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Modeling Metabolism and Finding New Antibiotics. Bioinformatics 2023. [DOI: 10.1007/978-3-662-65036-3_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023] Open
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2
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Narad P, Naresh G, Sengupta A. Metabolomics and flux balance analysis. Bioinformatics 2022. [DOI: 10.1016/b978-0-323-89775-4.00008-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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3
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Osmanoglu Ö, Khaled AlSeiari M, AlKhoori HA, Shams S, Bencurova E, Dandekar T, Naseem M. Topological Analysis of the Carbon-Concentrating CETCH Cycle and a Photorespiratory Bypass Reveals Boosted CO 2-Sequestration by Plants. Front Bioeng Biotechnol 2021; 9:708417. [PMID: 34790651 PMCID: PMC8591258 DOI: 10.3389/fbioe.2021.708417] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 08/25/2021] [Indexed: 01/11/2023] Open
Abstract
Synthetically designed alternative photorespiratory pathways increase the biomass of tobacco and rice plants. Likewise, some in planta-tested synthetic carbon-concentrating cycles (CCCs) hold promise to increase plant biomass while diminishing atmospheric carbon dioxide burden. Taking these individual contributions into account, we hypothesize that the integration of bypasses and CCCs will further increase plant productivity. To test this in silico, we reconstructed a metabolic model by integrating photorespiration and photosynthesis with the synthetically designed alternative pathway 3 (AP3) enzymes and transporters. We calculated fluxes of the native plant system and those of AP3 combined with the inhibition of the glycolate/glycerate transporter by using the YANAsquare package. The activity values corresponding to each enzyme in photosynthesis, photorespiration, and for synthetically designed alternative pathways were estimated. Next, we modeled the effect of the crotonyl-CoA/ethylmalonyl-CoA/hydroxybutyryl-CoA cycle (CETCH), which is a set of natural and synthetically designed enzymes that fix CO₂ manifold more than the native Calvin-Benson-Bassham (CBB) cycle. We compared estimated fluxes across various pathways in the native model and under an introduced CETCH cycle. Moreover, we combined CETCH and AP3-w/plgg1RNAi, and calculated the fluxes. We anticipate higher carbon dioxide-harvesting potential in plants with an AP3 bypass and CETCH-AP3 combination. We discuss the in vivo implementation of these strategies for the improvement of C3 plants and in natural high carbon harvesters.
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Affiliation(s)
- Özge Osmanoglu
- Department of Bioinformatics, Functional Genomics and Systems Biology Group, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany
| | - Mariam Khaled AlSeiari
- College of Natural and Health Sciences, Department of Life and Environmental Sciences, Zayed University, Abu Dhabi, UAE
| | - Hasa Abduljaleel AlKhoori
- College of Natural and Health Sciences, Department of Life and Environmental Sciences, Zayed University, Abu Dhabi, UAE
| | - Shabana Shams
- Department of Animal Sciences, Quaid-i-Azam University, Islamabad, Pakistan
| | - Elena Bencurova
- Department of Bioinformatics, Functional Genomics and Systems Biology Group, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany
| | - Thomas Dandekar
- Department of Bioinformatics, Functional Genomics and Systems Biology Group, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany
| | - Muhammad Naseem
- Department of Bioinformatics, Functional Genomics and Systems Biology Group, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany
- College of Natural and Health Sciences, Department of Life and Environmental Sciences, Zayed University, Abu Dhabi, UAE
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4
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Pusa T, Ferrarini MG, Andrade R, Mary A, Marchetti-Spaccamela A, Stougie L, Sagot MF. MOOMIN - Mathematical explOration of 'Omics data on a MetabolIc Network. Bioinformatics 2019; 36:514-523. [PMID: 31504164 PMCID: PMC9883724 DOI: 10.1093/bioinformatics/btz584] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 07/16/2019] [Accepted: 08/19/2019] [Indexed: 02/03/2023] Open
Abstract
MOTIVATION Analysis of differential expression of genes is often performed to understand how the metabolic activity of an organism is impacted by a perturbation. However, because the system of metabolic regulation is complex and all changes are not directly reflected in the expression levels, interpreting these data can be difficult. RESULTS In this work, we present a new algorithm and computational tool that uses a genome-scale metabolic reconstruction to infer metabolic changes from differential expression data. Using the framework of constraint-based analysis, our method produces a qualitative hypothesis of a change in metabolic activity. In other words, each reaction of the network is inferred to have increased, decreased, or remained unchanged in flux. In contrast to similar previous approaches, our method does not require a biological objective function and does not assign on/off activity states to genes. An implementation is provided and it is available online. We apply the method to three published datasets to show that it successfully accomplishes its two main goals: confirming or rejecting metabolic changes suggested by differentially expressed genes based on how well they fit in as parts of a coordinated metabolic change, as well as inferring changes in reactions whose genes did not undergo differential expression. AVAILABILITY AND IMPLEMENTATION github.com/htpusa/moomin. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Taneli Pusa
- To whom correspondence should be addressed. or
| | - Mariana Galvão Ferrarini
- Laboratoire de Biométrie et Biologie Évolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon 1, Villeurbanne 69622, France,Univ Lyon, INSA-Lyon, INRA, BF2i, UMR0203, F-69621, Villeurbanne 69622, France
| | - Ricardo Andrade
- INRIA Grenoble Rhône-Alpes, Montbonnot-Saint-Martin 38334, France,Laboratoire de Biométrie et Biologie Évolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon 1, Villeurbanne 69622, France
| | - Arnaud Mary
- INRIA Grenoble Rhône-Alpes, Montbonnot-Saint-Martin 38334, France,Laboratoire de Biométrie et Biologie Évolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon 1, Villeurbanne 69622, France
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5
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Srivastava M, Bencurova E, Gupta SK, Weiss E, Löffler J, Dandekar T. Aspergillus fumigatus Challenged by Human Dendritic Cells: Metabolic and Regulatory Pathway Responses Testify a Tight Battle. Front Cell Infect Microbiol 2019; 9:168. [PMID: 31192161 PMCID: PMC6540932 DOI: 10.3389/fcimb.2019.00168] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 05/06/2019] [Indexed: 12/18/2022] Open
Abstract
Dendritic cells (DCs) are antigen presenting cells which serve as a passage between the innate and the acquired immunity. Aspergillosis is a major lethal condition in immunocompromised patients caused by the adaptable saprophytic fungus Aspergillus fumigatus. The healthy human immune system is capable to ward off A. fumigatus infections however immune-deficient patients are highly vulnerable to invasive aspergillosis. A. fumigatus can persist during infection due to its ability to survive the immune response of human DCs. Therefore, the study of the metabolism specific to the context of infection may allow us to gain insight into the adaptation strategies of both the pathogen and the immune cells. We established a metabolic model of A. fumigatus central metabolism during infection of DCs and calculated the metabolic pathway (elementary modes; EMs). Transcriptome data were used to identify pathways activated when A. fumigatus is challenged with DCs. In particular, amino acid metabolic pathways, alternative carbon metabolic pathways and stress regulating enzymes were found to be active. Metabolic flux modeling identified further active enzymes such as alcohol dehydrogenase, inositol oxygenase and GTP cyclohydrolase participating in different stress responses in A. fumigatus. These were further validated by qRT-PCR from RNA extracted under these different conditions. For DCs, we outlined the activation of metabolic pathways in response to the confrontation with A. fumigatus. We found the fatty acid metabolism plays a crucial role, along with other metabolic changes. The gene expression data and their analysis illuminate additional regulatory pathways activated in the DCs apart from interleukin regulation. In particular, Toll-like receptor signaling, NOD-like receptor signaling and RIG-I-like receptor signaling were active pathways. Moreover, we identified subnetworks and several novel key regulators such as UBC, EGFR, and CUL3 of DCs to be activated in response to A. fumigatus. In conclusion, we analyze the metabolic and regulatory responses of A. fumigatus and DCs when confronted with each other.
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Affiliation(s)
- Mugdha Srivastava
- Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany
| | - Elena Bencurova
- Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany
| | - Shishir K Gupta
- Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany
| | - Esther Weiss
- Department of Internal Medicine II, University Hospital of Würzburg, Würzburg, Germany
| | - Jürgen Löffler
- Department of Internal Medicine II, University Hospital of Würzburg, Würzburg, Germany
| | - Thomas Dandekar
- Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany.,EMBL Heidelberg, Structural and Computational Biology, Heidelberg, Germany
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6
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Identification of Antifungal Targets Based on Computer Modeling. J Fungi (Basel) 2018; 4:jof4030081. [PMID: 29973534 PMCID: PMC6162656 DOI: 10.3390/jof4030081] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 06/24/2018] [Accepted: 06/29/2018] [Indexed: 01/07/2023] Open
Abstract
Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host⁻pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools.
