1
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Kariya Y, Honma M. Applications of model simulation in pharmacological fields and the problems of theoretical reliability. Drug Metab Pharmacokinet 2024; 56:100996. [PMID: 38797090 DOI: 10.1016/j.dmpk.2024.100996] [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: 11/02/2023] [Revised: 12/23/2023] [Accepted: 12/31/2023] [Indexed: 05/29/2024]
Abstract
The use of mathematical models has become increasingly prevalent in pharmacological fields, particularly in drug development processes. These models are instrumental in tasks such as designing clinical trials and assessing factors like efficacy, toxicity, and clinical practice. Various types of models have been developed and documented. Nevertheless, emphasizing the reliability of parameter values is crucial, as they play a pivotal role in shaping the behavior of the system. In some instances, parameter values reported previously are treated as fixed values, which can lead to convergence towards values that deviate substantially from those found in actual biological systems. This is especially true when parameter values are determined through fitting to limited observations. To mitigate this risk, the reuse of parameter values from previous reports should be approached with a critical evaluation of their validity. Currently, there is a proposal for a simultaneous search for plausible values for all parameters using comprehensive search algorithms in both pharmacokinetic and pharmacodynamic or systems pharmacological models. Implementing these methodologies can help address issues related to parameter determination. Furthermore, integrating these approaches with methods developed in the field of machine-learning field has the potential to enhance the reliability of parameter values and the resulting model outputs.
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Affiliation(s)
- Yoshiaki Kariya
- Education Center for Medical Pharmaceutics, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan; Laboratory of Pharmaceutical Regulatory Sciences, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan; Department of Pharmacy, The University of Tokyo Hospital, Faculty of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
| | - Masashi Honma
- Department of Pharmacy, The University of Tokyo Hospital, Faculty of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
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2
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Zhao L, Zhao Y, Liu Q, Huang J, Lu Y, Ping J. DDX5/METTL3-METTL14/YTHDF2 Axis Regulates Replication of Influenza A Virus. Microbiol Spectr 2022; 10:e0109822. [PMID: 35583334 PMCID: PMC9241928 DOI: 10.1128/spectrum.01098-22] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 04/28/2022] [Indexed: 12/14/2022] Open
Abstract
DEAD-box helicase 5 (DDX5), a member of the DEAD/H-box helicases, is known to participate in all aspects of RNA metabolism. However, its regulatory effect in antiviral innate immunity during replication of influenza virus remains unclear. Herein, we found that human DDX5 promotes replication of influenza virus in A549 cells. Moreover, our results further revealed that DDX5 relies on its N terminus to interact with the nucleoprotein (NP) of influenza virus, which is independent of RNA. Of course, we also observed colocalization of DDX5 with NP in the context of transfection or infection. However, influenza virus infection had no significant effect on the protein expression and nucleocytoplasmic distribution of DDX5. Importantly, we found that DDX5 suppresses antiviral innate immunity induced by influenza virus infection. Mechanistically, DDX5 downregulated the mRNA levels of interferon beta (IFN-β), interleukin 6 (IL-6), and DHX58 via the METTL3-METTL14/YTHDF2 axis. We revealed that DDX5 bound antiviral transcripts and regulated immune responses through YTHDF2-dependent mRNA decay. Taken together, our data demonstrate that the DDX5/METTL3-METTL14/YTHDF2 axis regulates the replication of influenza A virus. IMPORTANCE The replication and transcription of influenza virus depends on the participation of many host factors in cells. Exploring the relationship between viruses and host factors will help us fully understand the characteristics and pathogenic mechanisms of influenza viruses. In this study, we showed that DDX5 interacted with the NP of influenza virus. We demonstrated that DDX5 downregulated the expression of IFN-β and IL-6 and the transcription of antiviral genes downstream from IFN-β in influenza virus-infected A549 cells. Additionally, DDX5 downregulated the mRNA levels of antiviral transcripts via the METTL3-METTL14/YTHDF2 axis. Our findings provide a novel perspective to understand the mechanism by which DDX5 regulates antiviral immunity.
