagen , Redes y Vías Metabólicas , Corteza Cerebral/metabolismo , Corteza Cerebral/diagnóstico por imagenRESUMEN
Metabolic pathways are affected by the impacts of environmental contaminants underlying a large variability of toxic effects across different species. However, the systematic reconstruction of metabolic pathways remains limited in environmental sentinel species due to the lack of available genomic data in many taxa of animal diversity. In this study we used a multi-omics approach to reconstruct the most comprehensive map of metabolic pathways for a crustacean model in biomonitoring, the amphipod Gammarus fossarum in order to improve the knowledge of the metabolism of this sentinel species. We revisited the assembly of RNA-seq data by de novo approaches to reduce RNA contaminants and transcript redundancy. We also acquired extensive mass spectrometry shotgun proteomic data on several organs from a reference population of G. fossarum males and females to identify organ-specific metabolic profiles. The G. fossarum metabolic pathway reconstruction (available through the metabolic database GamfoCyc) was performed by adapting the genomic tool CycADS and we identified 377 pathways representing 7630 annotated enzymes, 2610 enzymatic reactions and the expression of 858 enzymes was experimentally validated by proteomics. To our knowledge, our analysis provides for the first time a systematic metabolic pathway reconstruction and the proteome profiles of these pathways at the organ level in this sentinel species. As an example, we show an elevated abundance in enzymes involved in ATP biosynthesis and fatty acid beta-oxidation indicative of the high-energy requirement of the gills, or the key anabolic and detoxification role of the hepatopancreatic caeca, as exemplified by the specific expression of the retinoid biosynthetic pathways and glutathione synthesis. In conclusion, the multi-omics data integration performed in this study provides new resources to investigate metabolic processes in crustacean amphipods and their role in mediating the effects of environmental contaminant exposures in sentinel species. SYNOPSIS: This study provide the first evidence that it is possible to combine multiple omics data to exhaustively describe the metabolic network of a model species in ecotoxicology, Gammarus fossarum, for which a reference genome is not yet available.
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Given the extensive heterogeneity and variability, understanding cellular functions and regulatory mechanisms through the analysis of multi-omics datasets becomes extremely challenging. Here, a comprehensive modeling framework of multi-omics machine learning and metabolic network models are proposed that covers various cellular biological processes across multiple scales. This model on an extensive normalized compendium of Bacillus subtilis is validated, which encompasses gene expression data from environmental perturbations, transcriptional regulation, signal transduction, protein translation, and growth measurements. Comparison with high-throughput experimental data shows that EM_iBsu1209-ME, constructed on this basis, can accurately predict the expression of 605 genes and the synthesis of 23 metabolites under different conditions. This study paves the way for the construction of comprehensive biological databases and high-performance multi-omics metabolic models to achieve accurate predictive analysis in exploring complex mechanisms of cell genotypes and phenotypes.
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Isoflavones, secondary metabolites with numerous health benefits, are predominantly found in legume seeds, especially soybean; however, their contents in domesticated soybean seeds are highly variable. Wild soybeans are known for higher seed isoflavone contents than cultivars. Here we used experimental and modelling approaches on wild soybean (W05) and cultivated soybean (C08) to delineate factors influencing isoflavone accumulation. We found imported nutrients were converted into storage compounds, with isoflavone accumulation in W05 seeds being faster than in C08 ones. The isoflavone accumulation during seed development was simulated using context-specific cotyledon metabolic models of four developmental stages on cultivar C08, and the metabolic burden imposed by increasing biomass was evaluated. Trade-off analyses between biomass and isoflavone suggest that high biomass requirement in cultivars could limit the reallocation of resources for secondary metabolite production. Isoflavone production in mature seeds was also influenced by biomass compositions. Seeds with higher carbohydrate contents favour isoflavone production, while those with highest protein and oil contents had lowest isoflavone contents. Although seeds could synthesize isoflavones on their own, the predicted fluxes from biosynthesis alone were lower than the empirical levels. Shadow price analyses indicated that isoflavone accumulation depended on both intrinsic biosynthesis and direct contribution from the plant.