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Khan S, Bhardwaj T, Somvanshi P, Mandal RK, Dar SA, Jawed A, Wahid M, Akhter N, Lohani M, Alouffi S, Haque S. Inhibition of C298S mutant of human aldose reductase for antidiabetic applications: Evidence from in silico elementary mode analysis of biological network model. J Cell Biochem 2018; 119:6961-6973. [PMID: 29693278 DOI: 10.1002/jcb.26904] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Accepted: 03/28/2018] [Indexed: 01/05/2023]
Abstract
Human aldose reductase (hAR) is the key enzyme in sorbitol pathway of glucose utilization and is implicated in the etiology of secondary complications of diabetes, such as, cardiovascular complications, neuropathy, nephropathy, retinopathy, and cataract genesis. It reduces glucose to sorbitol in the presence of NADPH and the major cause of diabetes complications could be the change in the osmotic pressure due to the accumulation of sorbitol. An activated form of hAR (activated hAR or ahAR) poses a potential obstacle in the development of diabetes drugs as hAR-inhibitors are ineffective against ahAR. The therapeutic efficacy of such drugs is compromised when a large fraction of the enzyme (hAR) undergoes conversion to the activated ahAR form as has been observed in the diabetic tissues. In the present study, attempts have been made to employ systems biology strategies to identify the elementary nodes of human polyol metabolic pathway, responsible for normal metabolic states, followed by the identification of natural potent inhibitors of the activated form of hAR represented by the mutant C298S for possible antidiabetic applications. Quantum Mechanical Molecular Mechanical docking strategy was used to determine the probable inhibitors of ahAR. Rosmarinic acid was found as the most potent natural ahAR inhibitor and warrants for experimental validation in the near future.
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Affiliation(s)
- Saif Khan
- Department of Clinical Laboratory Science, College of Applied Medical Sciences, University of Ha'il, Ha'il, Saudi Arabia
| | - Tulika Bhardwaj
- Department of Biotechnology, TERI School of Advanced Studies, New Delhi, India
| | - Pallavi Somvanshi
- Department of Biotechnology, TERI School of Advanced Studies, New Delhi, India
| | - Raju K Mandal
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia
| | - Sajad A Dar
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia
| | - Arshad Jawed
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia
| | - Mohd Wahid
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia
| | - Naseem Akhter
- Faculty of Applied Medical Sciences, Department of Laboratory Medicine, Albaha University, Albaha, Saudi Arabia
| | - Mohtashim Lohani
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia
| | - S Alouffi
- Department of Clinical Laboratory Science, College of Applied Medical Sciences, University of Ha'il, Ha'il, Saudi Arabia
| | - Shafiul Haque
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia
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8
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Samal SS, Radulescu O, Weber A, Fröhlich H. Linking metabolic network features to phenotypes using sparse group lasso. Bioinformatics 2017; 33:3445-3453. [DOI: 10.1093/bioinformatics/btx427] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2016] [Accepted: 06/30/2017] [Indexed: 12/19/2022] Open
Affiliation(s)
- Satya Swarup Samal
- Algorithmic Bioinformatics, Bonn-Aachen International Center for IT, Bonn, Germany
| | - Ovidiu Radulescu
- DIMNP UMR CNRS 5235, University of Montpellier, Montpellier, France
| | - Andreas Weber
- Institut für Informatik II, University of Bonn, Bonn, Germany
| | - Holger Fröhlich
- Algorithmic Bioinformatics, Bonn-Aachen International Center for IT, Bonn, Germany
- UCB Biosciences GmbH, Monheim, Germany
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9
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Klamt S, Regensburger G, Gerstl MP, Jungreuthmayer C, Schuster S, Mahadevan R, Zanghellini J, Müller S. From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints. PLoS Comput Biol 2017; 13:e1005409. [PMID: 28406903 PMCID: PMC5390976 DOI: 10.1371/journal.pcbi.1005409] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks.
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Affiliation(s)
- Steffen Klamt
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Georg Regensburger
- Institute for Algebra, Johannes Kepler University Linz (JKU), Linz, Austria
| | - Matthias P. Gerstl
- Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria
- Austrian Centre of Biotechnology, Vienna, Austria
| | - Christian Jungreuthmayer
- Austrian Centre of Biotechnology, Vienna, Austria
- TGM - Technologisches Gewerbemuseum, Vienna, Austria
| | - Stefan Schuster
- Department of Bioinformatics, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, Jena, Germany
| | - Radhakrishnan Mahadevan
- Department of Chemical Engineering & Applied Chemistry, Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Jürgen Zanghellini
- Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria
- Austrian Centre of Biotechnology, Vienna, Austria
| | - Stefan Müller
- Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Linz, Austria
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Cerqueda-García D, Falcón LI. Metabolic potential of microbial mats and microbialites: Autotrophic capabilities described by an in silico stoichiometric approach from shared genomic resources. J Bioinform Comput Biol 2016; 14:1650020. [PMID: 27324427 DOI: 10.1142/s0219720016500207] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Microbialites and microbial mats are complex communities with high phylogenetic diversity. These communities are mostly composed of bacteria and archaea, which are the earliest living forms on Earth and relevant to biogeochemical evolution. In this study, we identified the shared metabolic pathways for uptake of inorganic C and N in microbial mats and microbialites based on metagenomic data sets. An in silico analysis for autotrophic pathways was used to trace the paths of C and N to the system, following an elementary flux modes (EFM) approach, resulting in a stoichiometric model. The fragility was analyzed by the minimal cut sets method. We found four relevant pathways for the incorporation of CO2 (Calvin cycle, reverse tricarboxylic acid cycle, reductive acetyl-CoA pathway, and dicarboxylate/4-hydroxybutyrate cycle), some of them present only in archaea, while nitrogen fixation was the most important source of N to the system. The metabolic potential to incorporate nitrate to biomass was also relevant. The fragility of the network was low, suggesting a high redundancy of the autotrophic pathways due to their broad metabolic diversity, and highlighting the relevance of reducing power source. This analysis suggests that microbial mats and microbialites are "metabolic pumps" for the incorporation of inorganic gases and formation of organic matter.
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Affiliation(s)
- Daniel Cerqueda-García
- 1 Universidad Nacional Autónoma de México, Instituto de Ecología, Circuito Exterior, Ciudad Universitaria, Distrito Federal 04510, Mexico
| | - Luisa I Falcón
- 1 Universidad Nacional Autónoma de México, Instituto de Ecología, Circuito Exterior, Ciudad Universitaria, Distrito Federal 04510, Mexico
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11
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Kaltdorf M, Srivastava M, Gupta SK, Liang C, Binder J, Dietl AM, Meir Z, Haas H, Osherov N, Krappmann S, Dandekar T. Systematic Identification of Anti-Fungal Drug Targets by a Metabolic Network Approach. Front Mol Biosci 2016; 3:22. [PMID: 27379244 PMCID: PMC4911368 DOI: 10.3389/fmolb.2016.00022] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 05/24/2016] [Indexed: 11/13/2022] Open
Abstract
New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness ("hubs"), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.
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Affiliation(s)
- Martin Kaltdorf
- Department of Bioinformatics, Biocenter, University of Würzburg Würzburg, Germany
| | - Mugdha Srivastava
- Department of Bioinformatics, Biocenter, University of Würzburg Würzburg, Germany
| | - Shishir K Gupta
- Department of Bioinformatics, Biocenter, University of Würzburg Würzburg, Germany
| | - Chunguang Liang
- Department of Bioinformatics, Biocenter, University of Würzburg Würzburg, Germany
| | - Jasmin Binder
- Microbiology Institute - Clinical Microbiology, Immunology and Hygiene, Friedrich-Alexander University Erlangen-Nürnberg, University Hospital of Erlangen Erlangen, Germany
| | - Anna-Maria Dietl
- Division of Molecular Biology/Biocenter, Medical University Innsbruck Innsbruck, Austria
| | - Zohar Meir
- Aspergillus and Antifungal Research Laboratory, Department of Clinical Microbiology and Immunology, Sackler School of Medicine, Tel Aviv University Tel-Aviv, Israel
| | - Hubertus Haas
- Division of Molecular Biology/Biocenter, Medical University Innsbruck Innsbruck, Austria
| | - Nir Osherov
- Aspergillus and Antifungal Research Laboratory, Department of Clinical Microbiology and Immunology, Sackler School of Medicine, Tel Aviv University Tel-Aviv, Israel
| | - Sven Krappmann
- Microbiology Institute - Clinical Microbiology, Immunology and Hygiene, Friedrich-Alexander University Erlangen-Nürnberg, University Hospital of Erlangen Erlangen, Germany
| | - Thomas Dandekar
- Department of Bioinformatics, Biocenter, University of Würzburg Würzburg, Germany
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Elementary Flux Mode Analysis Revealed Cyclization Pathway as a Powerful Way for NADPH Regeneration of Central Carbon Metabolism. PLoS One 2015; 10:e0129837. [PMID: 26086807 PMCID: PMC4472234 DOI: 10.1371/journal.pone.0129837] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2014] [Accepted: 05/13/2015] [Indexed: 01/18/2023] Open
Abstract
NADPH regeneration capacity is attracting growing research attention due to its important role in resisting oxidative stress. Besides, NADPH availability has been regarded as a limiting factor in production of industrially valuable compounds. The central carbon metabolism carries the carbon skeleton flux supporting the operation of NADPH-regenerating enzyme and offers flexibility in coping with NADPH demand for varied intracellular environment. To acquire an insightful understanding of its NADPH regeneration capacity, the elementary mode method was employed to compute all elementary flux modes (EFMs) of a network representative of central carbon metabolism. Based on the metabolic flux distributions of these modes, a cluster analysis of EFMs with high NADPH regeneration rate was conducted using the self-organizing map clustering algorithm. The clustering results were used to study the relationship between the flux of total NADPH regeneration and the flux in each NADPH producing enzyme. The results identified several reaction combinations supporting high NADPH regeneration, which are proven to be feasible in cells via thermodynamic analysis and coincident with a great deal of previous experimental report. Meanwhile, the reaction combinations showed some common characteristics: there were one or two decarboxylation oxidation reactions in the combinations that produced NADPH and the combination constitution included certain gluconeogenesis pathways. These findings suggested cyclization pathways as a powerful way for NADPH regeneration capacity of bacterial central carbon metabolism.