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Affiliation(s)
- Lingcai Zhao
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Yongzhen Zhao
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Qingzheng Liu
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Jingjin Huang
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Yuanlu Lu
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Jihui Ping
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
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3
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Adler SO, Spiesser TW, Uschner F, Münzner U, Hahn J, Krantz M, Klipp E. A yeast cell cycle model integrating stress, signaling, and physiology. FEMS Yeast Res 2022; 22:6592118. [PMID: 35617157 PMCID: PMC9246278 DOI: 10.1093/femsyr/foac026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 04/22/2022] [Accepted: 05/23/2022] [Indexed: 11/25/2022] Open
Abstract
The cell division cycle in eukaryotic cells is a series of highly coordinated molecular interactions that ensure that cell growth, duplication of genetic material, and actual cell division are precisely orchestrated to give rise to two viable progeny cells. Moreover, the cell cycle machinery is responsible for incorporating information about external cues or internal processes that the cell must keep track of to ensure a coordinated, timely progression of all related processes. This is most pronounced in multicellular organisms, but also a cardinal feature in model organisms such as baker's yeast. The complex and integrative behavior is difficult to grasp and requires mathematical modeling to fully understand the quantitative interplay of the single components within the entire system. Here, we present a self-oscillating mathematical model of the yeast cell cycle that comprises all major cyclins and their main regulators. Furthermore, it accounts for the regulation of the cell cycle machinery by a series of external stimuli such as mating pheromones and changes in osmotic pressure or nutrient quality. We demonstrate how the external perturbations modify the dynamics of cell cycle components and how the cell cycle resumes after adaptation to or relief from stress.
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Affiliation(s)
- Stephan O Adler
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
| | - Thomas W Spiesser
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
| | - Friedemann Uschner
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany.,Institute for Medical Informatics and Biometry, Technische Universität Dresden, Fetscherstr. 74, 01307 Dresden, Sachsen, Germany
| | - Ulrike Münzner
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany.,Laboratory of Cell Systems, Institute for Protein Research, Osaka University, 3-2 Yamadaoka, 565-0871, Suita, Osaka, Japan
| | - Jens Hahn
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
| | - Marcus Krantz
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
| | - Edda Klipp
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
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4
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Cyclin/Forkhead-mediated coordination of cyclin waves: an autonomous oscillator rationalizing the quantitative model of Cdk control for budding yeast. NPJ Syst Biol Appl 2021; 7:48. [PMID: 34903735 PMCID: PMC8668886 DOI: 10.1038/s41540-021-00201-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 11/01/2021] [Indexed: 01/21/2023] Open
Abstract
Networks of interacting molecules organize topology, amount, and timing of biological functions. Systems biology concepts required to pin down 'network motifs' or 'design principles' for time-dependent processes have been developed for the cell division cycle, through integration of predictive computer modeling with quantitative experimentation. A dynamic coordination of sequential waves of cyclin-dependent kinases (cyclin/Cdk) with the transcription factors network offers insights to investigate how incompatible processes are kept separate in time during the eukaryotic cell cycle. Here this coordination is discussed for the Forkhead transcription factors in light of missing gaps in the current knowledge of cell cycle control in budding yeast. An emergent design principle is proposed where cyclin waves are synchronized by a cyclin/Cdk-mediated feed-forward regulation through the Forkhead as a transcriptional timer. This design is rationalized by the bidirectional interaction between mitotic cyclins and the Forkhead transcriptional timer, resulting in an autonomous oscillator that may be instrumental for a well-timed progression throughout the cell cycle. The regulation centered around the cyclin/Cdk-Forkhead axis can be pivotal to timely coordinate cell cycle dynamics, thereby to actuate the quantitative model of Cdk control.