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BACKGROUND: Chemical bioproduction has attracted attention as a key technology in a decarbonized society. In computational design for chemical bioproduction, it is necessary to predict changes in metabolic fluxes when up-/down-regulating enzymatic reactions, that is, responses of the system to enzyme perturbations. Structural sensitivity analysis (SSA) was previously developed as a method to predict qualitative responses to enzyme perturbations on the basis of the structural information of the reaction network. However, the network structural information can sometimes be insufficient to predict qualitative responses unambiguously, which is a practical issue in bioproduction applications. To address this, in this study, we propose BayesianSSA, a Bayesian statistical model based on SSA. BayesianSSA extracts environmental information from perturbation datasets collected in environments of interest and integrates it into SSA predictions. RESULTS: We applied BayesianSSA to synthetic and real datasets of the central metabolic pathway of Escherichia coli. Our result demonstrates that BayesianSSA can successfully integrate environmental information extracted from perturbation data into SSA predictions. In addition, the posterior distribution estimated by BayesianSSA can be associated with the known pathway reported to enhance succinate export flux in previous studies. CONCLUSIONS: We believe that BayesianSSA will accelerate the chemical bioproduction process and contribute to advancements in the field.
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Teorema de Bayes , Escherichia coli , Redes y Vías Metabólicas , Escherichia coli/metabolismo , Escherichia coli/genética , Modelos Estadísticos , Biología Computacional/métodos , Enzimas/metabolismoRESUMEN
Recent advancements in biosensor technology have revolutionized the field of microbial engineering, enabling efficient and precise optimization of strains for the production of valuable chemicals. This review comprehensively explores the innovative integration of biosensors to enhance microbial cell factories, with a particular emphasis on the crucial role of high-throughput biosensor-assisted screening. Biosensor-assisted approaches have enabled the identification of novel transporters, the elucidation of underlying transport mechanisms, and the fine-tuning of metabolic pathways for enhanced production. Furthermore, this review illustrates the utilization of biosensors for manipulating cellular behaviors, including interactions with environmental factors, and the reduction of nongenetic cell-to-cell variations. This review highlights the indispensable role of biosensors in advancing the field of microbial engineering through the modulation and exploitation of diverse cellular physiological processes.
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Bacterias , Técnicas Biosensibles , Ingeniería Metabólica , Técnicas Biosensibles/métodos , Técnicas Biosensibles/instrumentación , Bacterias/metabolismo , Bacterias/genética , Bacterias/aislamiento & purificación , Bacterias/clasificación , Fenómenos Fisiológicos BacterianosRESUMEN
The metabolic networks of microorganisms are remarkably robust to genetic and environmental perturbations. This robustness stems from redundancies such as gene duplications, isoenzymes, alternative metabolic pathways, and also from non-enzymatic reactions. In the oxidative branch of the pentose phosphate pathway (oxPPP), 6-phosphogluconolactone hydrolysis into 6-phosphogluconate is catalysed by 6-phosphogluconolactonase (Pgl) but in the absence of the latter, the oxPPP flux is thought to be maintained by spontaneous hydrolysis. However, in Δpgl Escherichia coli, an extracellular pathway can also contribute to pentose phosphate synthesis. This raises question as to whether the intracellular non-enzymatic reaction can compensate for the absence of 6-phosphogluconolactonase and, ultimately, on the role of 6-phosphogluconolactonase in central metabolism. Our results validate that the bypass pathway is active in the absence of Pgl, specifically involving the extracellular spontaneous hydrolysis of gluconolactones to gluconate. Under these conditions, metabolic flux analysis reveals that this bypass pathway accounts for the entire flux into the oxPPP. This alternative metabolic route-partially extracellular-sustains the flux through the oxPPP necessary for cell growth, albeit at a reduced rate in the absence of Pgl. Importantly, these findings imply that intracellular non-enzymatic hydrolysis of 6-phosphogluconolactone does not compensate for the absence of Pgl. This underscores the crucial role of Pgl in ensuring the efficient functioning of the oxPPP.
