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Williamson G, Bizior A, Harris T, Pritchard L, Hoskisson P, Javelle A. Biological ammonium transporters from the Amt/Mep/Rh superfamily: mechanism, energetics, and technical limitations. Biosci Rep 2024; 44:BSR20211209. [PMID: 38131184 PMCID: PMC10794816 DOI: 10.1042/bsr20211209] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/12/2023] [Accepted: 12/21/2023] [Indexed: 12/23/2023] Open
Abstract
The exchange of ammonium across cellular membranes is a fundamental process in all domains of life and is facilitated by the ubiquitous Amt/Mep/Rh transporter superfamily. Remarkably, despite a high structural conservation in all domains of life, these proteins have gained various biological functions during evolution. It is tempting to hypothesise that the physiological functions gained by these proteins may be explained at least in part by differences in the energetics of their translocation mechanisms. Therefore, in this review, we will explore our current knowledge of energetics of the Amt/Mep/Rh family, discuss variations in observations between different organisms, and highlight some technical drawbacks which have hampered effects at mechanistic characterisation. Through the review, we aim to provide a comprehensive overview of current understanding of the mechanism of transport of this unique and extraordinary Amt/Mep/Rh superfamily of ammonium transporters.
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Affiliation(s)
- Gordon Williamson
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, U.K
| | - Adriana Bizior
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, U.K
| | - Thomas Harris
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, U.K
| | - Leighton Pritchard
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, U.K
| | - Paul A. Hoskisson
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, U.K
| | - Arnaud Javelle
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, U.K
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2
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Westerhoff HV. On paradoxes between optimal growth, metabolic control analysis, and flux balance analysis. Biosystems 2023; 233:104998. [PMID: 37591451 DOI: 10.1016/j.biosystems.2023.104998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 08/04/2023] [Accepted: 08/08/2023] [Indexed: 08/19/2023]
Abstract
In Microbiology it is often assumed that growth rate is maximal. This may be taken to suggest that the dependence of the growth rate on every enzyme activity is at the top of an inverse-parabolic function, i.e. that all flux control coefficients should equal zero. This might seem to imply that the sum of these flux control coefficients equals zero. According to the summation law of Metabolic Control Analysis (MCA) the sum of flux control coefficients should equal 1 however. And in Flux Balance Analysis (FBA) catabolism is often limited by a hard bound, causing catabolism to fully control the fluxes, again in apparent contrast with a flux control coefficient of zero. Here we resolve these paradoxes (apparent contradictions) in an analysis that uses the 'Edinburgh pathway', the 'Amsterdam pathway', as well as a generic metabolic network providing the building blocks or Gibbs energy for microbial growth. We review and show that (i) optimization depends on so-called enzyme control coefficients rather than the 'catalytic control coefficients' of MCA's summation law, (ii) when optimization occurs at fixed total protein, the former differ from the latter to the extent that they may all become equal to zero in the optimum state, (iii) in more realistic scenarios of optimization where catalytically inert biomass is compensating or maintenance metabolism is taken into consideration, the optimum enzyme concentrations should not be expected to equal those that maximize the specific growth rate, (iv) optimization may be in terms of yield rather than specific growth rate, which resolves the paradox because the sum of catalytic control coefficients on yield equals 0, (v) FBA effectively maximizes growth yield, and for yield the summation law states 0 rather than 1, thereby removing the paradox, (vi) furthermore, FBA then comes more often to a 'hard optimum' defined by a maximum catabolic flux and a catabolic-enzyme control coefficient of 1. The trade-off between maintenance metabolism and growth is highlighted as worthy of further analysis.
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Affiliation(s)
- Hans V Westerhoff
- Department of Molecular Cell Biology, Vrije Universiteit Amsterdam, A-Life, De Boelelaan 1085, 1081 HV, Amsterdam, the Netherlands; Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 XH, Amsterdam, the Netherlands; School of Biological Sciences, Medicine and Health, University of Manchester, Manchester, United Kingdom; Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, 7600, South Africa.