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5
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Tyson JJ, Novak B. A Dynamical Paradigm for Molecular Cell Biology. Trends Cell Biol 2020; 30:504-515. [DOI: 10.1016/j.tcb.2020.04.002] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 03/30/2020] [Accepted: 04/01/2020] [Indexed: 12/20/2022]
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6
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Gallegos JE, Adames NR, Rogers MF, Kraikivski P, Ibele A, Nurzynski-Loth K, Kudlow E, Murali TM, Tyson JJ, Peccoud J. Genetic interactions derived from high-throughput phenotyping of 6589 yeast cell cycle mutants. NPJ Syst Biol Appl 2020; 6:11. [PMID: 32376972 PMCID: PMC7203125 DOI: 10.1038/s41540-020-0134-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 04/06/2020] [Indexed: 11/09/2022] Open
Abstract
Over the last 30 years, computational biologists have developed increasingly realistic mathematical models of the regulatory networks controlling the division of eukaryotic cells. These models capture data resulting from two complementary experimental approaches: low-throughput experiments aimed at extensively characterizing the functions of small numbers of genes, and large-scale genetic interaction screens that provide a systems-level perspective on the cell division process. The former is insufficient to capture the interconnectivity of the genetic control network, while the latter is fraught with irreproducibility issues. Here, we describe a hybrid approach in which the 630 genetic interactions between 36 cell-cycle genes are quantitatively estimated by high-throughput phenotyping with an unprecedented number of biological replicates. Using this approach, we identify a subset of high-confidence genetic interactions, which we use to refine a previously published mathematical model of the cell cycle. We also present a quantitative dataset of the growth rate of these mutants under six different media conditions in order to inform future cell cycle models.
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Affiliation(s)
- Jenna E Gallegos
- Colorado State University, Chemical and Biological Engineering, Fort Collins, CO, USA
| | - Neil R Adames
- Colorado State University, Chemical and Biological Engineering, Fort Collins, CO, USA.,New Culture, Inc., San Francisco, CA, USA
| | | | - Pavel Kraikivski
- Virginia Tech, Academy of Integrated Sciences, Blacksburg, VA, USA
| | - Aubrey Ibele
- Colorado State University, Chemical and Biological Engineering, Fort Collins, CO, USA
| | - Kevin Nurzynski-Loth
- Colorado State University, Chemical and Biological Engineering, Fort Collins, CO, USA
| | - Eric Kudlow
- Colorado State University, Chemical and Biological Engineering, Fort Collins, CO, USA
| | - T M Murali
- Virginia Tech, Computer Science, Blacksburg, VA, USA
| | - John J Tyson
- Virginia Tech, Biological Sciences, Blacksburg, VA, USA
| | - Jean Peccoud
- Colorado State University, Chemical and Biological Engineering, Fort Collins, CO, USA. .,GenoFAB, Inc., Fort Collins, CO, USA.
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7
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Mondeel TDGA, Ivanov O, Westerhoff HV, Liebermeister W, Barberis M. Clb3-centered regulations are recurrent across distinct parameter regions in minimal autonomous cell cycle oscillator designs. NPJ Syst Biol Appl 2020; 6:8. [PMID: 32245958 PMCID: PMC7125140 DOI: 10.1038/s41540-020-0125-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Accepted: 02/20/2020] [Indexed: 12/13/2022] Open
Abstract
Some biological networks exhibit oscillations in their components to convert stimuli to time-dependent responses. The eukaryotic cell cycle is such a case, being governed by waves of cyclin-dependent kinase (cyclin/Cdk) activities that rise and fall with specific timing and guarantee its timely occurrence. Disruption of cyclin/Cdk oscillations could result in dysfunction through reduced cell division. Therefore, it is of interest to capture properties of network designs that exhibit robust oscillations. Here we show that a minimal yeast cell cycle network is able to oscillate autonomously, and that cyclin/Cdk-mediated positive feedback loops (PFLs) and Clb3-centered regulations sustain cyclin/Cdk oscillations, in known and hypothetical network designs. We propose that Clb3-mediated coordination of cyclin/Cdk waves reconciles checkpoint and oscillatory cell cycle models. Considering the evolutionary conservation of the cyclin/Cdk network across eukaryotes, we hypothesize that functional ("healthy") phenotypes require the capacity to oscillate autonomously whereas dysfunctional (potentially "diseased") phenotypes may lack this capacity.