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Both clinical diagnosis and neuropathological diagnosis are commonly used in literature to categorize individuals as Alzheimer's disease (AD) or non-AD in omics analyses. Whether these diagnostic strategies result in distinct profiles of molecular abnormalities is poorly understood. Here, we analysed one of the most commonly used AD omics datasets in the literature from the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort and compared the two diagnosis strategies using brain transcriptome and metabolome by grouping individuals as non-AD and AD according to clinical or neuropathological diagnosis separately. Differentially expressed genes, associated pathways related with AD hallmarks and AD-related genes showed that the categorization based on neuropathological diagnosis more accurately reflects the disease state at the molecular level than the categorization based on clinical diagnosis. We further identified consensus biomarker candidates between the two diagnosis strategies such as 5-hydroxylysine, sphingomyelin and 1-myristoyl-2-palmitoyl-GPC as metabolite biomarkers and sphingolipid metabolism as a pathway biomarker, which could be robust AD biomarkers since they are independent of diagnosis strategies. We also used consensus AD and consensus non-AD individuals between the two diagnostic strategies to train a machine-learning based model, which we used to classify the individuals who were cognitively normal but diagnosed as AD based on neuropathological diagnosis (asymptomatic AD individuals). The majority of these individuals were classified as consensus AD patients for both omics data types. Our study provides a detailed characterization of both diagnostic strategies in terms of the association of the corresponding multi-omics profiles with AD.
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Enfermedad de Alzheimer , Biomarcadores , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/metabolismo , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/patología , Humanos , Biomarcadores/metabolismo , Masculino , Transcriptoma , Encéfalo/metabolismo , Encéfalo/patología , Anciano , Femenino , Anciano de 80 o más Años , Metaboloma , Aprendizaje Automático , MultiómicaRESUMEN
Rice, a primary staple food, may be improved in value via fermentation. Here, ten medicinal basidiomycetous fungi were separately applied for rice fermentation. After preliminary screening, Ganoderma boninense, Phylloporia pulla, Sanghuangporus sanghuang and Sanghuangporus weigelae were selected for further LC-MS based determination of the changes in metabolic profile after their fermentation with rice, and a total of 261, 296, 312, and 355 differential compounds were identified, respectively. Most of these compounds were up-regulated and involved in the metabolic pathways of amino acid metabolism, lipid metabolism, carbohydrate metabolism and the biosynthesis of other secondary metabolites. Sanghuangporus weigelae endowed the rice with the highest nutritional and bioactive values. The metabolic network of the identified differential compounds in rice fermented by S. weigelae illustrated their close relationships. In summary, this study provides insights into the preparation and application of potential functional food via the fermentation of rice with medicinal fungi.