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Horvat P, Koller M, Braunegg G. Recent advances in elementary flux modes and yield space analysis as useful tools in metabolic network studies. World J Microbiol Biotechnol 2015; 31:1315-28. [DOI: 10.1007/s11274-015-1887-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Accepted: 06/05/2015] [Indexed: 11/25/2022]
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14
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Cecil A, Ohlsen K, Menzel T, François P, Schrenzel J, Fischer A, Dörries K, Selle M, Lalk M, Hantzschmann J, Dittrich M, Liang C, Bernhardt J, Ölschläger TA, Bringmann G, Bruhn H, Unger M, Ponte-Sucre A, Lehmann L, Dandekar T. Modelling antibiotic and cytotoxic isoquinoline effects in Staphylococcus aureus, Staphylococcus epidermidis and mammalian cells. Int J Med Microbiol 2014; 305:96-109. [PMID: 25500547 DOI: 10.1016/j.ijmm.2014.11.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2013] [Revised: 10/16/2014] [Accepted: 11/09/2014] [Indexed: 12/15/2022] Open
Abstract
Isoquinolines (IQs) are natural substances with an antibiotic potential we aim to optimize. Specifically, IQ-238 is a synthetic analog of the novel-type N,C-coupled naphthylisoquinoline (NIQ) alkaloid ancisheynine. Recently, we developed and tested other IQs such as IQ-143. By utilizing genome-wide gene expression data, metabolic network modelling and Voronoi tessalation based data analysis - as well as cytotoxicity measurements, chemical properties calculations and principal component analysis of the NIQs - we show that IQ-238 has strong antibiotic potential for staphylococci and low cytotoxicity against murine or human cells. Compared to IQ-143, systemic effects are less pronounced. Most enzyme activity changes due to IQ-238 are located in the carbohydrate metabolism. Validation includes metabolite measurements on biological replicates. IQ-238 delineates key properties and a chemical space for a good therapeutic window. The combination of analysis methods allows suggestions for further lead development and yields an in-depth look at staphylococcal adaptation and network changes after antibiosis. Results are compared to eukaryotic host cells.
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Affiliation(s)
- Alexander Cecil
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074 Würzburg, Germany
| | - Knut Ohlsen
- University of Würzburg, Institute for Molecular-Infection Biology, 97070 Würzburg, Germany
| | - Thomas Menzel
- University of Würzburg, Institute for Molecular-Infection Biology, 97070 Würzburg, Germany
| | - Patrice François
- Genomic Research Laboratory, Service of Infectious Diseases, University of Geneva Hospitals, Rue Gabrielle-Perret-Gentil 4, CH-1211 Geneva 14, Switzerland
| | - Jacques Schrenzel
- Genomic Research Laboratory, Service of Infectious Diseases, University of Geneva Hospitals, Rue Gabrielle-Perret-Gentil 4, CH-1211 Geneva 14, Switzerland
| | - Adrien Fischer
- Genomic Research Laboratory, Service of Infectious Diseases, University of Geneva Hospitals, Rue Gabrielle-Perret-Gentil 4, CH-1211 Geneva 14, Switzerland
| | - Kirsten Dörries
- Institute of Biochemistry, Ernst-Moritz-Arndt-University Greifswald, Felix-Hausdorff-Straße 4, D-17487 Greifswald, Germany
| | - Martina Selle
- University of Würzburg, Institute for Molecular-Infection Biology, 97070 Würzburg, Germany
| | - Michael Lalk
- Institute of Biochemistry, Ernst-Moritz-Arndt-University Greifswald, Felix-Hausdorff-Straße 4, D-17487 Greifswald, Germany
| | - Julia Hantzschmann
- University of Würzburg, Institute for Molecular-Infection Biology, 97070 Würzburg, Germany
| | - Marcus Dittrich
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074 Würzburg, Germany
| | - Chunguang Liang
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074 Würzburg, Germany
| | - Jörg Bernhardt
- Institute for Microbiology, Ernst-Moritz-Arndt-University Greifswald, Friedrich-Ludwig-Jahn Strasse 15, D-17487 Greifswald, Germany
| | - Tobias A Ölschläger
- University of Würzburg, Institute for Molecular-Infection Biology, 97070 Würzburg, Germany
| | - Gerhard Bringmann
- University of Würzburg, Institute for Organic Chemistry, Am Hubland, 97074 Würzburg, Germany
| | - Heike Bruhn
- University of Würzburg, Institute for Molecular-Infection Biology, 97070 Würzburg, Germany
| | - Matthias Unger
- University of Würzburg, Institute for Pharmacy and Food Chemistry, Am Hubland, 97074 Würzburg, Germany
| | - Alicia Ponte-Sucre
- Laboratory of Molecular Physiology, Universidad Central de Venezuela, Caracas, Venezuela
| | - Leane Lehmann
- University of Würzburg, Institute for Pharmacy and Food Chemistry, Am Hubland, 97074 Würzburg, Germany
| | - Thomas Dandekar
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074 Würzburg, Germany; EMBL Heidelberg, BioComputing Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany.
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15
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Rezola A, Pey J, Tobalina L, Rubio A, Beasley JE, Planes FJ. Advances in network-based metabolic pathway analysis and gene expression data integration. Brief Bioinform 2014; 16:265-79. [DOI: 10.1093/bib/bbu009] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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16
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Hyun TK, Lee S, Rim Y, Kumar R, Han X, Lee SY, Lee CH, Kim JY. De-novo RNA sequencing and metabolite profiling to identify genes involved in anthocyanin biosynthesis in Korean black raspberry (Rubus coreanus Miquel). PLoS One 2014; 9:e88292. [PMID: 24505466 PMCID: PMC3914977 DOI: 10.1371/journal.pone.0088292] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2013] [Accepted: 01/07/2014] [Indexed: 11/28/2022] Open
Abstract
The Korean black raspberry (Rubus coreanus Miquel, KB) on ripening is usually consumed as fresh fruit, whereas the unripe KB has been widely used as a source of traditional herbal medicine. Such a stage specific utilization of KB has been assumed due to the changing metabolite profile during fruit ripening process, but so far molecular and biochemical changes during its fruit maturation are poorly understood. To analyze biochemical changes during fruit ripening process at molecular level, firstly, we have sequenced, assembled, and annotated the transcriptome of KB fruits. Over 4.86 Gb of normalized cDNA prepared from fruits was sequenced using Illumina HiSeq™ 2000, and assembled into 43,723 unigenes. Secondly, we have reported that alterations in anthocyanins and proanthocyanidins are the major factors facilitating variations in these stages of fruits. In addition, up-regulation of F3'H1, DFR4 and LDOX1 resulted in the accumulation of cyanidin derivatives during the ripening process of KB, indicating the positive relationship between the expression of anthocyanin biosynthetic genes and the anthocyanin accumulation. Furthermore, the ability of RcMCHI2 (R. coreanus Miquel chalcone flavanone isomerase 2) gene to complement Arabidopsis transparent testa 5 mutant supported the feasibility of our transcriptome library to provide the gene resources for improving plant nutrition and pigmentation. Taken together, these datasets obtained from transcriptome library and metabolic profiling would be helpful to define the gene-metabolite relationships in this non-model plant.
