scholarly journals Promiscuity in the Archaea: The enzymology of their metabolic pathways

2005 ◽  
Vol 27 (1) ◽  
pp. 17-21 ◽  
Author(s):  
Michael J. Danson ◽  
David W. Hough
Keyword(s):  
Metabolic Pathway ◽  
Metabolic Pathways ◽  
Hyperthermophilic Archaea ◽  
Structural Basis ◽  
Central Metabolism ◽  
Central Metabolic Pathway ◽  
Living Organisms ◽  
Single Set

The pathways of central metabolism provide the metabolic connections between the catabolic (degradative) and anabolic (biosynthetic) routes in all living organisms. In hyperthermophilic Archaea, we have discovered a promiscuous central metabolic pathway that catabolizes a variety of sugars using a single set of enzymes. This article explores the structural basis of this promiscuity in enzymes that have to maintain their integrity at temperatures approaching 100°C.

scholarly journals iMPTCE-Hnetwork: A Multilabel Classifier for Identifying Metabolic Pathway Types of Chemicals and Enzymes with a Heterogeneous Network

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yuanyuan Zhu ◽  
Bin Hu ◽  
Lei Chen ◽  
Qi Dai
Keyword(s):  
Metabolic Pathway ◽  
Metabolic Pathways ◽  
Heterogeneous Network ◽  
Cross Validation ◽  
Polynomial Kernel ◽  
Support Vector ◽  
Exact Match ◽  
Living Organisms ◽  
A Chain ◽  
Fold Cross Validation

Metabolic pathway is an important type of biological pathways. It produces essential molecules and energies to maintain the life of living organisms. Each metabolic pathway consists of a chain of chemical reactions, which always need enzymes to participate in. Thus, chemicals and enzymes are two major components for each metabolic pathway. Although several metabolic pathways have been uncovered, the metabolic pathway system is still far from complete. Some hidden chemicals or enzymes are not discovered in a certain metabolic pathway. Besides the traditional experiments to detect hidden chemicals or enzymes, an alternative pipeline is to design efficient computational methods. In this study, we proposed a powerful multilabel classifier, called iMPTCE-Hnetwork, to uniformly assign chemicals and enzymes to metabolic pathway types reported in KEGG. Such classifier adopted the embedding features derived from a heterogeneous network, which defined chemicals and enzymes as nodes and the interactions between chemicals and enzymes as edges, through a powerful network embedding algorithm, Mashup. The popular RAndom k-labELsets (RAKEL) algorithm was employed to construct the classifier, which incorporated the support vector machine (polynomial kernel) as the basic classifier. The ten-fold cross-validation results indicated that such a classifier had good performance with accuracy higher than 0.800 and exact match higher than 0.750. Several comparisons were done to indicate the superiority of the iMPTCE-Hnetwork.

scholarly journals iMPT-FRAKEL: A Simple Multi-label Web-server that Only Uses Fingerprints to Identify which Metabolic Pathway Types Compounds can Participate In

2020 ◽  
Vol 13 (1) ◽  
pp. 83-91
Author(s):  
Yanjuan Jia ◽  
Lei Chen ◽  
Jian-Peng Zhou ◽  
Min Liu
Keyword(s):  
Metabolic Pathway ◽  
Metabolic Pathways ◽  
Learning Algorithm ◽  
Web Server ◽  
Support Vector ◽  
Binary Relevance ◽  
Comparison Results ◽  
Rbf Kernel ◽  
Living Organisms ◽  
Set Up

Background: Metabolic pathway is one of the most basic biological pathways in living organisms. It consists of a series of chemical reactions and provides the necessary molecules and energies for organisms. To date, lots of metabolic pathways have been detected. However, there still exist hidden participants (compounds and enzymes) for some metabolic pathways due to the complexity and diversity of metabolic pathways. It is necessary to develop quick, reliable, and non-animal-involved prediction model to recognize metabolic pathways for any compound. Methods: In this study, a multi-label classifier, namely iMPT-FRAKEL, was developed for identifying which metabolic pathway types that compounds can participate in. Compounds and 12 metabolic pathway types were retrieved from KEGG. Each compound was represented by its fingerprints, which was the most widely used form for representing compounds and can be extracted from its SMILES format. A popular multi-label classification scheme, Random k-Labelsets (RAKEL) algorithm, was adopted to build the classifier. Classic machine learning algorithm, Support Vector Machine (SVM) with RBF kernel, was selected as the basic classification algorithm. Ten-fold cross-validation was used to evaluate the performance of the iMPT-FRAKEL. In addition, a web-server version of such classifier was set up, which can be assessed at http://cie.shmtu.edu.cn/impt/index. Results: iMPT-FRAKEL yielded the accuracy of 0.804, exact match of 0.745 and hamming loss of 0.039. Comparison results indicated that such classifier was superior to other models, including models with Binary Relevance (BR) or other classification algorithms. Conclusion: The proposed classifier employed limited prior knowledge of compounds but gives satisfying performance for recognizing metabolic pathways of compounds.