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Fermentación , Alimentos Funcionales , Metabolómica , Oryza , Oryza/metabolismo , Oryza/química , Oryza/microbiología , Alimentos Funcionales/análisis , Basidiomycota/metabolismo , Basidiomycota/crecimiento & desarrollo , Basidiomycota/química , Espectrometría de Masas , Hongos/metabolismoRESUMEN
BACKGROUND: Metabolism is increasingly recognized as a key regulator of the function and phenotype of the primary cellular constituents of the atherosclerotic vascular wall, including endothelial cells, smooth muscle cells, and inflammatory cells. However, a comprehensive analysis of metabolic changes associated with the transition of plaque from a stable to a hemorrhaged phenotype is lacking. METHODS: In this study, we integrated two large mRNA expression and protein abundance datasets (BIKE, n = 126; MaasHPS, n = 43) from human atherosclerotic carotid artery plaque to reconstruct a genome-scale metabolic network (GEM). Next, the GEM findings were linked to metabolomics data from MaasHPS, providing a comprehensive overview of metabolic changes in human plaque. RESULTS: Our study identified significant changes in lipid, cholesterol, and inositol metabolism, along with altered lysosomal lytic activity and increased inflammatory activity, in unstable plaques with intraplaque hemorrhage (IPH+) compared to non-hemorrhaged (IPH-) plaques. Moreover, topological analysis of this network model revealed that the conversion of glutamine to glutamate and their flux between the cytoplasm and mitochondria were notably compromised in hemorrhaged plaques, with a significant reduction in overall glutamate levels in IPH+ plaques. Additionally, reduced glutamate availability was associated with an increased presence of macrophages and a pro-inflammatory phenotype in IPH+ plaques, suggesting an inflammation-prone microenvironment. CONCLUSIONS: This study is the first to establish a robust and comprehensive GEM for atherosclerotic plaque, providing a valuable resource for understanding plaque metabolism. The utility of this GEM was illustrated by its ability to reliably predict dysregulation in the cholesterol hydroxylation, inositol metabolism, and the glutamine/glutamate pathway in rupture-prone hemorrhaged plaques, a finding that may pave the way to new diagnostic or therapeutic measures.
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Enfermedades de las Arterias Carótidas , Ácido Glutámico , Glutamina , Macrófagos , Redes y Vías Metabólicas , Fenotipo , Placa Aterosclerótica , Humanos , Glutamina/metabolismo , Ácido Glutámico/metabolismo , Macrófagos/metabolismo , Macrófagos/patología , Enfermedades de las Arterias Carótidas/metabolismo , Enfermedades de las Arterias Carótidas/patología , Enfermedades de las Arterias Carótidas/genética , Rotura Espontánea , Arterias Carótidas/patología , Arterias Carótidas/metabolismo , Metabolómica , Bases de Datos Genéticas , Inflamación/metabolismo , Inflamación/genética , Inflamación/patología , Metabolismo Energético , Conjuntos de Datos como Asunto , MasculinoRESUMEN
Soil metabolites are critical in regulating the dynamics of ecosystem structure and function, particularly in fragile karst ecosystems. Clarification of response of soil metabolism to vegetation succession in karst areas will contribute to the overall understanding and management of karst soils. Here, we investigated the metabolite characteristics of karst soils with different vegetation stages (grassland, brushwood, secondary forest and primary forest) based on untargeted metabolomics. We confirmed that the abundance and composition of soil metabolites altered with vegetation succession. Of the 403 metabolites we found, 157 had significantly varied expression levels across vegetation soils, including mainly lipids and lipid-like molecules, phenylpropanoids and polyketides, organic acids and derivatives. Certain soil metabolites, such as maltotetraose and bifurcose, were sensitive to vegetation succession, increasing significantly from grassland to brushwood and then decreasing dramatically in secondary and primary forests, making them possible indicators of karst vegetation succession. In addition, soil metabolic pathways, such as galactose metabolism and biosynthesis of unsaturated fatty acids, also changed with vegetation succession. This study characterized the soil metabolic profile in different vegetation stages during karst secondary succession, which would provide new insights for the management of karst soils.
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UV can serve as an effective light spectrum for regulating plant secondary metabolites, while relevant studies on UV-A are much less extensive than those on UV-B. A comprehensive understanding of the selective effects of UV-A on different secondary metabolites and the specific features of primary metabolism that drive these effects is still lacking. To address this knowledge gap, we conducted a study to analyze the dynamic changes in the metabolome and transcriptome of lettuce leaves irradiated with red plus UV-A light (monochromatic red light as control). Generally, UV-A promoted the synthesis of most phenylpropanoids and terpenoids originating from the shikimate and methylerythritol phosphate (MEP) pathway in plastids but sacrificed the synthesis of terpenoids derived from the mevalonate (MVA) pathway, particularly sesquiterpenes. Increased precursors supply for the shikimate and MEP pathway under UV-A was directly supported by the activation of the Calvin-Benson cycle and phosphoenolpyruvate transport. Whereas, along with phosphoenolpyruvate transport, the TCA cycle was restrained, causing deprivation of the MVA pathway precursor. In addition, UV-A also activated the plastidic oxidative branch of the pentose phosphate pathway, photorespiration, and malate shuttle, to ensure a sufficient supply of nitrogen, circulation homeostasis of the Calvin-Benson cycle, and energy balance, thus indirectly supporting UV-A-induced specific secondary metabolic output. This study provides a comprehensive framework for understanding the flexible primary-secondary metabolism interactions that are able to produce specific metabolites favorable for adaptation to environmental stimuli.