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Affiliation(s)
- Tae Kyung Hyun
- Division of Applied Life Science (BK21plus), Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju, Republic of Korea
| | - Sarah Lee
- Division of Bioscience and Biotechnology, Konkuk University, Seoul, Republic of Korea
| | - Yeonggil Rim
- Division of Applied Life Science (BK21plus), Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju, Republic of Korea
| | - Ritesh Kumar
- Division of Applied Life Science (BK21plus), Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju, Republic of Korea
| | - Xiao Han
- Division of Applied Life Science (BK21plus), Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju, Republic of Korea
| | - Sang Yeol Lee
- Division of Applied Life Science (BK21plus), Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju, Republic of Korea
| | - Choong Hwan Lee
- Division of Bioscience and Biotechnology, Konkuk University, Seoul, Republic of Korea
| | - Jae-Yean Kim
- Division of Applied Life Science (BK21plus), Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju, Republic of Korea
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Kumar M, Saini S, Gayen K. Elementary mode analysis reveals that Clostridium acetobutylicum modulates its metabolic strategy under external stress. ACTA ACUST UNITED AC 2014; 10:2090-105. [DOI: 10.1039/c4mb00126e] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Clostridium acetobutylicumis a strict anaerobe which exhibits two distinct steps in its metabolic network.
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Affiliation(s)
- Manish Kumar
- Department of Chemical Engineering
- Indian Institute of Technology Gandhinagar
- Ahmedabad - 382424, India
| | - Supreet Saini
- Department of Chemical Engineering
- Indian Institute of Technology Bombay
- Mumbai - 400076, India
| | - Kalyan Gayen
- Department of Chemical Engineering
- National Institute of Technology Agartala
- Tripura - 799053, India
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18
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Metabolic analysis of Chlorobium chlorochromatii CaD3 reveals clues of the symbiosis in 'Chlorochromatium aggregatum'. ISME JOURNAL 2013; 8:991-8. [PMID: 24285361 DOI: 10.1038/ismej.2013.207] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2013] [Revised: 09/25/2013] [Accepted: 10/07/2013] [Indexed: 11/08/2022]
Abstract
A symbiotic association occurs in 'Chlorochromatium aggregatum', a phototrophic consortium integrated by two species of phylogenetically distant bacteria composed by the green-sulfur Chlorobium chlorochromatii CaD3 epibiont that surrounds a central β-proteobacterium. The non-motile chlorobia can perform nitrogen and carbon fixation, using sulfide as electron donors for anoxygenic photosynthesis. The consortium can move due to the flagella present in the central β-protobacterium. Although Chl. chlorochromatii CaD3 is never found as free-living bacteria in nature, previous transcriptomic and proteomic studies have revealed that there are differential transcription patterns between the symbiotic and free-living status of Chl. chlorocromatii CaD3 when grown in laboratory conditions. The differences occur mainly in genes encoding the enzymatic reactions involved in nitrogen and amino acid metabolism. We performed a metabolic reconstruction of Chl. chlorochromatii CaD3 and an in silico analysis of its amino acid metabolism using an elementary flux modes approach (EFM). Our study suggests that in symbiosis, Chl. chlorochromatii CaD3 is under limited nitrogen conditions where the GS/GOGAT (glutamine synthetase/glutamate synthetase) pathway is actively assimilating ammonia obtained via N2 fixation. In contrast, when free-living, Chl. chlorochromatii CaD3 is in a condition of nitrogen excess and ammonia is assimilated by the alanine dehydrogenase (AlaDH) pathway. We postulate that 'Chlorochromatium aggregatum' originated from a parasitic interaction where the N2 fixation capacity of the chlorobia would be enhanced by injection of 2-oxoglutarate from the β-proteobacterium via the periplasm. This consortium would have the advantage of motility, which is fundamental to a phototrophic bacterium, and the syntrophy of nitrogen and carbon sources.
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19
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Predictions of Enzymatic Parameters: A Mini-Review with Focus on Enzymes for Biofuel. Appl Biochem Biotechnol 2013; 171:590-615. [DOI: 10.1007/s12010-013-0328-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2013] [Accepted: 06/11/2013] [Indexed: 12/25/2022]
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20
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Zanghellini J, Ruckerbauer DE, Hanscho M, Jungreuthmayer C. Elementary flux modes in a nutshell: properties, calculation and applications. Biotechnol J 2013; 8:1009-16. [PMID: 23788432 DOI: 10.1002/biot.201200269] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2012] [Revised: 02/26/2013] [Accepted: 05/08/2013] [Indexed: 02/04/2023]
Abstract
Elementary flux mode (EFM) analysis allows the unbiased decomposition of a metabolic network into minimal functional units, making it a powerful tool for metabolic engineering. While the use of EFM analysis (EFMA) is still limited by the size of the models it can handle, EFMA has been successfully applied to solve real-world metabolic engineering problems. Here we provide a user-oriented introduction to EFMA, provide examples of recent applications, analyze current research strategies to overcome the computational restrictions and give an overview over current approaches, which aim to identify and calculate only biologically relevant EFMs.
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Affiliation(s)
- Jürgen Zanghellini
- Austrian Centre of Industrial Biotechnology, Vienna, Austria; Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.
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21
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Rezola A, Pey J, de Figueiredo LF, Podhorski A, Schuster S, Rubio A, Planes FJ. Selection of human tissue-specific elementary flux modes using gene expression data. ACTA ACUST UNITED AC 2013; 29:2009-16. [PMID: 23742984 DOI: 10.1093/bioinformatics/btt328] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
MOTIVATION The analysis of high-throughput molecular data in the context of metabolic pathways is essential to uncover their underlying functional structure. Among different metabolic pathway concepts in systems biology, elementary flux modes (EFMs) hold a predominant place, as they naturally capture the complexity and plasticity of cellular metabolism and go beyond predefined metabolic maps. However, their use to interpret high-throughput data has been limited so far, mainly because their computation in genome-scale metabolic networks has been unfeasible. To face this issue, different optimization-based techniques have been recently introduced and their application to human metabolism is promising. RESULTS In this article, we exploit and generalize the K-shortest EFM algorithm to determine a subset of EFMs in a human genome-scale metabolic network. This subset of EFMs involves a wide number of reported human metabolic pathways, as well as potential novel routes, and constitutes a valuable database where high-throughput data can be mapped and contextualized from a metabolic perspective. To illustrate this, we took expression data of 10 healthy human tissues from a previous study and predicted their characteristic EFMs based on enrichment analysis. We used a multivariate hypergeometric test and showed that it leads to more biologically meaningful results than standard hypergeometric. Finally, a biological discussion on the characteristic EFMs obtained in liver is conducted, finding a high level of agreement when compared with the literature.
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Affiliation(s)
- Alberto Rezola
- Biomedical Engineering Department, CEIT and Tecnun, University of Navarra, San Sebastian, Spain
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22
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Effect of fasting on the metabolic response of liver to experimental burn injury. PLoS One 2013; 8:e54825. [PMID: 23393558 PMCID: PMC3564862 DOI: 10.1371/journal.pone.0054825] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2012] [Accepted: 12/17/2012] [Indexed: 12/31/2022] Open
Abstract
Liver metabolism is altered after systemic injuries such as burns and trauma. These changes have been elucidated in rat models of experimental burn injury where the liver was isolated and perfused ex vivo. Because these studies were performed in fasted animals to deplete glycogen stores, thus simplifying quantification of gluconeogenesis, these observations reflect the combined impact of fasting and injury on liver metabolism. Herein we asked whether the metabolic response to experimental burn injury is different in fed vs. fasted animals. Rats were subjected to a cutaneous burn covering 20% of the total body surface area, or to similar procedures without administering the burn, hence a sham-burn. Half of the animals in the burn and sham-burn groups were fasted starting on postburn day 3, and the others allowed to continue ad libitum. On postburn day 4, livers were isolated and perfused for 1 hour in physiological medium supplemented with 10% hematocrit red blood cells. The uptake/release rates of major carbon and nitrogen sources, oxygen, and carbon dioxide were measured during the perfusion and the data fed into a mass balance model to estimate intracellular fluxes. The data show that in fed animals, injury increased glucose output mainly from glycogen breakdown and minimally impacted amino acid metabolism. In fasted animals, injury did not increase glucose output but increased urea production and the uptake of several amino acids, namely glutamine, arginine, glycine, and methionine. Furthermore, sham-burn animals responded to fasting by triggering gluconeogenesis from lactate; however, in burned animals the preferred gluconeogenic substrate was amino acids. Taken together, these results suggest that the fed state prevents the burn-induced increase in hepatic amino acid utilization for gluconeogenesis. The role of glycogen stores and means to increase and/or maintain internal sources of glucose to prevent increased hepatic amino acid utilization warrant further studies.