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Affiliation(s)
- Thierry D G A Mondeel
- Systems Biology, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, UK.,Centre for Mathematical and Computational Biology, CMCB, University of Surrey, Guildford, UK.,Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Oleksandr Ivanov
- Theoretical Research in Evolutionary Life Sciences, Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands.,Systems, Control and Applied Analysis Group, Johan Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen, The Netherlands
| | - Hans V Westerhoff
- Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Wolfram Liebermeister
- Institute of Biochemistry, Charité Universitätsmedizin Berlin, Berlin, Germany.,Université Paris-Saclay, INRAE, MaIAGE, Jouy en Josas, France
| | - Matteo Barberis
- Systems Biology, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, UK. .,Centre for Mathematical and Computational Biology, CMCB, University of Surrey, Guildford, UK. .,Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.
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8
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Münzner U, Klipp E, Krantz M. A comprehensive, mechanistically detailed, and executable model of the cell division cycle in Saccharomyces cerevisiae. Nat Commun 2019; 10:1308. [PMID: 30899000 PMCID: PMC6428898 DOI: 10.1038/s41467-019-08903-w] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2018] [Accepted: 01/24/2019] [Indexed: 01/31/2023] Open
Abstract
Understanding how cellular functions emerge from the underlying molecular mechanisms is a key challenge in biology. This will require computational models, whose predictive power is expected to increase with coverage and precision of formulation. Genome-scale models revolutionised the metabolic field and made the first whole-cell model possible. However, the lack of genome-scale models of signalling networks blocks the development of eukaryotic whole-cell models. Here, we present a comprehensive mechanistic model of the molecular network that controls the cell division cycle in Saccharomyces cerevisiae. We use rxncon, the reaction-contingency language, to neutralise the scalability issues preventing formulation, visualisation and simulation of signalling networks at the genome-scale. We use parameter-free modelling to validate the network and to predict genotype-to-phenotype relationships down to residue resolution. This mechanistic genome-scale model offers a new perspective on eukaryotic cell cycle control, and opens up for similar models-and eventually whole-cell models-of human cells.
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Affiliation(s)
- Ulrike Münzner
- Humboldt-Universität zu Berlin, Institute of Biology, Theoretical Biophysics, Berlin, 10099, Germany
- Bioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, 611-0011, Japan
| | - Edda Klipp
- Humboldt-Universität zu Berlin, Institute of Biology, Theoretical Biophysics, Berlin, 10099, Germany
| | - Marcus Krantz
- Humboldt-Universität zu Berlin, Institute of Biology, Theoretical Biophysics, Berlin, 10099, Germany.