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Lactuca , Hojas de la Planta , Metabolismo Secundario , Rayos Ultravioleta , Lactuca/metabolismo , Lactuca/efectos de la radiación , Lactuca/química , Lactuca/genética , Lactuca/crecimiento & desarrollo , Metabolismo Secundario/efectos de la radiación , Hojas de la Planta/metabolismo , Hojas de la Planta/efectos de la radiación , Hojas de la Planta/química , Proteínas de Plantas/metabolismo , Proteínas de Plantas/genética , Metaboloma/efectos de la radiación , Regulación de la Expresión Génica de las Plantas/efectos de la radiación , MultiómicaRESUMEN
Clorobiocin is a well-known, highly effective inhibitor of DNA gyrase belonging to the aminocoumarin antibiotics. To identify potentially novel derivatives of this natural product, we conducted an untargeted investigation of clorobiocin biosynthesis in the known producer Streptomyces roseochromogenes DS 12.976 using LC-MSE, molecular networking, and analysis of fragmentation spectra. Previously undescribed clorobiocin derivatives uncovered in this study include bromobiocin, a variant halogenated with bromine instead of chlorine, hydroxylated clorobiocin, carrying an additional hydroxyl group on its 5-methyl-pyrrole 2-carboxyl moiety, and two other derivatives with modifications on their 3-dimethylallyl 4-hydroxybenzoate moieties. Furthermore, we identified several compounds not previously considered clorobiocin pathway products, which provide new insights into the clorobiocin biosynthetic pathway. By supplementing the medium with different concentrations of potassium bromide, we confirmed that the clorobiocin halogenase can utilize bromine instead of chlorine. The reaction, however, is impeded such that non-halogenated clorobiocin derivatives accumulate. Preliminary assays indicate that the antibacterial activity of bromobioin against Bacillus subtilis and efflux-impaired Escherichia coli matches that of clorobiocin. Our findings emphasize that yet unexplored compounds can be discovered from established strains and biosynthetic gene clusters by means of metabolomics analysis and highlight the utility of LC-MSE-based methods to contribute to unraveling natural product biosynthetic pathways. IMPORTANCE: The aminocoumarin clorobiocin is a well-known gyrase inhibitor produced by the gram-positive bacterium Streptomyces roseochromogenes DS 12.976. To gain a deeper understanding of the biosynthetic pathway of this complex composite of three chemically distinct entities and the product spectrum, we chose a metabolite-centric approach. Employing high-resolution LC-MSE analysis, we investigated the pathway products in extracted culture supernatants of the natural producer. Novel pathway products were identified that expand our understanding of three aspects of the biosynthetic pathway, namely the modification of the noviose, transfer and methylation of the pyrrole 2-carboxyl moiety, and halogenation. For the first time, brominated products were detected. Their levels and the levels of non-halogenated products increased in medium supplemented with KBr. Based on the presented data, we propose that the enzyme promiscuity contributes to a broad product spectrum.