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Cicek AE, Bederman I, Henderson L, Drumm ML, Ozsoyoglu G. ADEMA: an algorithm to determine expected metabolite level alterations using mutual information. PLoS Comput Biol 2013; 9:e1002859. [PMID: 23341761 PMCID: PMC3547803 DOI: 10.1371/journal.pcbi.1002859] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2012] [Accepted: 10/23/2012] [Indexed: 01/07/2023] Open
Abstract
Metabolomics is a relatively new “omics” platform, which analyzes a discrete set of metabolites detected in bio-fluids or tissue samples of organisms. It has been used in a diverse array of studies to detect biomarkers and to determine activity rates for pathways based on changes due to disease or drugs. Recent improvements in analytical methodology and large sample throughput allow for creation of large datasets of metabolites that reflect changes in metabolic dynamics due to disease or a perturbation in the metabolic network. However, current methods of comprehensive analyses of large metabolic datasets (metabolomics) are limited, unlike other “omics” approaches where complex techniques for analyzing coexpression/coregulation of multiple variables are applied. This paper discusses the shortcomings of current metabolomics data analysis techniques, and proposes a new multivariate technique (ADEMA) based on mutual information to identify expected metabolite level changes with respect to a specific condition. We show that ADEMA better predicts De Novo Lipogenesis pathway metabolite level changes in samples with Cystic Fibrosis (CF) than prediction based on the significance of individual metabolite level changes. We also applied ADEMA's classification scheme on three different cohorts of CF and wildtype mice. ADEMA was able to predict whether an unknown mouse has a CF or a wildtype genotype with 1.0, 0.84, and 0.9 accuracy for each respective dataset. ADEMA results had up to 31% higher accuracy as compared to other classification algorithms. In conclusion, ADEMA advances the state-of-the-art in metabolomics analysis, by providing accurate and interpretable classification results. Metabolomics is an experimental approach that analyzes differences in metabolite levels detected in experimental samples. It has been used in the literature to understand the changes in metabolism with respect to diseases or drugs. Unlike transcriptomics or proteomics, which analyze gene and protein expression levels respectively, the techniques that consider co-regulation of multiple metabolites are quite limited. In this paper, we propose a novel technique, called ADEMA, which computes the expected level changes for each metabolite with respect to a given condition. ADEMA considers multiple metabolites at the same time and is mutual information (MI)-based. We show that ADEMA predicts metabolite level changes for young mice with Cystic Fibrosis (CF) better than significance testing that considers one metabolite at a time. Using three different datasets that contain CF and wild-type (WT) mice, we show that ADEMA can classify an individual as being CF or WT based on the metabolic profiles (with 1.0, 0.84, and 0.9 accuracy, respectively). Compared to other well-known classification algorithms, ADEMA's accuracy is higher by up to 31%.
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Affiliation(s)
- A Ercument Cicek
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, USA.
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24
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Dandekar T, Fieselmann A, Majeed S, Ahmed Z. Software applications toward quantitative metabolic flux analysis and modeling. Brief Bioinform 2012; 15:91-107. [PMID: 23142828 DOI: 10.1093/bib/bbs065] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Metabolites and their pathways are central for adaptation and survival. Metabolic modeling elucidates in silico all the possible flux pathways (flux balance analysis, FBA) and predicts the actual fluxes under a given situation, further refinement of these models is possible by including experimental isotopologue data. In this review, we initially introduce the key theoretical concepts and different analysis steps in the modeling process before comparing flux calculation and metabolite analysis programs such as C13, BioOpt, COBRA toolbox, Metatool, efmtool, FiatFlux, ReMatch, VANTED, iMAT and YANA. Their respective strengths and limitations are discussed and compared to alternative software. While data analysis of metabolites, calculation of metabolic fluxes, pathways and their condition-specific changes are all possible, we highlight the considerations that need to be taken into account before deciding on a specific software. Current challenges in the field include the computation of large-scale networks (in elementary mode analysis), regulatory interactions and detailed kinetics, and these are discussed in the light of powerful new approaches.
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Affiliation(s)
- Thomas Dandekar
- Department of Bioinformatics, Biocenter, University of Wüerzburg, Am Hubland, 97074 Wuerzburg, Germany. Tel.: +49-931-318-4551; Fax: +49-931-318-4552;
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25
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Marashi SA, David L, Bockmayr A. On flux coupling analysis of metabolic subsystems. J Theor Biol 2012; 302:62-9. [DOI: 10.1016/j.jtbi.2012.02.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2011] [Revised: 01/23/2012] [Accepted: 02/21/2012] [Indexed: 01/04/2023]
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26
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Marashi SA, David L, Bockmayr A. Analysis of metabolic subnetworks by flux cone projection. Algorithms Mol Biol 2012; 7:17. [PMID: 22642830 PMCID: PMC3408373 DOI: 10.1186/1748-7188-7-17] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2011] [Accepted: 05/29/2012] [Indexed: 12/05/2022] Open
Abstract
Background Analysis of elementary modes (EMs) is proven to be a powerful constraint-based method in the study of metabolic networks. However, enumeration of EMs is a hard computational task. Additionally, due to their large number, EMs cannot be simply used as an input for subsequent analysis. One possibility is to limit the analysis to a subset of interesting reactions. However, analysing an isolated subnetwork can result in finding incorrect EMs which are not part of any steady-state flux distribution of the original network. The ideal set to describe the reaction activity in a subnetwork would be the set of all EMs projected to the reactions of interest. Recently, the concept of "elementary flux patterns" (EFPs) has been proposed. Each EFP is a subset of the support (i.e., non-zero elements) of at least one EM. Results We introduce the concept of ProCEMs (Projected Cone Elementary Modes). The ProCEM set can be computed by projecting the flux cone onto a lower-dimensional subspace and enumerating the extreme rays of the projected cone. In contrast to EFPs, ProCEMs are not merely a set of reactions, but projected EMs. We additionally prove that the set of EFPs is included in the set of ProCEM supports. Finally, ProCEMs and EFPs are compared for studying substructures of biological networks. Conclusions We introduce the concept of ProCEMs and recommend its use for the analysis of substructures of metabolic networks for which the set of EMs cannot be computed.
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Network reduction in metabolic pathway analysis: elucidation of the key pathways involved in the photoautotrophic growth of the green alga Chlamydomonas reinhardtii. Metab Eng 2012; 14:458-67. [PMID: 22342232 DOI: 10.1016/j.ymben.2012.01.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2011] [Revised: 01/13/2012] [Accepted: 01/31/2012] [Indexed: 11/21/2022]
Abstract
Metabolic pathway analysis aims at discovering and analyzing meaningful routes and their interactions in metabolic networks. A major difficulty in applying this technique lies in the decomposition of metabolic flux distributions into elementary mode or extreme pathway activity patterns, which in general is not unique. We propose a network reduction approach based on the decomposition of a set of flux vectors representing adaptive microbial metabolic behavior in bioreactors into a minimal set of shared pathways. Several optimality criteria from the literature were compared in order to select the most appropriate objective function. We further analyze photoautotrophic metabolism of the green alga Chlamydomonas reinhardtii growing in a photobioreactor under maximal growth rate conditions. Key pathways involved in its adaptive metabolic response to changes in light influx are identified and discussed using an energetic approach.
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Abstract
Metabolism can be defined as the complete set of chemical reactions that occur in living organisms in order to maintain life. Enzymes are the main players in this process as they are responsible for catalyzing the chemical reactions. The enzyme-reaction relationships can be used for the reconstruction of a network of reactions, which leads to a metabolic model of metabolism. A genome-scale metabolic network of chemical reactions that take place inside a living organism is primarily reconstructed from the information that is present in its genome and the literature and involves steps such as functional annotation of the genome, identification of the associated reactions and determination of their stoichiometry, assignment of localization, determination of the biomass composition, estimation of energy requirements, and definition of model constraints. This information can be integrated into a stoichiometric model of metabolism that can be used for detailed analysis of the metabolic potential of the organism using constraint-based modeling approaches and hence is valuable in understanding its metabolic capabilities.
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Affiliation(s)
- Gino J E Baart
- VIB Department of Plant Systems Biology/Department of Biology, Protistology and Aquatic Ecology, Ghent University, Ghent, Belgium.
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29
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Clark ST, Verwoerd WS. A systems approach to identifying correlated gene targets for the loss of colour pigmentation in plants. BMC Bioinformatics 2011; 12:343. [PMID: 21849042 PMCID: PMC3180701 DOI: 10.1186/1471-2105-12-343] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2011] [Accepted: 08/17/2011] [Indexed: 01/20/2023] Open
Abstract
Background The numerous diverse metabolic pathways by which plant compounds can be produced make it difficult to predict how colour pigmentation is lost for different tissues and plants. This study employs mathematical and in silico methods to identify correlated gene targets for the loss of colour pigmentation in plants from a whole cell perspective based on the full metabolic network of Arabidopsis. This involves extracting a self-contained flavonoid subnetwork from the AraCyc database and calculating feasible metabolic routes or elementary modes (EMs) for it. Those EMs leading to anthocyanin compounds are taken to constitute the anthocyanin biosynthetic pathway (ABP) and their interplay with the rest of the EMs is used to study the minimal cut sets (MCSs), which are different combinations of reactions to block for eliminating colour pigmentation. By relating the reactions to their corresponding genes, the MCSs are used to explore the phenotypic roles of the ABP genes, their relevance to the ABP and the impact their eliminations would have on other processes in the cell. Results Simulation and prediction results of the effect of different MCSs for eliminating colour pigmentation correspond with existing experimental observations. Two examples are: i) two MCSs which require the simultaneous suppression of genes DFR and ANS to eliminate colour pigmentation, correspond to observational results of the same genes being co-regulated for eliminating floral pigmentation in Aquilegia and; ii) the impact of another MCS requiring CHS suppression, corresponds to findings where the suppression of the early gene CHS eliminated nearly all flavonoids but did not affect the production of volatile benzenoids responsible for floral scent. Conclusions From the various MCSs identified for eliminating colour pigmentation, several correlate to existing experimental observations, indicating that different MCSs are suitable for different plants, different cells, and different conditions and could also be related to regulatory genes. Being able to correlate the predictions with experimental results gives credence to the use of these mathematical and in silico analyses methods in the design of experiments. The methods could be used to prioritize target enzymes for different objectives to achieve desired outcomes, especially for less understood pathways.
