•The recent epidemics of metabolic diseases cannot be attributed only to genetic background and changes in diet, exercise and aging.•Metabolic diseases have their origins during development due to ...altered programming that increases susceptibility to disease later in life.•Metabolism disruptors are endocrine disruptors that increase the susceptibility to metabolic diseases.•Some metabolism disruptors may cause metabolic diseases per se while others act via increasing the sensitivity or set point for disease.•The metabolic disruptor hypotheses provides a focus on preventing metabolic diseases.
The recent epidemics of metabolic diseases, obesity, type 2 diabetes(T2D), liver lipid disorders and metabolic syndrome have largely been attributed to genetic background and changes in diet, exercise and aging. However, there is now considerable evidence that other environmental factors may contribute to the rapid increase in the incidence of these metabolic diseases. This review will examine changes to the incidence of obesity, T2D and non-alcoholic fatty liver disease (NAFLD), the contribution of genetics to these disorders and describe the role of the endocrine system in these metabolic disorders. It will then specifically focus on the role of endocrine disrupting chemicals (EDCs) in the etiology of obesity, T2D and NAFLD while finally integrating the information on EDCs on multiple metabolic disorders that could lead to metabolic syndrome. We will specifically examine evidence linking EDC exposures during critical periods of development with metabolic diseases that manifest later in life and across generations.
Current machine learning techniques enable robust association of biological signals with measured phenotypes, but these approaches are incapable of identifying causal relationships. Here, we develop ...an integrated “white-box” biochemical screening, network modeling, and machine learning approach for revealing causal mechanisms and apply this approach to understanding antibiotic efficacy. We counter-screen diverse metabolites against bactericidal antibiotics in Escherichia coli and simulate their corresponding metabolic states using a genome-scale metabolic network model. Regression of the measured screening data on model simulations reveals that purine biosynthesis participates in antibiotic lethality, which we validate experimentally. We show that antibiotic-induced adenine limitation increases ATP demand, which elevates central carbon metabolism activity and oxygen consumption, enhancing the killing effects of antibiotics. This work demonstrates how prospective network modeling can couple with machine learning to identify complex causal mechanisms underlying drug efficacy.
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•A white-box machine learning approach is developed for antibiotics research•Network modeling is coupled to a biochemical screen to identify pathway mechanisms•Antibiotic-induced adenine limitation increases purine biosynthesis and ATP demand•Increased ATP demand drives central carbon metabolism and oxygen consumption
Causal metabolic pathways underlying antibiotic lethality in bacteria are illuminated by a network model-driven machine learning approach, overcoming limitations of existing “black-box” approaches that cannot reveal causal relationships from large biological datasets.
The prediction of cellular function from a genotype is a fundamental goal in biology. For metabolism, constraint-based modelling methods systematize biochemical, genetic and genomic knowledge into a ...mathematical framework that enables a mechanistic description of metabolic physiology. The use of constraint-based approaches has evolved over ~30 years, and an increasing number of studies have recently combined models with high-throughput data sets for prospective experimentation. These studies have led to validation of increasingly important and relevant biological predictions. As reviewed here, these recent successes have tangible implications in the fields of microbial evolution, interaction networks, genetic engineering and drug discovery.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Here, we explore the manipulation of immune cell metabolism as a strategy in target discovery and drug development for immune-mediated diseases. Comparing exploitation of metabolic pathways to kill ...tumor cells for cancer treatment with the reprogramming of immune cells to treat autoimmune diseases highlights differences that confer several advantages to the latter (including a more favorable therapeutic index and greater target stability). We discuss technological capabilities and gaps, including the challenge of relating in vitro observations to in vivo biology. Finally, we conclude by identifying future opportunities that will move the field forward and accelerate drug discovery.
Growing knowledge of the link between immune cell metabolism and immune cell function has led to the concept of manipulating intracellular metabolic pathways as an approach to treating immune-mediated diseases. In this Perspective, Mazumdar et al. discuss the state of the art, assess gaps, and outline potential paths ahead.
Phenolic acids have recently gained substantial attention due to their various practical, biological and pharmacological effects. Chlorogenic Acid (CGA, 3-CQA) is a most abundant isomer among ...caffeoylquinic acid isomers (3-, 4-, and 5-CQA), that currently known as 5-CQA as per guidelines of IUPAC. It is one of the most available acids among phenolic acid compounds which can be naturally found in green coffee extracts and tea. CGA is an important and biologically active dietary polyphenol, playing several important and therapeutic roles such as antioxidant activity, antibacterial, hepatoprotective, cardioprotective, anti-inflammatory, antipyretic, neuroprotective, anti-obesity, antiviral, anti-microbial, anti-hypertension, free radicals scavenger and a central nervous system (CNS) stimulator. In addition, it has been found that CGA could modulate lipid metabolism and glucose in both genetically and healthy metabolic related disorders. It is speculated that CGA can perform crucial roles in lipid and glucose metabolism regulation and thus help to treat many disorders such as hepatic steatosis, cardiovascular disease, diabetes, and obesity as well. Furthermore, this phenolic acid (CGA) causes hepatoprotective effects by protecting animals from chemical or lipopolysaccharide-induced injuries. The hypocholesterolemic influence of CGA can result from the altered metabolism of nutrients, including amino acids, glucose and fatty acids (FA). The purpose of this review was to broaden the scope of knowledge of researchers to conduct more studies on this subject to both unveil and optimize its biological and pharmacological effects. As a result, CGA may be practically used as a natural safeguard food additive to replace the synthetic antibiotics and thereby reduce the medicinal cost.