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3
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Liu Y, Westerhoff HV. 'Social' versus 'asocial' cells-dynamic competition flux balance analysis. NPJ Syst Biol Appl 2023; 9:53. [PMID: 37898597 PMCID: PMC10613221 DOI: 10.1038/s41540-023-00313-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 10/09/2023] [Indexed: 10/30/2023] Open
Abstract
In multicellular organisms cells compete for resources or growth factors. If any one cell type wins, the co-existence of diverse cell types disappears. Existing dynamic Flux Balance Analysis (dFBA) does not accommodate changes in cell density caused by competition. Therefore we here develop 'dynamic competition Flux Balance Analysis' (dcFBA). With total biomass synthesis as objective, lower-growth-yield cells were outcompeted even when cells synthesized mutually required nutrients. Signal transduction between cells established co-existence, which suggests that such 'socialness' is required for multicellularity. Whilst mutants with increased specific growth rate did not outgrow the other cell types, loss of social characteristics did enable a mutant to outgrow the other cells. We discuss that 'asocialness' rather than enhanced growth rates, i.e., a reduced sensitivity to regulatory factors rather than enhanced growth rates, may characterize cancer cells and organisms causing ecological blooms. Therapies reinforcing cross-regulation may therefore be more effective than those targeting replication rates.
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Affiliation(s)
- Yanhua Liu
- Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Hans V Westerhoff
- Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.
- Molecular Cell Biology, A-Life, Faculty of Science, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
- Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, 7600, South Africa.
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4
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Bao YQ, Zhang MT, Feng BY, Jieensi W, Xu Y, Xu LR, Han YY, Chen YP. Construction, Characterization, and Application of an Ammonium Transporter (AmtB) Deletion Mutant of the Nitrogen-Fixing Bacterium Kosakonia radicincitans GXGL-4A in Cucumis sativus L. Seedlings. Curr Microbiol 2023; 80:58. [PMID: 36588112 DOI: 10.1007/s00284-022-03160-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 12/19/2022] [Indexed: 01/03/2023]
Abstract
Nitrogen is an important factor affecting crop yield, but excessive use of chemical nitrogen fertilizer has caused decline in nitrogen utilization and soil and water pollution. Reducing the utilization of chemical nitrogen fertilizers by biological nitrogen fixation (BNF) is feasible for green production of crops. However, there are few reports on how to have more ammonium produced by nitrogen-fixing bacteria (NFB) flow outside the cell. In the present study, the amtB gene encoding an ammonium transporter (AmtB) in the genome of NFB strain Kosakonia radicincitans GXGL-4A was deleted and the △amtB mutant was characterized. The results showed that deletion of the amtB gene had no influence on the growth of bacterial cells. The extracellular ammonium nitrogen (NH4+) content of the △amtB mutant under nitrogen-free culture conditions was significantly higher than that of the wild-type strain GXGL-4A (WT-GXGL-4A), suggesting disruption of NH4+ transport. Meanwhile, the plant growth-promoting effect in cucumber seedlings was visualized after fertilization using cells of the △amtB mutant. NFB fertilization continuously increased the cucumber rhizosphere soil pH. The nitrate nitrogen (NO3-) content in soil in the △amtB treatment group was significantly higher than that in the WT-GXGL-4A treatment group in the short term but there was no difference in soil NH4+ contents between groups. Soil enzymatic activities varied during a 45-day assessment period, indicating that △amtB fertilization influenced soil nitrogen cycling in the cucumber rhizosphere. The results will provide a solid foundation for developing the NFB GXGL-4A into an efficient biofertilizer agent.