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Affiliation(s)
- Sangaalofa T Clark
- Centre for Advanced Computational Solutions (CfACS), Agriculture and Life Sciences Division Lincoln University, Canterbury, New Zealand.
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Orman MA, Ierapetritou MG, Androulakis IP, Berthiaume F. Metabolic response of perfused livers to various oxygenation conditions. Biotechnol Bioeng 2011; 108:2947-57. [PMID: 21755498 DOI: 10.1002/bit.23261] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2011] [Revised: 06/21/2011] [Accepted: 06/24/2011] [Indexed: 01/06/2023]
Abstract
Isolated liver perfusion systems have been used to characterize intrinsic metabolic changes in liver as a result of various perturbations, including systemic injury, hepatotoxin exposure, and warm ischemia. Most of these studies were done using hyperoxic conditions (95% O(2)) but without the use of oxygen carriers in the perfusate. Prior literature data do not clearly establish the impact of oxygenation, and in particular that of adding oxygen carriers to the perfusate, on the metabolic functions of the liver. Therefore, herein the effects of oxygen delivery in the perfusion system on liver metabolism were investigated by comparing three modes of oxygenation. Rat livers were perfused via the portal and hepatic veins at a constant flow rate of 3 mL/min/g liver in a recirculating perfusion system. In the first group, the perfusate was equilibrated in a membrane oxygenator with room air (21% O(2)) before entering the liver. In the second group, the perfusate was equilibrated with a 95% O(2)/5% CO(2) gas mixture. In the third group, the perfusate was supplemented with washed bovine red blood cells (RBCs) at 10% hematocrit and also equilibrated with the 95% O(2)/5% CO(2) gas mixture. Oxygen and CO(2) gradients across the liver were measured periodically with a blood gas analyzer. The rate of change in the concentration of major metabolites in the perfusate was measured over time. Net extracellular fluxes were calculated from these measurements and applied to a stoichiometric-based optimization problem to determine the intracellular fluxes and active pathways in the perfused livers. Livers perfused with RBCs consumed oxygen at twice the rate observed using hyperoxic (95% O(2)) perfusate without RBCs, and also produced more urea and ketone bodies. At the flow rate used, the oxygen supply in perfusate without RBCs was just sufficient to meet the average oxygen demand of the liver but would be insufficient if it increased above baseline, as is often the case in response to environmental perturbations. Metabolic pathway analysis suggests that significant anaerobic glycolysis occurred in the absence of RBCs even using hyperoxic perfusate. Conversely, when RBCs were used, glucose production from lactate and glutamate, as well as pathways related to energy metabolism were upregulated. RBCs also reversed an increase in PPP fluxes induced by the use of hyperoxic perfusate alone. In conclusion, the use of oxygen carriers is required to investigate the effect of various perturbations on liver metabolism.
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Affiliation(s)
- Mehmet A Orman
- Department of Chemical and Biochemical Engineering, Rutgers, State University of New Jersey, Piscataway, New Jersey 08854, USA
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31
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Beuster G, Zarse K, Kaleta C, Thierbach R, Kiehntopf M, Steinberg P, Schuster S, Ristow M. Inhibition of alanine aminotransferase in silico and in vivo promotes mitochondrial metabolism to impair malignant growth. J Biol Chem 2011; 286:22323-30. [PMID: 21540181 PMCID: PMC3121379 DOI: 10.1074/jbc.m110.205229] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Cancer cells commonly exhibit increased nonoxidative d-glucose metabolism whereas induction of mitochondrial metabolism may impair malignant growth. We have first used an in silico method called elementary mode analysis to identify inhibition of ALAT (l-alanine aminotransferase) as a putative target to promote mitochondrial metabolism. We then experimentally show that two competitive inhibitors of ALAT, l-cycloserine and β-chloro-l-alanine, inhibit l-alanine production and impair d-glucose uptake of LLC1 Lewis lung carcinoma cells. The latter inhibition is linked to an initial energy deficit, as quantified by decreased ATP content, which is then followed by an activation of AMP-activated protein kinase and subsequently increased respiration rates and mitochondrial production of reactive oxygen species, culminating in ATP replenishment in ALAT-inhibited LLC1 cells. Moreover, we observe altered phosphorylation of p38 MAPK (mitogen-activated protein kinase 14), ERK (extracellular signal-regulated kinase 1/2), and Rb1 (retinoblastoma 1) proteins, as well as decreased expression of Cdc25a (cell decision cycle 25 homolog A) and Cdk4 (cyclin-dependent kinase 4). Importantly, these sequelae of ALAT inhibition culminate in similarly reduced anchorage-dependent and anchorage-independent growth rates of LLC1 cells, together suggesting that inhibition of ALAT efficiently impairs cancer growth by counteracting the Warburg effect due to compensatory activation of mitochondrial metabolism.
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Affiliation(s)
- Gregor Beuster
- Department of Human Nutrition, Institute of Nutrition, University of Jena, Jena D-07743, Germany
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Förster F, Beisser D, Frohme M, Schill RO, Dandekar T. Bioinformatics identifies tardigrade molecular adaptations including the DNA‐j family and first steps towards dynamical modelling. J ZOOL SYST EVOL RES 2011. [DOI: 10.1111/j.1439-0469.2010.00609.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Frank Förster
- Department of Bioinformatics, Biocenter University of Würzburg, Würzburg, Germany
| | - Daniela Beisser
- Department of Bioinformatics, Biocenter University of Würzburg, Würzburg, Germany
| | | | - Ralph O. Schill
- Department of Zoology, Institute for Biology, Universität Stuttgart, Stuttgart, Germany
| | - Thomas Dandekar
- Department of Bioinformatics, Biocenter University of Würzburg, Würzburg, Germany
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Cecil A, Rikanović C, Ohlsen K, Liang C, Bernhardt J, Oelschlaeger TA, Gulder T, Bringmann G, Holzgrabe U, Unger M, Dandekar T. Modeling antibiotic and cytotoxic effects of the dimeric isoquinoline IQ-143 on metabolism and its regulation in Staphylococcus aureus, Staphylococcus epidermidis and human cells. Genome Biol 2011; 12:R24. [PMID: 21418624 PMCID: PMC3129674 DOI: 10.1186/gb-2011-12-3-r24] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2010] [Revised: 03/14/2011] [Accepted: 03/21/2011] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Xenobiotics represent an environmental stress and as such are a source for antibiotics, including the isoquinoline (IQ) compound IQ-143. Here, we demonstrate the utility of complementary analysis of both host and pathogen datasets in assessing bacterial adaptation to IQ-143, a synthetic analog of the novel type N,C-coupled naphthyl-isoquinoline alkaloid ancisheynine. RESULTS Metabolite measurements, gene expression data and functional assays were combined with metabolic modeling to assess the effects of IQ-143 on Staphylococcus aureus, Staphylococcus epidermidis and human cell lines, as a potential paradigm for novel antibiotics. Genome annotation and PCR validation identified novel enzymes in the primary metabolism of staphylococci. Gene expression response analysis and metabolic modeling demonstrated the adaptation of enzymes to IQ-143, including those not affected by significant gene expression changes. At lower concentrations, IQ-143 was bacteriostatic, and at higher concentrations bactericidal, while the analysis suggested that the mode of action was a direct interference in nucleotide and energy metabolism. Experiments in human cell lines supported the conclusions from pathway modeling and found that IQ-143 had low cytotoxicity. CONCLUSIONS The data suggest that IQ-143 is a promising lead compound for antibiotic therapy against staphylococci. The combination of gene expression and metabolite analyses with in silico modeling of metabolite pathways allowed us to study metabolic adaptations in detail and can be used for the evaluation of metabolic effects of other xenobiotics.