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9
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Ostaszewski M, Kieffer E, Danoy G, Schneider R, Bouvry P. Clustering approaches for visual knowledge exploration in molecular interaction networks. BMC Bioinformatics 2018; 19:308. [PMID: 30157777 PMCID: PMC6116538 DOI: 10.1186/s12859-018-2314-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 08/14/2018] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Biomedical knowledge grows in complexity, and becomes encoded in network-based repositories, which include focused, expert-drawn diagrams, networks of evidence-based associations and established ontologies. Combining these structured information sources is an important computational challenge, as large graphs are difficult to analyze visually. RESULTS We investigate knowledge discovery in manually curated and annotated molecular interaction diagrams. To evaluate similarity of content we use: i) Euclidean distance in expert-drawn diagrams, ii) shortest path distance using the underlying network and iii) ontology-based distance. We employ clustering with these metrics used separately and in pairwise combinations. We propose a novel bi-level optimization approach together with an evolutionary algorithm for informative combination of distance metrics. We compare the enrichment of the obtained clusters between the solutions and with expert knowledge. We calculate the number of Gene and Disease Ontology terms discovered by different solutions as a measure of cluster quality. Our results show that combining distance metrics can improve clustering accuracy, based on the comparison with expert-provided clusters. Also, the performance of specific combinations of distance functions depends on the clustering depth (number of clusters). By employing bi-level optimization approach we evaluated relative importance of distance functions and we found that indeed the order by which they are combined affects clustering performance. Next, with the enrichment analysis of clustering results we found that both hierarchical and bi-level clustering schemes discovered more Gene and Disease Ontology terms than expert-provided clusters for the same knowledge repository. Moreover, bi-level clustering found more enriched terms than the best hierarchical clustering solution for three distinct distance metric combinations in three different instances of disease maps. CONCLUSIONS In this work we examined the impact of different distance functions on clustering of a visual biomedical knowledge repository. We found that combining distance functions may be beneficial for clustering, and improve exploration of such repositories. We proposed bi-level optimization to evaluate the importance of order by which the distance functions are combined. Both combination and order of these functions affected clustering quality and knowledge recognition in the considered benchmarks. We propose that multiple dimensions can be utilized simultaneously for visual knowledge exploration.
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Affiliation(s)
- Marek Ostaszewski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, Avenue des Hauts-Fourneaux, Esch-Belval, Luxembourg
| | - Emmanuel Kieffer
- Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, 6, Avenue de la Fonte, Esch-Belval, Luxembourg
| | - Grégoire Danoy
- Computer Science and Communications Research Unit, University of Luxembourg, 6, Avenue de la Fonte, Esch-Belval, Luxembourg
| | - Reinhard Schneider
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, Avenue des Hauts-Fourneaux, Esch-Belval, Luxembourg
| | - Pascal Bouvry
- Computer Science and Communications Research Unit, University of Luxembourg, 6, Avenue de la Fonte, Esch-Belval, Luxembourg
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10
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Zhou S, Appleman VA, Rose CM, Jun HJ, Yang J, Zhou Y, Bronson RT, Gygi SP, Charest A. Chronic platelet-derived growth factor receptor signaling exerts control over initiation of protein translation in glioma. Life Sci Alliance 2018; 1:e201800029. [PMID: 30456354 PMCID: PMC6238596 DOI: 10.26508/lsa.201800029] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Revised: 05/29/2018] [Accepted: 05/29/2018] [Indexed: 01/23/2023] Open
Abstract
Using phospho-proteomics in a new model of malignant glioma, we reveal that clinically relevant, chronic PDGFRα signaling differs considerably from acute receptor stimulation and unveils previously unrecognized control over key elements of the translation initiation machinery. Activation of the platelet-derived growth factor receptors (PDGFRs) gives rise to some of the most important signaling pathways that regulate mammalian cellular growth, survival, proliferation, and differentiation and their misregulation is common in a variety of diseases. Herein, we present a comprehensive and detailed map of PDGFR signaling pathways assembled from literature and integrate this map in a bioinformatics protocol designed to extract meaningful information from large-scale quantitative proteomics mass spectrometry data. We demonstrate the usefulness of this approach using a new genetically engineered mouse model of PDGFRα-driven glioma. We discovered that acute PDGFRα stimulation differs considerably from chronic receptor activation in the regulation of protein translation initiation. Transient stimulation activates several key components of the translation initiation machinery, whereas the clinically relevant chronic activity of PDGFRα is associated with a significant shutdown of translational members. Our work defines a step-by-step approach to extract biologically relevant insights from global unbiased phospho-protein datasets to uncover targets for therapeutic assessment.