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Affiliation(s)
- Yu-Qing Bao
- Department of Resources and Environment, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Meng-Ting Zhang
- Department of Resources and Environment, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Bao-Yun Feng
- Department of Resources and Environment, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Wulale Jieensi
- Department of Resources and Environment, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Yu Xu
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, 321004, China
| | - Lu-Rong Xu
- Department of Resources and Environment, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Ying-Ying Han
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Yun-Peng Chen
- Department of Resources and Environment, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
- Ministry of Science and Technology, Shanghai Yangtze River Delta Eco-Environmental Change and Research Station, Shanghai, 200240, China.
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5
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Goldberg RN, Giessmann RT, Halling PJ, Kettner C, Westerhoff HV. Recommendations for performing measurements of apparent equilibrium constants of enzyme-catalyzed reactions and for reporting the results of these measurements. Beilstein J Org Chem 2023; 19:303-316. [PMID: 36960304 PMCID: PMC10028569 DOI: 10.3762/bjoc.19.26] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 02/15/2023] [Indexed: 03/17/2023] Open
Abstract
The measurement of values of apparent equilibrium constants K' for enzyme-catalyzed reactions involve a substantial number of critical details, neglect of which could lead to systematic errors. Here, interferences, impurities in the substances used, and failure to achieve equilibrium are matters of substantial consequence. Careful reporting of results is of great importance if the results are to have archival value. Thus, attention must be paid to the identification of the substances, specification of the reaction(s), the conditions of reaction, the definition of the equilibrium constant(s) and standard states, the use of standard nomenclature, symbols, and units, and uncertainties. This document contains a general discussion of various aspects of these equilibrium measurements as well as STRENDA (Standards for Reporting Enzymology Data) recommendations regarding the measurements and the reporting of results.
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Affiliation(s)
- Robert N Goldberg
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, Maryland, 20899, USA
| | - Robert T Giessmann
- Institute for Globally Distributed Open Research and Education (IGDORE), Berlin, Germany
| | | | - Carsten Kettner
- Beilstein-Institut, Trakehner Straße 7–9, 60487 Frankfurt am Main, Germany
| | - Hans V Westerhoff
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Molecular Cell Biology, Faculty of Science, Free University Amsterdam, The Netherlands
- School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, UK
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6
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Maeda K, Hatae A, Sakai Y, Boogerd FC, Kurata H. MLAGO: machine learning-aided global optimization for Michaelis constant estimation of kinetic modeling. BMC Bioinformatics 2022; 23:455. [PMID: 36319952 PMCID: PMC9624028 DOI: 10.1186/s12859-022-05009-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 10/26/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Kinetic modeling is a powerful tool for understanding the dynamic behavior of biochemical systems. For kinetic modeling, determination of a number of kinetic parameters, such as the Michaelis constant (Km), is necessary, and global optimization algorithms have long been used for parameter estimation. However, the conventional global optimization approach has three problems: (i) It is computationally demanding. (ii) It often yields unrealistic parameter values because it simply seeks a better model fitting to experimentally observed behaviors. (iii) It has difficulty in identifying a unique solution because multiple parameter sets can allow a kinetic model to fit experimental data equally well (the non-identifiability problem). RESULTS To solve these problems, we propose the Machine Learning-Aided Global Optimization (MLAGO) method for Km estimation of kinetic modeling. First, we use a machine learning-based Km predictor based only on three factors: EC number, KEGG Compound ID, and Organism ID, then conduct a constrained global optimization-based parameter estimation by using the machine learning-predicted Km values as the reference values. The machine learning model achieved relatively good prediction scores: RMSE = 0.795 and R2 = 0.536, making the subsequent global optimization easy and practical. The MLAGO approach reduced the error between simulation and experimental data while keeping Km values close to the machine learning-predicted values. As a result, the MLAGO approach successfully estimated Km values with less computational cost than the conventional method. Moreover, the MLAGO approach uniquely estimated Km values, which were close to the measured values. CONCLUSIONS MLAGO overcomes the major problems in parameter estimation, accelerates kinetic modeling, and thus ultimately leads to better understanding of complex cellular systems. The web application for our machine learning-based Km predictor is accessible at https://sites.google.com/view/kazuhiro-maeda/software-tools-web-apps , which helps modelers perform MLAGO on their own parameter estimation tasks.