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Affiliation(s)
- Alexander Cecil
- University of Würzburg, Theodor-Boveri Institute, Department of Bioinformatics, Am Hubland, 97074 Würzburg, Germany
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Verwoerd WS. A new computational method to split large biochemical networks into coherent subnets. BMC SYSTEMS BIOLOGY 2011; 5:25. [PMID: 21294924 PMCID: PMC3045323 DOI: 10.1186/1752-0509-5-25] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2010] [Accepted: 02/07/2011] [Indexed: 11/17/2022]
Abstract
Background Compared to more general networks, biochemical networks have some special features: while generally sparse, there are a small number of highly connected metabolite nodes; and metabolite nodes can also be divided into two classes: internal nodes with associated mass balance constraints and external ones without. Based on these features, reclassifying selected internal nodes (separators) to external ones can be used to divide a large complex metabolic network into simpler subnetworks. Selection of separators based on node connectivity is commonly used but affords little detailed control and tends to produce excessive fragmentation. The method proposed here (Netsplitter) allows the user to control separator selection. It combines local connection degree partitioning with global connectivity derived from random walks on the network, to produce a more even distribution of subnetwork sizes. Partitioning is performed progressively and the interactive visual matrix presentation used allows the user considerable control over the process, while incorporating special strategies to maintain the network integrity and minimise the information loss due to partitioning. Results Partitioning of a genome scale network of 1348 metabolites and 1468 reactions for Arabidopsis thaliana encapsulates 66% of the network into 10 medium sized subnets. Applied to the flavonoid subnetwork extracted in this way, it is shown that Netsplitter separates this naturally into four subnets with recognisable functionality, namely synthesis of lignin precursors, flavonoids, coumarin and benzenoids. A quantitative quality measure called efficacy is constructed and shows that the new method gives improved partitioning for several metabolic networks, including bacterial, plant and mammal species. Conclusions For the examples studied the Netsplitter method is a considerable improvement on the performance of connection degree partitioning, giving a better balance of subnet sizes with the removal of fewer mass balance constraints. In addition, the user can interactively control which metabolite nodes are selected for cutting and when to stop further partitioning as the desired granularity has been reached. Finally, the blocking transformation at the heart of the procedure provides a powerful visual display of network structure that may be useful for its exploration independent of whether partitioning is required.
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Affiliation(s)
- Wynand S Verwoerd
- Centre for Advanced Computational Solutions, Dept WF & Molecular Bioscience, Lincoln University, Ellesmere Junction Road, Christchurch, New Zealand.
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Orman MA, Berthiaume F, Androulakis IP, Ierapetritou MG. Pathway analysis of liver metabolism under stressed condition. J Theor Biol 2010; 272:131-40. [PMID: 21163266 DOI: 10.1016/j.jtbi.2010.11.042] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2010] [Revised: 11/17/2010] [Accepted: 11/24/2010] [Indexed: 11/28/2022]
Abstract
Pathway analysis is a useful tool which reveals important metabolic network properties. However, the big challenge is to propose an objective function for estimating active pathways, which represent the actual state of network. In order to provide weight values for all possible pathways within the metabolic network, this study presents different approaches, considering the structural and physiological properties of the metabolic network, aiming at a unique decomposition of the flux vector into pathways. These methods were used to analyze the hepatic metabolism considering available data sets obtained from the perfused livers of fasted rats receiving burn injury. Utilizing unique decomposition techniques and different fluxes revealed that higher weights were always attributed to short pathways. Specific pathways, including pyruvate, glutamate and oxaloacetate pools, and urea production from arginine, were found to be important or essential in all methods and experimental conditions. Moreover the pathways, including serine production from glycine and conversion between acetoacetate and B-OH-butyrate, were assigned higher weights. Pathway analysis was also used to identify the main sources for the production of certain products in the hepatic metabolic network to gain a better understanding of the effects of burn injury on liver metabolism.
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Affiliation(s)
- Mehmet A Orman
- Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
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Schauer K, Geginat G, Liang C, Goebel W, Dandekar T, Fuchs TM. Deciphering the intracellular metabolism of Listeria monocytogenes by mutant screening and modelling. BMC Genomics 2010; 11:573. [PMID: 20955543 PMCID: PMC3091722 DOI: 10.1186/1471-2164-11-573] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2010] [Accepted: 10/18/2010] [Indexed: 11/29/2022] Open
Abstract
Background The human pathogen Listeria monocytogenes resides and proliferates within the cytoplasm of epithelial cells. While the virulence factors essentially contributing to this step of the infection cycle are well characterized, the set of listerial genes contributing to intracellular replication remains to be defined on a genome-wide level. Results A comprehensive library of L. monocytogenes strain EGD knockout mutants was constructed upon insertion-duplication mutagenesis, and 1491 mutants were tested for their phenotypes in rich medium and in a Caco-2 cell culture assay. Following sequencing of the plasmid insertion site, 141 different genes required for invasion of and replication in Caco-2 cells were identified. Ten in-frame deletion mutants were constructed that confirmed the data. The genes with known functions are mainly involved in cellular processes including transport, in the intermediary metabolism of sugars, nucleotides and lipids, and in information pathways such as regulatory functions. No function could be ascribed to 18 genes, and a counterpart of eight genes is missing in the apathogenic species L. innocua. Mice infection studies revealed the in vivo requirement of IspE (Lmo0190) involved in mevalonate synthesis, and of the novel ABC transporter Lmo0135-0137 associated with cysteine transport. Based on the data of this genome-scale screening, an extreme pathway and elementary mode analysis was applied that demonstrates the critical role of glycerol and purine metabolism, of fucose utilization, and of the synthesis of glutathione, aspartate semialdehyde, serine and branched chain amino acids during intracellular replication of L. monocytogenes. Conclusion The combination of a genetic screening and a modelling approach revealed that a series of transporters help L. monocytogenes to overcome a putative lack of nutrients within cells, and that a high metabolic flexibility contributes to the intracellular replication of this pathogen.
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Affiliation(s)
- Kristina Schauer
- Zentralinstitut für Ernährungs- und Lebensmittelforschung (ZIEL), Abteilung Mikrobiologie, Technische Universität München, Weihenstephaner Berg 3, Freising, Germany
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Drug target identification in sphingolipid metabolism by computational systems biology tools: Metabolic control analysis and metabolic pathway analysis. J Biomed Inform 2010; 43:537-49. [DOI: 10.1016/j.jbi.2010.03.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2009] [Revised: 11/24/2009] [Accepted: 03/22/2010] [Indexed: 11/21/2022]
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Cakmak A, Ozsoyoglu G, Hanson RW. Querying metabolism under different physiological constraints. J Bioinform Comput Biol 2010; 8:247-93. [PMID: 20401946 DOI: 10.1142/s0219720010004604] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2009] [Revised: 11/02/2009] [Accepted: 11/02/2009] [Indexed: 11/18/2022]
Abstract
Metabolism is a representation of the biochemical principles that govern the production, consumption, degradation, and biosynthesis of metabolites in living cells. Organisms respond to changes in their physiological conditions or environmental perturbations (i.e. constraints) via cooperative implementation of such principles. Querying inner working principles of metabolism under different constraints provides invaluable insights for both researchers and educators. In this paper, we propose a metabolism query language (MQL) and discuss its query processing. MQL enables researchers to explore the behavior of the metabolism with a wide-range of predicates including dietary and physiological condition specifications. The query results of MQL are enriched with both textual and visual representations, and its query processing is completely tailored based on the underlying metabolic principles.
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Affiliation(s)
- Ali Cakmak
- Department of Electrical Engineering & Computer Science, Case Western Reserve University, USA.
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39
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Which metabolic pathways generate and characterize the flux space? A comparison among elementary modes, extreme pathways and minimal generators. J Biomed Biotechnol 2010; 2010:753904. [PMID: 20467567 PMCID: PMC2868190 DOI: 10.1155/2010/753904] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2009] [Revised: 12/29/2009] [Accepted: 02/11/2010] [Indexed: 01/05/2023] Open
Abstract
Important efforts are being done to systematically identify the relevant pathways in a metabolic network. Unsurprisingly, there is not a unique set of network-based pathways to be tagged as relevant, and at least four related concepts have been proposed: extreme currents, elementary modes, extreme pathways, and minimal generators. Basically, there are two properties that these sets of pathways can hold: they can generate the flux space--if every feasible flux distribution can be represented as a nonnegative combination of flux through them--or they can comprise all the nondecomposable pathways in the network. The four concepts fulfill the first property, but only the elementary modes fulfill the second one. This subtle difference has been a source of errors and misunderstandings. This paper attempts to clarify the intricate relationship between the network-based pathways performing a comparison among them.