Measuring intracellular metabolism has increasingly led to important insights in biomedical research. (13)C tracer analysis, although less information-rich than quantitative (13)C flux analysis that ...requires computational data integration, has been established as a time-efficient method to unravel relative pathway activities, qualitative changes in pathway contributions, and nutrient contributions. Here, we review selected key issues in interpreting (13)C metabolite labeling patterns, with the goal of drawing accurate conclusions from steady state and dynamic stable isotopic tracer experiments.
Immune cells play a key role in host defense against infection and cancer. Upon encountering danger signals, these cells undergo activation leading to a modulation in their immune functions. However, ...recent studies reveal that immune cells upon activation also show distinct metabolic changes that impact their immune functions. Such metabolic reprogramming and its functional effects are well known for cancer cells. Given that immune cells have emerged as crucial players in cancer progression, it is important to understand whether immune cells also undergo metabolic reprogramming in tumors and how this might affect their contribution in cancer progression. This emerging aspect of tumor-associated immune cells is reviewed here, discussing metabolic reprogramming of different immune cell types, the key pathways involved, and its impact on tumor progression.
Immune cells have a crucial contribution in cancer. However, it is not known whether these cells, like cancer cells, undergo a metabolic reprogramming that regulates their role in cancer progression. Biswas reviews this emerging aspect of tumor-associated immune cells.
Macrophage polarization involves a coordinated metabolic and transcriptional rewiring that is only partially understood. By using an integrated high-throughput transcriptional-metabolic profiling and ...analysis pipeline, we characterized systemic changes during murine macrophage M1 and M2 polarization. M2 polarization was found to activate glutamine catabolism and UDP-GlcNAc-associated modules. Correspondingly, glutamine deprivation or inhibition of N-glycosylation decreased M2 polarization and production of chemokine CCL22. In M1 macrophages, we identified a metabolic break at Idh, the enzyme that converts isocitrate to alpha-ketoglutarate, providing mechanistic explanation for TCA cycle fragmentation. 13C-tracer studies suggested the presence of an active variant of the aspartate-arginosuccinate shunt that compensated for this break. Consistently, inhibition of aspartate-aminotransferase, a key enzyme of the shunt, inhibited nitric oxide and interleukin-6 production in M1 macrophages, while promoting mitochondrial respiration. This systems approach provides a highly integrated picture of the physiological modules supporting macrophage polarization, identifying potential pharmacologic control points for both macrophage phenotypes.
•Glutamine deprivation affects M2 polarization but not M1 polarization•UDP-GlcNAc biosynthesis and N-glycosylation are important for M2 polarization•There is no reverse or direct flow through Idh or malic enzyme in M1 macrophages•Aspartate-arginosuccinate shunt connects the NO and TCA cycles in M1 polarization
Polarization of macrophages involves a metabolic and transcriptional rewiring that is only partially understood. Artyomov and colleagues used an integrated high-throughput transcriptional-metabolic profiling and analysis pipeline to identify metabolic modules that support macrophage polarization and function.
► Aldosterone is the major mineralocorticoid produced by the adrenal zona glomerulosa. ► Glomerulosa cells are primarily regulated by angiotensin II, serum potassium and ACTH. ► Aldosterone synthesis ...involves two key phases, acute and chronic. ► Cholesterol delivery into mitochondria is the rate-limiting step in the acute phase. ► Aldosterone synthase (CYP11B2) is the rate-limiting step in the chronic phase.
Aldosterone is the major mineralocorticoid synthesized by the adrenal and plays an important role in the regulation of systemic blood pressure through the absorption of sodium and water. Aldosterone production is regulated tightly by selective expression of aldosterone synthase (CYP11B2) in the adrenal outermost zone, the zona glomerulosa. Angiotensin II (Ang II), potassium (K+) and adrenocorticotropin (ACTH) are the main physiological agonists which regulate aldosterone secretion. Aldosterone production is regulated within minutes of stimulation (acutely) through increased expression and phosphorylation of the steroidogenic acute regulatory (StAR) protein and over hours to days (chronically) by increased expression of the enzymes involved in the synthesis of aldosterone, particularly CYP11B2. Imbalance in any of these processes may lead to several disorders of aldosterone excess. In this review we attempt to summarize the key molecular events involved in the acute and chronic phases of aldosterone secretion.
Abstract
The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism, and other cellular processes as an ordered ...network of molecular transformations-an extended version of a classic metabolic map, in a single consistent data model. Reactome functions both as an archive of biological processes and as a tool for discovering unexpected functional relationships in data such as gene expression profiles or somatic mutation catalogues from tumor cells. To support the continued brisk growth in the size and complexity of Reactome, we have implemented a graph database, improved performance of data analysis tools, and designed new data structures and strategies to boost diagram viewer performance. To make our website more accessible to human users, we have improved pathway display and navigation by implementing interactive Enhanced High Level Diagrams (EHLDs) with an associated icon library, and subpathway highlighting and zooming, in a simplified and reorganized web site with adaptive design. To encourage re-use of our content, we have enabled export of pathway diagrams as 'PowerPoint' files.
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