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Affiliation(s)
- Kazuhiro Maeda
- grid.258806.10000 0001 2110 1386Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502 Japan
| | - Aoi Hatae
- grid.258806.10000 0001 2110 1386Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502 Japan
| | - Yukie Sakai
- grid.258806.10000 0001 2110 1386Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502 Japan
| | - Fred C. Boogerd
- grid.12380.380000 0004 1754 9227Department of Molecular Cell Biology, Faculty of Science, VU University Amsterdam, O
- 2 Building, Amsterdam, The Netherlands
| | - Hiroyuki Kurata
- grid.258806.10000 0001 2110 1386Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502 Japan
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7
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Bowlin MQ, Long AR, Huffines JT, Gray MJ. The role of nitrogen-responsive regulators in controlling inorganic polyphosphate synthesis in Escherichia coli. MICROBIOLOGY (READING, ENGLAND) 2022; 168:001185. [PMID: 35482529 PMCID: PMC10233264 DOI: 10.1099/mic.0.001185] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 04/10/2022] [Indexed: 12/22/2022]
Abstract
Inorganic polyphosphate (polyP) is synthesized by bacteria under stressful environmental conditions and acts by a variety of mechanisms to promote cell survival. While the kinase that synthesizes polyP (PPK, encoded by the ppk gene) is well known, ppk transcription is not activated by environmental stress and little is understood about how environmental stress signals lead to polyP accumulation. Previous work has shown that the transcriptional regulators DksA, RpoN (σ54) and RpoE (σ24) positively regulate polyP production, but not ppk transcription, in Escherichia coli. In this work, we examine the role of the alternative sigma factor RpoN and nitrogen starvation stress response pathways in controlling polyP synthesis. We show that the RpoN enhancer binding proteins GlnG and GlrR impact polyP production, and uncover a new role for the nitrogen phosphotransferase regulator PtsN (EIIANtr) as a positive regulator of polyP production, acting upstream of DksA, downstream of RpoN and apparently independently of RpoE. However, neither these regulatory proteins nor common nitrogen metabolites appear to act directly on PPK, and the precise mechanism(s) by which polyP production is modulated after stress remain(s) unclear. Unexpectedly, we also found that the genes that impact polyP production vary depending on the composition of the rich media in which the cells were grown before exposure to polyP-inducing stress. These results constitute progress towards deciphering the regulatory networks driving polyP production under stress, and highlight the remarkable complexity of this regulation and its connections to a broad range of stress-sensing pathways.
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Affiliation(s)
- Marvin Q. Bowlin
- Department of Microbiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Abagail Renee Long
- Department of Microbiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Joshua T. Huffines
- Department of Microbiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Michael Jeffrey Gray
- Department of Microbiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
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8
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Modelling Female Physiology from Head to Toe: Impact of Sex Hormones, Menstrual Cycle, and Pregnancy. J Theor Biol 2022; 540:111074. [DOI: 10.1016/j.jtbi.2022.111074] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 02/18/2022] [Accepted: 02/21/2022] [Indexed: 12/14/2022]
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9
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Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes. iScience 2021; 24:102101. [PMID: 33615200 PMCID: PMC7878987 DOI: 10.1016/j.isci.2021.102101] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 12/21/2020] [Accepted: 01/20/2021] [Indexed: 12/11/2022] Open
Abstract
A virtual metabolic human model is a valuable complement to experimental biology and clinical studies, because in vivo research involves serious ethical and technical problems. I have proposed a multi-organ and multi-scale kinetic model that formulates the reactions of enzymes and transporters with the regulation of hormonal actions at postprandial and postabsorptive states. The computational model consists of 202 ordinary differential equations for metabolites with 217 reaction rates and 1,140 kinetic parameter constants. It is the most comprehensive, largest, and highly predictive model of the whole-body metabolism. Use of the model revealed the mechanisms by which individual disorders, such as steatosis, β cell dysfunction, and insulin resistance, were combined to cause diabetes. The model predicted a glycerol kinase inhibitor to be an effective medicine for type 2 diabetes, which not only decreased hepatic triglyceride but also reduced plasma glucose. The model also enabled us to rationally design combination therapy. A standard of virtual metabolic human dynamic models is proposed It integrates the three scales of molecules, organs, and whole body It gets insight into pathological mechanisms of type 1 and type 2 diabetes It enables the computer-aided design of medication treatment for diabetes