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40
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Pitkänen E, Jouhten P, Rousu J. Inferring branching pathways in genome-scale metabolic networks. BMC SYSTEMS BIOLOGY 2009; 3:103. [PMID: 19874610 PMCID: PMC2791103 DOI: 10.1186/1752-0509-3-103] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2009] [Accepted: 10/29/2009] [Indexed: 11/17/2022]
Abstract
Background A central problem in computational metabolic modelling is how to find biochemically plausible pathways between metabolites in a metabolic network. Two general, complementary frameworks have been utilized to find metabolic pathways: constraint-based modelling and graph-theoretical path finding approaches. In constraint-based modelling, one aims to find pathways where metabolites are balanced in a pseudo steady-state. Constraint-based methods, such as elementary flux mode analysis, have typically a high computational cost stemming from a large number of steady-state pathways in a typical metabolic network. On the other hand, graph-theoretical approaches avoid the computational complexity of constraint-based methods by solving a simpler problem of finding shortest paths. However, while scaling well with network size, graph-theoretic methods generally tend to return more false positive pathways than constraint-based methods. Results In this paper, we introduce a computational method, ReTrace, for finding biochemically relevant, branching metabolic pathways in an atom-level representation of metabolic networks. The method finds compact pathways which transfer a high fraction of atoms from source to target metabolites by considering combinations of linear shortest paths. In contrast to current steady-state pathway analysis methods, our method scales up well and is able to operate on genome-scale models. Further, we show that the pathways produced are biochemically meaningful by an example involving the biosynthesis of inosine 5'-monophosphate (IMP). In particular, the method is able to avoid typical problems associated with graph-theoretic approaches such as the need to define side metabolites or pathways not carrying any net carbon flux appearing in results. Finally, we discuss an application involving reconstruction of amino acid pathways of a recently sequenced organism demonstrating how measurement data can be easily incorporated into ReTrace analysis. ReTrace is licensed under GPL and is freely available for academic use at http://www.cs.helsinki.fi/group/sysfys/software/retrace/. Conclusion ReTrace is a useful method in metabolic path finding tasks, combining some of the best aspects in constraint-based and graph-theoretic methods. It finds use in a multitude of tasks ranging from metabolic engineering to metabolic reconstruction of recently sequenced organisms.
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Affiliation(s)
- Esa Pitkänen
- Department of Computer Science, University of Helsinki, Finland.
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41
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Figueiredo LFD, Schuster S, Kaleta C, Fell DA. Response to comment on 'Can sugars be produced from fatty acids? A test case for pathway analysis tools'. Bioinformatics 2009; 25:3330-1. [DOI: 10.1093/bioinformatics/btp591] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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42
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Krüger B, Dandekar T. Bioinformatical Approaches to Detect and Analyze Protein Interactions. Proteomics 2009; 564:401-31. [DOI: 10.1007/978-1-60761-157-8_23] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
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43
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Sass MB, Lorenz AN, Green RL, Coleman RA. A pragmatic approach to biochemical systems theory applied to an α-synuclein-based model of Parkinson's disease. J Neurosci Methods 2009; 178:366-77. [DOI: 10.1016/j.jneumeth.2008.12.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2008] [Revised: 11/24/2008] [Accepted: 12/11/2008] [Indexed: 10/21/2022]
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Trinh CT, Wlaschin A, Srienc F. Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism. Appl Microbiol Biotechnol 2008; 81:813-26. [PMID: 19015845 DOI: 10.1007/s00253-008-1770-1] [Citation(s) in RCA: 181] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2008] [Revised: 10/23/2008] [Accepted: 10/25/2008] [Indexed: 12/19/2022]
Abstract
Elementary mode analysis is a useful metabolic pathway analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering.
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Affiliation(s)
- Cong T Trinh
- Department of Chemical Engineering and Materials Science, University of Minnesota, 151 Amundson Hall, 421 Washington Ave SE, Minneapolis, MN 55455, USA
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45
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Steuer R, Junker BH. Computational Models of Metabolism: Stability and Regulation in Metabolic Networks. ADVANCES IN CHEMICAL PHYSICS 2008. [DOI: 10.1002/9780470475935.ch3] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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Wright J, Wagner A. The Systems Biology Research Tool: evolvable open-source software. BMC SYSTEMS BIOLOGY 2008; 2:55. [PMID: 18588708 PMCID: PMC2446383 DOI: 10.1186/1752-0509-2-55] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2008] [Accepted: 06/29/2008] [Indexed: 12/03/2022]
Abstract
Background Research in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput) experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level. Results We introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT) to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology. Conclusion The Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability), to facilitate cooperation among researchers, and to expedite progress in the field of systems biology.
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Affiliation(s)
- Jeremiah Wright
- Department of Biochemistry, University of Zurich, Zurich, Switzerland.
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47
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Planes FJ, Beasley JE. A critical examination of stoichiometric and path-finding approaches to metabolic pathways. Brief Bioinform 2008; 9:422-36. [DOI: 10.1093/bib/bbn018] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Llaneras F, Picó J. Stoichiometric modelling of cell metabolism. J Biosci Bioeng 2008; 105:1-11. [DOI: 10.1263/jbb.105.1] [Citation(s) in RCA: 95] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2007] [Accepted: 10/25/2007] [Indexed: 10/22/2022]
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Schwarz R, Liang C, Kaleta C, Kühnel M, Hoffmann E, Kuznetsov S, Hecker M, Griffiths G, Schuster S, Dandekar T. Integrated network reconstruction, visualization and analysis using YANAsquare. BMC Bioinformatics 2007; 8:313. [PMID: 17725829 PMCID: PMC2020486 DOI: 10.1186/1471-2105-8-313] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2007] [Accepted: 08/28/2007] [Indexed: 01/29/2023] Open
Abstract
Background Modeling of metabolic networks includes tasks such as network assembly, network overview, calculation of metabolic fluxes and testing the robustness of the network. Results YANAsquare provides a software framework for rapid network assembly (flexible pathway browser with local or remote operation mode), network overview (visualization routine and YANAsquare editor) and network performance analysis (calculation of flux modes as well as target and robustness tests). YANAsquare comes as an easy-to-setup program package in Java. It is fully compatible and integrates the programs YANA (translation of gene expression values into flux distributions, metabolite network dissection) and Metatool (elementary mode calculation). As application examples we set-up and model the phospholipid network in the phagosome and genome-scale metabolic maps of S.aureus, S.epidermidis and S.saprophyticus as well as test their robustness against enzyme impairment. Conclusion YANAsquare is an application software for rapid setup, visualization and analysis of small, larger and genome-scale metabolic networks.
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Affiliation(s)
- Roland Schwarz
- Department of Bioinformatics, Biocenter Am Hubland, D-97074 University of Würzburg, Germany
| | - Chunguang Liang
- Department of Bioinformatics, Biocenter Am Hubland, D-97074 University of Würzburg, Germany
| | - Christoph Kaleta
- Bio Systems Analysis Group, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Germany
| | - Mark Kühnel
- Cell Biology Program, EMBL Heidelberg, Germany
| | - Eik Hoffmann
- Department of Cell Biology and Biosystems Technology, Albert-Einstein-Str. 3, D-18059 University of Rostock, Germany
| | - Sergei Kuznetsov
- Department of Cell Biology and Biosystems Technology, Albert-Einstein-Str. 3, D-18059 University of Rostock, Germany
| | - Michael Hecker
- Institute for Microbiology, Friedrich-Ludwig-Jahn-Str. 15, D-17487 University of Greifswald, Germany
| | | | - Stefan Schuster
- Department of Bioinformatics, Ernst-Abbe-Platz 2, D-07743 University of Jena, Germany
| | - Thomas Dandekar
- Department of Bioinformatics, Biocenter Am Hubland, D-97074 University of Würzburg, Germany
- Structural and Computational Biology, EMBL Heidelberg, Germany
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Rios-Estepa R, Lange BM. Experimental and mathematical approaches to modeling plant metabolic networks. PHYTOCHEMISTRY 2007; 68:2351-74. [PMID: 17561179 DOI: 10.1016/j.phytochem.2007.04.021] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2007] [Revised: 04/16/2007] [Accepted: 04/17/2007] [Indexed: 05/15/2023]
Abstract
To support their sessile and autotrophic lifestyle higher plants have evolved elaborate networks of metabolic pathways. Dynamic changes in these metabolic networks are among the developmental forces underlying the functional differentiation of organs, tissues and specialized cell types. They are also important in the various interactions of a plant with its environment. Further complexity is added by the extensive compartmentation of the various interconnected metabolic pathways in plants. Thus, although being used widely for assessing the control of metabolic flux in microbes, mathematical modeling approaches that require steady-state approximations are of limited utility for understanding complex plant metabolic networks. However, considerable progress has been made when manageable metabolic subsystems were studied. In this article, we will explain in general terms and using simple examples the concepts underlying stoichiometric modeling (metabolic flux analysis and metabolic pathway analysis) and kinetic approaches to modeling (including metabolic control analysis as a special case). Selected studies demonstrating the prospects of these approaches, or combinations of them, for understanding the control of flux through particular plant pathways are discussed. We argue that iterative cycles of (dry) mathematical modeling and (wet) laboratory testing will become increasingly important for simulating the distribution of flux in plant metabolic networks and deriving rational experimental designs for metabolic engineering efforts.
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Affiliation(s)
- Rigoberto Rios-Estepa
- Institute of Biological Chemistry, M.J. Murdock Metabolomics Laboratory, Center for Integrated Biotechnology, Washington State University, PO Box 646340, Pullman, WA 99164-6340, USA
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