Pentose Phosphate Pathway in Disease and Therapy

2014 ◽  
Vol 995 ◽  
pp. 1-27 ◽  
Author(s):  
Mahbuba Rahman ◽  
M. Rubayet Hasan
Keyword(s):  
Metabolic Pathways ◽  
Cell Cycle Progression ◽  
Metabolic Diseases ◽  
Pentose Phosphate ◽  
Cycle Progression ◽  
Novel Drugs ◽  
Abnormal Cells ◽  
Living Organisms ◽  
And Function

Pentose phosphate (PP) pathway, which is ubiquitously present in all living organisms, is one of the major metabolic pathways associated with glucose metabolism. The most important functions of this pathway includes the generation of reducing equivalents in the form of NADPH for reductive biosynthesis, and production of ribose sugars for the biosynthesis of nucleotides, amino acids, and other macromolecules required by all living cells. Under normal conditions of growth, PP pathway is important for cell cycle progression, myelin formation, and the maintenance of the structure and function of brain, liver, cortex and other organs. Under diseased conditions, such as in cases of many metabolic, neurological or malignant diseases, pathological mechanisms augment due to defects in the PP pathway genes. Adoption of alternative metabolic pathways by cells that are metabolically abnormal, or malignant cells that are resistant to chemotherapeutic drugs often plays important roles in disease progression and severity. Accordingly, the PP pathway has been suggested to play critical roles in protecting cancer or abnormal cells by providing reduced environment, to protect cells from oxidative damage and generating structural components for nucleic acids biosynthesis. Novel drugs that targets one or more components of the PP pathway could potentially serve to overcome challenges associated with currently available therapeutic options for many metabolic and non-metabolic diseases. However, careful designing of drugs is critical that takes into the accounts of cell’s broader genomic, proteomic and metabolic contexts under consideration, in order to avoid undesirable side-effects. In this review, we discuss the role of PP pathway under normal and abnormal physiological conditions and the potential of the PP pathway as a target for new drug development to treat metabolic and non-metabolic diseases.

scholarly journals Pathway swapping: Toward modular engineering of essential cellular processes

2016 ◽  
Vol 113 (52) ◽  
pp. 15060-15065 ◽  
Author(s):  
Niels G. A. Kuijpers ◽  
Daniel Solis-Escalante ◽  
Marijke A. H. Luttik ◽  
Markus M. M. Bisschops ◽  
Francine J. Boonekamp ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Metabolic Pathways ◽  
Applied Research ◽  
Central Metabolism ◽  
Microbial Genomes ◽  
Cellular Processes ◽  
Recent Developments ◽  
One Step ◽  
Saccharomyces Kudriavzevii

Recent developments in synthetic biology enable one-step implementation of entire metabolic pathways in industrial microorganisms. A similarly radical remodelling of central metabolism could greatly accelerate fundamental and applied research, but is impeded by the mosaic organization of microbial genomes. To eliminate this limitation, we propose and explore the concept of “pathway swapping,” using yeast glycolysis as the experimental model. Construction of a “single-locus glycolysis” Saccharomyces cerevisiae platform enabled quick and easy replacement of this yeast’s entire complement of 26 glycolytic isoenzymes by any alternative, functional glycolytic pathway configuration. The potential of this approach was demonstrated by the construction and characterization of S. cerevisiae strains whose growth depended on two nonnative glycolytic pathways: a complete glycolysis from the related yeast Saccharomyces kudriavzevii and a mosaic glycolysis consisting of yeast and human enzymes. This work demonstrates the feasibility and potential of modular, combinatorial approaches to engineering and analysis of core cellular processes.