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10
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N Kolodkin A, Sharma RP, Colangelo AM, Ignatenko A, Martorana F, Jennen D, Briedé JJ, Brady N, Barberis M, Mondeel TDGA, Papa M, Kumar V, Peters B, Skupin A, Alberghina L, Balling R, Westerhoff HV. ROS networks: designs, aging, Parkinson's disease and precision therapies. NPJ Syst Biol Appl 2020; 6:34. [PMID: 33106503 PMCID: PMC7589522 DOI: 10.1038/s41540-020-00150-w] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 08/28/2020] [Indexed: 12/11/2022] Open
Abstract
How the network around ROS protects against oxidative stress and Parkinson's disease (PD), and how processes at the minutes timescale cause disease and aging after decades, remains enigmatic. Challenging whether the ROS network is as complex as it seems, we built a fairly comprehensive version thereof which we disentangled into a hierarchy of only five simpler subnetworks each delivering one type of robustness. The comprehensive dynamic model described in vitro data sets from two independent laboratories. Notwithstanding its five-fold robustness, it exhibited a relatively sudden breakdown, after some 80 years of virtually steady performance: it predicted aging. PD-related conditions such as lack of DJ-1 protein or increased α-synuclein accelerated the collapse, while antioxidants or caffeine retarded it. Introducing a new concept (aging-time-control coefficient), we found that as many as 25 out of 57 molecular processes controlled aging. We identified new targets for "life-extending interventions": mitochondrial synthesis, KEAP1 degradation, and p62 metabolism.
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Affiliation(s)
- Alexey N Kolodkin
- Infrastructure for Systems Biology Europe (ISBE.NL), Amsterdam, The Netherlands.
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
- Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands.
- Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.
| | - Raju Prasad Sharma
- Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands
- Environmental Engineering Laboratory, Departament d'Enginyeria Quimica, Universitat Rovira i Virgili, Tarragona, Spain
| | - Anna Maria Colangelo
- Infrastructure for Systems Biology Europe (ISBE.IT), Milan, Italy
- SysBio Centre of Systems Biology (ISBE.IT), University of Milano-Bicocca, Milan, Italy
- Laboratory of Neuroscience "R Levi-Montalcini" Dept of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy
| | - Andrew Ignatenko
- Luxembourg Institute of Science and Technology (LIST), Esch-sur-Alzette, Luxembourg
| | - Francesca Martorana
- Infrastructure for Systems Biology Europe (ISBE.IT), Milan, Italy
- SysBio Centre of Systems Biology (ISBE.IT), University of Milano-Bicocca, Milan, Italy
- Laboratory of Neuroscience "R Levi-Montalcini" Dept of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy
| | - Danyel Jennen
- Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Jacco J Briedé
- Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Nathan Brady
- Department of Molecular Microbiology & Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Matteo Barberis
- Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Systems Biology, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
- Centre for Mathematical and Computational Biology, CMCB, University of Surrey, Surrey, UK
| | - Thierry D G A Mondeel
- Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Systems Biology, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
- Centre for Mathematical and Computational Biology, CMCB, University of Surrey, Surrey, UK
| | - Michele Papa
- SysBio Centre of Systems Biology (ISBE.IT), University of Milano-Bicocca, Milan, Italy
- Infrastructure for Systems Biology Europe (ISBE.IT), Naples, Italy
- Department of Mental and Physical Health, University of Campania-L. Vanvitelli, Napoli, Italia
| | - Vikas Kumar
- Environmental Engineering Laboratory, Departament d'Enginyeria Quimica, Universitat Rovira i Virgili, Tarragona, Spain
- IISPV, Hospital Universitari Sant Joan de Reus, Universitat Rovira I Virgili, Reus, Spain
| | - Bernhard Peters
- Faculty of Science, Technology and Communication, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Alexander Skupin
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Lilia Alberghina
- Infrastructure for Systems Biology Europe (ISBE.IT), Milan, Italy
- SysBio Centre of Systems Biology (ISBE.IT), University of Milano-Bicocca, Milan, Italy
| | - Rudi Balling
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Hans V Westerhoff
- Infrastructure for Systems Biology Europe (ISBE.NL), Amsterdam, The Netherlands.
- Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands.
- Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.
- Manchester Centre for Integrative Systems Biology, School for Chemical Engineering and Analytical Science, The University of Manchester, Manchester, UK.
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11
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Williamson G, Tamburrino G, Bizior A, Boeckstaens M, Dias Mirandela G, Bage MG, Pisliakov A, Ives CM, Terras E, Hoskisson PA, Marini AM, Zachariae U, Javelle A. A two-lane mechanism for selective biological ammonium transport. eLife 2020; 9:57183. [PMID: 32662768 PMCID: PMC7447429 DOI: 10.7554/elife.57183] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 07/13/2020] [Indexed: 11/13/2022] Open
Abstract
The transport of charged molecules across biological membranes faces the dual problem of accommodating charges in a highly hydrophobic environment while maintaining selective substrate translocation. This has been the subject of a particular controversy for the exchange of ammonium across cellular membranes, an essential process in all domains of life. Ammonium transport is mediated by the ubiquitous Amt/Mep/Rh transporters that includes the human Rhesus factors. Here, using a combination of electrophysiology, yeast functional complementation and extended molecular dynamics simulations, we reveal a unique two-lane pathway for electrogenic NH4+ transport in two archetypal members of the family, the transporters AmtB from Escherichia coli and Rh50 from Nitrosomonas europaea. The pathway underpins a mechanism by which charged H+ and neutral NH3 are carried separately across the membrane after NH4+ deprotonation. This mechanism defines a new principle of achieving transport selectivity against competing ions in a biological transport process.
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Affiliation(s)
- Gordon Williamson
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Giulia Tamburrino
- Computational Biology, School of Life Sciences, University of Dundee, Dundee, United Kingdom.,Physics, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Adriana Bizior
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Mélanie Boeckstaens
- Biology of Membrane Transport Laboratory, Department of Molecular Biology, Université Libre de Bruxelles, Gosselies, Belgium
| | - Gaëtan Dias Mirandela
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Marcus G Bage
- Computational Biology, School of Life Sciences, University of Dundee, Dundee, United Kingdom.,Physics, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Andrei Pisliakov
- Computational Biology, School of Life Sciences, University of Dundee, Dundee, United Kingdom.,Physics, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Callum M Ives
- Computational Biology, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Eilidh Terras
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Paul A Hoskisson
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Anna Maria Marini
- Biology of Membrane Transport Laboratory, Department of Molecular Biology, Université Libre de Bruxelles, Gosselies, Belgium
| | - Ulrich Zachariae
- Computational Biology, School of Life Sciences, University of Dundee, Dundee, United Kingdom.,Physics, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Arnaud Javelle
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
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Abudukelimu A, Barberis M, Redegeld F, Sahin N, Sharma RP, Westerhoff HV. Complex Stability and an Irrevertible Transition Reverted by Peptide and Fibroblasts in a Dynamic Model of Innate Immunity. Front Immunol 2020; 10:3091. [PMID: 32117197 PMCID: PMC7033641 DOI: 10.3389/fimmu.2019.03091] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 12/17/2019] [Indexed: 12/12/2022] Open
Abstract