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Antibacterianos , Vías Biosintéticas , Metabolómica , Novobiocina , Streptomyces , Streptomyces/metabolismo , Streptomyces/genética , Antibacterianos/farmacología , Antibacterianos/biosíntesis , Antibacterianos/metabolismo , Antibacterianos/química , Novobiocina/análogos & derivados , Novobiocina/biosíntesis , Novobiocina/farmacología , Novobiocina/metabolismo , Cromatografía LiquidaRESUMEN
BACKGROUND: Coronary atherosclerosis (CAS) is a prevalent and chronic life-threatening disease. However, the detection of CAS at an early stage is difficult because of the lack of effective noninvasive diagnostic methods. The present study aimed to characterize the plasma metabolome of early-stage CAS patients to discover metabolomic biomarkers, develop a novel metabolite-based model for accurate noninvasive diagnosis of early-stage CAS, and explore the underlying metabolic mechanisms involved. METHODS: A total of 100 patients with early-stage CAS and 120 age- and sex-matched control subjects were recruited from the Chinese Han population and further randomly divided into training (n = 120) and test sets (n = 100). The metabolomic profiles of the plasma samples were analyzed by an integrated untargeted liquid chromatography-mass spectrometry approach, including two separation modes and two ionization modes. Univariate and multivariate statistical analyses were employed to identify potential biomarkers and construct an early-stage CAS diagnostic model. RESULTS: The integrated analytical method established herein improved metabolite coverage compared with single chromatographic separation and MS ionization mode. A total of 80 metabolites were identified as potential biomarkers of early-stage CAS, and these metabolites were mainly involved in glycerophospholipid, fatty acid, sphingolipid, and amino acid metabolism. An effective diagnostic model for early-stage CAS was established, incorporating 11 metabolites and achieving areas under the receiver operating characteristic curve (AUCs) of 0.984 and 0.908 in the training and test sets, respectively. CONCLUSIONS: Our study not only successfully developed an effective noninvasive diagnostic model for identifying early-stage CAS but also provided novel insights into the pathogenesis of CAS.
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Biomarcadores , Enfermedad de la Arteria Coronaria , Metabolómica , Humanos , Biomarcadores/sangre , Masculino , Metabolómica/métodos , Enfermedad de la Arteria Coronaria/sangre , Enfermedad de la Arteria Coronaria/diagnóstico , Femenino , Persona de Mediana Edad , Anciano , Cromatografía Liquida , Espectrometría de MasasRESUMEN
Huangjiu is a spontaneously fermented alcoholic beverage, that undergoes intricate microbial compositional changes. This study aimed to unravel the flavor and quality formation mechanisms based on the microbial metabolism of Huangjiu. Here, metagenome techniques, chemometrics analysis, and headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) metabolomics combined with microbial metabolic network were employed to investigate the distinctions and relationship between the microbial profiles and the quality characteristics, flavor metabolites, functional metabolic patterns of Huangjiu across three regions. Significant variations (P < 0.05) were observed in metabolic rate of physicochemical parameters and biogenic amine concentration among three regions. 8 aroma compounds (phenethyl acetate, phenylethyl alcohol, isobutyl alcohol, ethyl octanoate, ethyl acetate, ethyl hexanoate, isoamyl alcohol, and diethyl succinate) out of 448 volatile compounds were identified as the regional chemical markers. 25 dominant microbial genera were observed through metagenomic analysis, and 13 species were confirmed as microbial markers in three regions. A metabolic network analysis revealed that Saccharomycetales (Saccharomyces), Lactobacillales (Lactobacillus, Weissella, and Leuconostoc), and Eurotiales (Aspergillus) were the predominant populations responsible for substrate, flavor (mainly esters and phenylethyl alcohol) metabolism, Lactobacillales and Enterobacterales were closely linked with biogenic amine. These findings provide scientific evidence for regional microbial contributions to geographical characteristics of Huangjiu, and perspectives for optimizing microbial function to promote Huangjiu quality.