IDENTIFYING RELEVANT PATHWAYS AND BIOMARKERS IN CROHN’S DISEASE USING CONTEXTUALIZED METABOLIC NETWORK MODEL

2021 ◽  
Vol 27 (Supplement_1) ◽  
pp. S9-S10
Author(s):  
Brooklyn McGrew ◽  
Aman Shrivastava ◽  
Philip Fernandes ◽  
Lubaina Ehsan ◽  
Yash Sharma ◽  
...  
Keyword(s):  
Gene Expression ◽  
Crohn’S Disease ◽  
Fatty Acid ◽  
Crohn's Disease ◽  
Fatty Acid Synthesis ◽  
Metabolic Pathway ◽  
Metabolic Pathways ◽  
Acid Synthesis ◽  
Transcriptomic Data ◽  
Context Specific

Abstract Background Candidate markers for Crohn’s Disease (CD) may be identified via gene expression-based construction of metabolic networks (MN). These can computationally describe gene-protein-reaction associations for entire tissues and also predict the flux of reactions (rate of turnover of specific molecules via a metabolic pathway). Recon3D is the most comprehensive human MN to date. We used publicly available CD transcriptomic data along with Recon3D to identify metabolites as potential diagnostic and prognostic biomarkers. Methods Terminal ileal gene expression profiles (36,372 genes; 218 CD. 42 controls) from the RISK cohort (Risk Stratification and Identification of Immunogenetic and Microbial Markers of Rapid Disease Progression in Children with Crohn’s Disease) and their transcriptomic abundances were used. Recon3D was pruned to only include RISK dataset transcripts which determined metabolic reaction linkage with transcriptionally active genes. Flux balance analysis (FBA) was then run using RiPTiDe with context specific transcriptomic data to further constrain genes (Figure 1). RiPTiDe was independently run on transcriptomic data from both CD and controls. From the pruned and constricted MN obtained, reactions were extracted for further analysis. Results After applying the necessary constraints to modify Recon3D, 527 CD and 537 control reactions were obtained. Reaction comparison with a publicly available list of healthy small intestinal epithelial reactions (n=1282) showed an overlap of 80 CD and 84 control reactions. These were then further grouped based on their metabolic pathways. RiPTiDe identified context specific metabolic pathway activity without supervision and the percentage of forward, backward, and balanced reactions for each metabolic pathway (Figure 2). The metabolite concentrations in the small intestine was altered among CD patients. Notably, the citric acid cycle and malate-aspartate shuttle were affected, highlighting changes in mitochondrial metabolic pathways. This is illustrated by changes in the number of reactions at equilibrium between CD and control. Conclusions The results are relevant as cytosolic acetyl-CoA is needed for fatty acid synthesis and is obtained by removing citrate from the citric acid cycle. An intermediate removal from the cycle has significant cataplerotic effects. The malate-aspartate shuttle also allows electrons to move across the impermeable membrane in the mitochondria (fatty acid synthesis location). These findings are reported by previously published studies where gene expression for fatty acid synthesis is altered in CD patients along with mitochondrial metabolic pathway changes, resulting in altered cell homeostasis. In-depth analysis is currently underway with our work supporting the utility of potential metabolic biomarkers for CD diagnosis, management and improved care.

scholarly journals Structural Basis of Functional Group Activation by Sulfotransferases in Complex Metabolic Pathways

2012 ◽  
Vol 7 (12) ◽  
pp. 1994-2003 ◽  
Author(s):  
Jennifer Gehret McCarthy ◽  
Eli B. Eisman ◽  
Sarang Kulkarni ◽  
Lena Gerwick ◽  
William H. Gerwick ◽  
...  
Keyword(s):  
Metabolic Pathways ◽  
Functional Group ◽  
Structural Basis

scholarly journals Genome Evolution at the Genus Level: Comparison of Three Complete Genomes of Hyperthermophilic Archaea

2001 ◽  
Vol 11 (6) ◽  
pp. 981-993
Author(s):  
Odile Lecompte ◽  
Raymond Ripp ◽  
Valérie Puzos-Barbe ◽  
Simone Duprat ◽  
Roland Heilig ◽  
...  
Keyword(s):  
Pyrococcus Furiosus ◽  
Hyperthermophilic Archaea ◽  
Trna Genes ◽  
Distance Ratio ◽  
Genomic Plasticity ◽  
Relative Contribution ◽  
Complete Genomes ◽  
Replication Terminus ◽  
Living Organisms ◽  
High Level