We here apply a control analysis and various types of stability analysis to an in silico model of innate immunity that addresses the management of inflammation by a therapeutic peptide. Motivation is the observation, both in silico and in experiments, that this therapy is not robust. Our modeling results demonstrate how (1) the biological phenomena of acute and chronic modes of inflammation may reflect an inherently complex bistability with an irrevertible flip between the two modes, (2) the chronic mode of the model has stable, sometimes unique, steady states, while its acute-mode steady states are stable but not unique, (3) as witnessed by TNF levels, acute inflammation is controlled by multiple processes, whereas its chronic-mode inflammation is only controlled by TNF synthesis and washout, (4) only when the antigen load is close to the acute mode's flipping point, many processes impact very strongly on cells and cytokines, (5) there is no antigen exposure level below which reduction of the antigen load alone initiates a flip back to the acute mode, and (6) adding healthy fibroblasts makes the transition from acute to chronic inflammation revertible, although (7) there is a window of antigen load where such a therapy cannot be effective. This suggests that triple therapies may be essential to overcome chronic inflammation. These may comprise (1) anti-immunoglobulin light chain peptides, (2) a temporarily reduced antigen load, and (3a) fibroblast repopulation or (3b) stem cell strategies.
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Affiliation(s)
- Abulikemu Abudukelimu
- Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.,Molecular Cell Physiology, VU University Amsterdam, Amsterdam, Netherlands
| | - Matteo Barberis
- Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.,Systems Biology, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.,Centre for Mathematical and Computational Biology, CMCB, University of Surrey, Guildford, United Kingdom
| | - Frank Redegeld
- Division of Pharmacology, Department of Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Nilgun Sahin
- Molecular Cell Physiology, VU University Amsterdam, Amsterdam, Netherlands
| | - Raju P Sharma
- Molecular Cell Physiology, VU University Amsterdam, Amsterdam, Netherlands
| | - Hans V Westerhoff
- Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.,Molecular Cell Physiology, VU University Amsterdam, Amsterdam, Netherlands.,School for Chemical Engineering and Analytical Science, University of Manchester, Manchester, United Kingdom.,Systems Biology Amsterdam, VU University Amsterdam, Amsterdam, Netherlands
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Kurata H. Self-replenishment cycles generate a threshold response. Sci Rep 2019; 9:17139. [PMID: 31748624 PMCID: PMC6868230 DOI: 10.1038/s41598-019-53589-1] [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: 07/05/2019] [Accepted: 11/02/2019] [Indexed: 11/10/2022] Open
Abstract
Many metabolic cycles, including the tricarboxylic acid cycle, glyoxylate cycle, Calvin cycle, urea cycle, coenzyme recycling, and substrate cycles, are well known to catabolize and anabolize different metabolites for efficient energy and mass conversion. In terms of stoichiometric structure, this study explicitly identifies two types of metabolic cycles. One is the well-known, elementary cycle that converts multiple substrates into different products and recycles one of the products as a substrate, where the recycled substrate is supplied from the outside to run the cycle. The other is the self-replenishment cycle that merges multiple substrates into two or multiple identical products and reuses one of the products as a substrate. The substrates are autonomously supplied within the cycle. This study first defines the self-replenishment cycles that many scientists have overlooked despite its functional importance. Theoretical analysis has revealed the design principle of the self-replenishment cycle that presents a threshold response without any bistability nor cooperativity. To verify the principle, three detailed kinetic models of self-replenishment cycles embedded in an E. coli metabolic system were simulated. They presented the threshold response or digital switch-like function that steeply shift metabolic status.
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Affiliation(s)
- Hiroyuki Kurata
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Fukuoka, Japan. .,Biomedical Informatics R&D Center, Kyushu Institute of Technology, Fukuoka, Japan.
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