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Bacterias , Fermentación , Cromatografía de Gases y Espectrometría de Masas , Redes y Vías Metabólicas , Metagenómica , Oryza , Compuestos Orgánicos Volátiles , Vino , Bacterias/clasificación , Bacterias/metabolismo , Bacterias/genética , Bacterias/aislamiento & purificación , Aminas Biogénicas/análisis , Aminas Biogénicas/metabolismo , China , Aromatizantes/metabolismo , Aromatizantes/química , Metabolómica/métodos , Microbiota , Odorantes/análisis , Oryza/microbiología , Oryza/química , Oryza/metabolismo , Microextracción en Fase Sólida , Gusto , Compuestos Orgánicos Volátiles/metabolismo , Compuestos Orgánicos Volátiles/análisis , Vino/análisis , Vino/microbiologíaRESUMEN
Cordyceps militaris, widely recognized as a medicinal and edible mushroom in East Asia, contains a variety of bioactive compounds, including cordycepin (COR), pentostatin (PTN) and other high-value compounds. This review explores the potential of developing C. militaris as a cell factory for the production of high-value chemicals and nutrients. This review comprehensively summarizes the fermentation advantages, metabolic networks, expression elements, and genome editing tools specific to C. militaris and discusses the challenges and barriers to further research on C. militaris across various fields, including computational biology, existing DNA elements, and genome editing approaches. This review aims to describe specific and promising opportunities for the in-depth study and development of C. militaris as a new chassis cell. Additionally, to increase the practicability of this review, examples of the construction of cell factories are provided, and promising strategies for synthetic biology development are illustrated.
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Cordyceps , Ingeniería Metabólica , Cordyceps/metabolismo , Cordyceps/genética , Cordyceps/crecimiento & desarrollo , Ingeniería Metabólica/métodos , Fermentación , Edición Génica , Biología Sintética , Redes y Vías Metabólicas/genéticaRESUMEN
Patient blood samples are invaluable in clinical omics databases, yet current methodologies often fail to fully uncover the molecular mechanisms driving patient pathology. While genome-scale metabolic models (GEMs) show promise in systems medicine by integrating various omics data, having only exometabolomic data remains a limiting factor. To address this gap, we introduce a comprehensive pipeline integrating GEMs with patient plasma metabolome. This pipeline constructs case-specific GEMs using literature-based and patient-specific metabolomic data. Novel computational methods, including adaptive sampling and an in-house developed algorithm for the rational exploration of the sampled space of solutions, enhance integration accuracy while improving computational performance. Model characterization involves task analysis in combination with clustering methods to identify critical cellular functions. The new pipeline was applied to a cohort of trauma patients to investigate shock-induced endotheliopathy using patient plasma metabolome data. By analyzing endothelial cell metabolism comprehensively, the pipeline identified critical therapeutic targets and biomarkers that can potentially contribute to the development of therapeutic strategies. Our study demonstrates the efficacy of integrating patient plasma metabolome data into computational models to analyze endothelial cell metabolism in disease contexts. This approach offers a deeper understanding of metabolic dysregulations and provides insights into diseases with metabolic components and potential treatments.
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Células Endoteliales , Metaboloma , Metabolómica , Humanos , Células Endoteliales/metabolismo , Metabolómica/métodos , Modelos Biológicos , Algoritmos , Biomarcadores/sangre , Biología Computacional/métodosRESUMEN
Impaired metabolism is recognized as an important contributor to pathogenicity of T cells in Systemic Lupus Erythematosus (SLE). Over the last two decades, we have acquired significant knowledge about the signaling and transcriptomic programs related to metabolic rewiring in healthy and SLE T cells. However, our understanding of metabolic network activity derives largely from studying metabolic pathways in isolation. Here, we argue that enzymatic activities are necessarily coupled through mass and energy balance constraints with in-built network-wide dependencies and compensation mechanisms. Therefore, metabolic rewiring of T cells in SLE must be understood in the context of the entire network, including changes in metabolic demands such as shifts in biomass composition and cytokine secretion rates as well as changes in uptake/excretion rates of multiple nutrients and waste products. As a way forward, we suggest cell physiology experiments and integration of orthogonal metabolic measurements through computational modeling towards a comprehensive understanding of T cell metabolism in lupus.