We have compared three complete genomes of closely related hyperthermophilic species of Archaea belonging to thePyrococcus genus: Pyrococcus abyssi, Pyrococcus horikoshii, and Pyrococcus furiosus. At the genomic level, the comparison reveals a differential conservation among four regions of the Pyrococcus chromosomes correlated with the location of genetic elements mediating DNA reorganization. This discloses the relative contribution of the major mechanisms that promote genomic plasticity in these Archaea, namely rearrangements linked to the replication terminus, insertion sequence-mediated recombinations, and DNA integration within tRNA genes. The combination of these mechanisms leads to a high level of genomic plasticity in these hyperthermophilic Archaea, at least comparable to the plasticity observed between closely related bacteria. At the proteomic level, the comparison of the threePyrococcus species sheds light on specific selection pressures acting both on their coding capacities and evolutionary rates. Indeed, thanks to two independent methods, the “reciprocal best hits“ approach and a new distance ratio analysis, we detect the false orthology relationships within the Pyrococcus lineage. This reveals a high amount of differential gains and losses of genes since the divergence of the three closely related species. The resulting polymorphism is probably linked to an adaptation of these free-living organisms to differential environmental constraints. As a corollary, we delineate the set of orthologous genes shared by the three species, that is, the genes that may characterize the Pyrococcus genus. In this conserved core, the amino acid substitution rate is equal between P. abyssi and P. horikoshii for most of their shared proteins, even for fast-evolving ones. In contrast, strong discrepancies exist among the substitution rates observed in P. furiosus relative to the two other species, which is in disagreement with the molecular clock hypothesis.

scholarly journals Uncovering miRNAs involved in crosstalk between nutrient deficiencies in Arabidopsis

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Gang Liang ◽  
Qin Ai ◽  
Diqiu Yu
Keyword(s):  
Metabolic Pathways ◽  
Nutrient Deficiency ◽  
Differentially Expressed ◽  
Nutrient Deficiencies ◽  
Nutrient Metabolism ◽  
S Deficiency ◽  
Differentially Expressed Mirnas ◽  
Living Organisms ◽  
Nutrient Homeostasis ◽  
Mirna Abundance

Abstract Integrating carbon (C), nitrogen (N) and sulfur (S) metabolism is essential for the growth and development of living organisms. MicroRNAs (miRNAs) play key roles in regulating nutrient metabolism in plants. However, how plant miRNAs mediate crosstalk between different nutrient metabolic pathways is unclear. In this study, deep sequencing of Arabidopsis thaliana small RNAs was used to reveal miRNAs that were differentially expressed in response to C, N, or S deficiency. Comparative analysis revealed that the targets of the differentially expressed miRNAs are involved in different cellular responses and metabolic processes, including transcriptional regulation, auxin signal transduction, nutrient homeostasis and regulation of development. C, N and S deficiency specifically induced miR169b/c, miR826 and miR395, respectively. In contrast, miR167, miR172, miR397, miR398, miR399, miR408, miR775, miR827, miR841, miR857 and miR2111 are commonly suppressed by C, N and S deficiency. In particular, the miRNAs that are induced specifically by a certain nutrient deficiency are often suppressed by other nutrient deficiencies. Further investigation indicated that the modulation of nutrient-responsive miRNA abundance affects the adaptation of plants to nutrient starvation conditions. This study revealed that miRNAs function as important regulatory nodes of different nutrient metabolic pathways.

scholarly journals Metabolic Pathway Genes Associated with Susceptibility Genes to Coronary Artery Disease

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Heng Lu ◽  
Yi Chen ◽  
Linlin Li
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Metabolic Pathway ◽  
Metabolic Pathways ◽  
Blood Lipids ◽  
Single Gene ◽  
Susceptibility Genes ◽  
Metabolic Factors ◽  
Citrate Cycle ◽  
Artery Disease

Coronary artery disease (CAD) is one of the leading threats to global health. Previous research has proven that metabolic pathway disorders, such as high blood lipids and diabetes, are one of the risk factors that mostly cause CAD. However, the crosstalk between metabolic pathways and CAD was mostly studied on physiology processes by analyzing a single gene function. A canonical correlation analysis was used to identify the metabolic pathways, which were integrated as a unit to coexpress with CAD susceptibility genes, and to resolve additional metabolic factors that are related to CAD. Seven pathways, including citrate cycle, ubiquinone, terpenoid quinone biosynthesis, and N-glycan biosynthesis, were identified as an integrated unit coexpressed with CAD genes. These pathways could not be revealed as a coexpressed pathway through traditional methods as each single gene has weak correlation. Furthermore, sets of genes in these pathways were candidate markers for diagnosis and detection from patients’ serum.

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