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Lupus Eritematoso Sistémico , Linfocitos T , Lupus Eritematoso Sistémico/metabolismo , Lupus Eritematoso Sistémico/inmunología , Humanos , Linfocitos T/inmunología , Linfocitos T/metabolismo , Redes y Vías Metabólicas , Metabolismo Energético , Animales , Transducción de Señal , Citocinas/metabolismoRESUMEN
Humans interact with a multitude of microorganisms in various ecological relationships, ranging from commensalism to pathogenicity. The same applies to fungi, long recognized for their pathogenic roles in infection-such as in invasive fungal diseases caused, among others, by Aspergillus fumigatus and Candida spp.-and, more recently, for their beneficial activities as an integral part of the microbiota. Indeed, alterations in the fungal component of the microbiota, or mycobiota, have been associated with inflammatory, infectious and metabolic diseases, and cancer. Whether acting as opportunistic pathogens or symbiotic commensals, fungi possess a complex enzymatic repertoire that intertwines with that of the host. In this metabolic cross-talk, fungal enzymes may be unique, thus providing novel metabolic opportunities to the host, or, conversely, produce toxic metabolites. Indeed, administration of fungal probiotics and fungi-derived products may be beneficial in inflammatory and infectious diseases, but fungi may also produce a plethora of toxic secondary metabolites, collectively known as mycotoxins. Fungal enzymes may also be homologues to human enzymes, but nevertheless embedded in fungal-specific metabolic networks, determined by all the interconnected enzymes and molecules, quantitatively and qualitatively specific to the network, such that the activity and metabolic effects of each enzyme remain unique to fungi. In this Opinion, we explore the concept that targeting this fungal metabolic unicity, either in opportunistic pathogens or commensals, may be exploited to develop novel therapeutic strategies. In doing so, we present our recent experience in different pathological settings that ultimately converge on relevant trans-kingdom metabolic differences.
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BACKGROUND: Bone metabolic diseases are serious health issues worldwide. Angelica sinensis (AS) is traditionally used in Chinese medicine for treating bone metabolism diseases clinically. However, the mechanism of AS in regulating bone metabolism remains uncertain. OBJECTIVE: The current investigation was structured to elucidate the potential mechanisms of AS for modulating bone metabolism. METHODS: Firstly, targets of AS regulating bone metabolism were collected by network pharmacology. Then, the transcriptional regulation of RUNX2 was enriched as one of the key pathways for AS to regulate bone metabolism, constructing its metabolic network. Secondly, combining molecular docking, network efficiency, and network flux analyses, we conducted a quantitative evaluation of the metabolic network to reveal the potential mechanisms and components of AS regulating bone metabolism. Finally, we explored the effect of AS on the differentiation of osteoclasts from M-CSF and RANKL-induced RAW264.7 cells, as well as its impact on the osteogenic induction of MC3T3-E1 cells. We verified the mechanism and key targets of AS on bone metabolism using qRT-PCR. Furthermore, the key component was preliminarily validated through molecular dynamics simulation. RESULTS: Quantitative metabolic network of the transcriptional regulation of RUNX2 was constructed to illustrate the potential mechanism of AS for regulating bone metabolism, indicating that ferulic acid may be a pharmacological component of AS that interferes with bone metabolism. AS suppressed osteoclast differentiation in M-CSF and RANKL-induced RAW264.7 cells and reversed the expressions of osteoclastic differentiation markers, including RUNX2 and SRC. Additionally, AS induced osteogenic generation in MC3T3-E1 cells and reversed the expressions of markers associated with osteoblastic generation, such as RUNX2 and HDAC4. Molecular dynamics simulation displayed a strong binding affinity among ferulic acid, HDAC4 and SRC. CONCLUSION: This study reveals a systematic perspective on the intervention bone mechanism of AS by transcriptive regulation by RUNX2, guiding the clinical use of AS in treating diseases of the skeletal system.