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Affiliation(s)
- Shuang Zhou
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Vicky A Appleman
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Hyun Jung Jun
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Juechen Yang
- Department of Computer Science, North Dakota State University, Fargo, ND, USA
| | - Yue Zhou
- Department of Statistics, North Dakota State University, Fargo, ND, USA
| | - Roderick T Bronson
- Rodent Histopathology Core, Dana-Farber/Harvard Cancer Center, Boston, MA, USA
| | - Steve P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
| | - Al Charest
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA
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11
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Pathak RK, Baunthiyal M, Pandey N, Pandey D, Kumar A. Modeling of the jasmonate signaling pathway in Arabidopsis thaliana with respect to pathophysiology of Alternaria blight in Brassica. Sci Rep 2017; 7:16790. [PMID: 29196636 PMCID: PMC5711873 DOI: 10.1038/s41598-017-16884-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Accepted: 11/08/2017] [Indexed: 01/01/2023] Open
Abstract
The productivity of Oilseed Brassica, one of the economically important crops of India, is seriously affected by the disease, Alternaria blight. The disease is mainly caused by two major necrotrophic fungi, Alternaria brassicae and Alternaria brassicicola which are responsible for significant yield losses. Till date, no resistant source is available against Alternaria blight, hence plant breeding methods can not be used to develop disease resistant varieties. Jasmonate mediated signalling pathway, which is known to play crucial role during defense response against necrotrophs, could be strengthened in Brassica plants to combat the disease. Since scanty information is available in Brassica-Alternaria pathosystems at molecular level therefore, in the present study efforts have been made to model jasmonic acid pathway in Arabidopsis thaliana to simulate the dynamic behaviour of molecular species in the model. Besides, the developed model was also analyzed topologically for investigation of the hubs node. COI1 is identified as one of the promising candidate genes in response to Alternaria and other linked components of plant defense mechanisms against the pathogens. The findings from present study are therefore informative for understanding the molecular basis of pathophysiology and rational management of Alternaria blight for securing food and nutritional security.
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Affiliation(s)
- Rajesh Kumar Pathak
- Department of Biotechnology, Govind Ballabh Pant Institute of Engineering & Technology, Pauri Garhwal, 246194, Uttarakhand, India
| | - Mamta Baunthiyal
- Department of Biotechnology, Govind Ballabh Pant Institute of Engineering & Technology, Pauri Garhwal, 246194, Uttarakhand, India.
| | - Neetesh Pandey
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute (IASRI), Pusa, 110012, New Delhi, India
| | - Dinesh Pandey
- Department of Molecular Biology & Genetic Engineering, College of Basic Sciences & Humanities, G. B. Pant University of Agriculture & Technology, Pantnagar, 263145, India
| | - Anil Kumar
- Department of Molecular Biology & Genetic Engineering, College of Basic Sciences & Humanities, G. B. Pant University of Agriculture & Technology, Pantnagar, 263145, India.
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12
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Dhusia K, Bajpai A, Ramteke PW. Overcoming antibiotic resistance: Is siderophore Trojan horse conjugation an answer to evolving resistance in microbial pathogens? J Control Release 2017; 269:63-87. [PMID: 29129658 DOI: 10.1016/j.jconrel.2017.11.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 10/30/2017] [Accepted: 11/01/2017] [Indexed: 01/11/2023]
Abstract
Comparative study of siderophore biosynthesis pathway in pathogens provides potential targets for antibiotics and host drug delivery as a part of computationally feasible microbial therapy. Iron acquisition using siderophore models is an essential and well established model in all microorganisms and microbial infections a known to cause great havoc to both plant and animal. Rapid development of antibiotic resistance in bacterial as well as fungal pathogens has drawn us at a verge where one has to get rid of the traditional way of obstructing pathogen using single or multiple antibiotic/chemical inhibitors or drugs. 'Trojan horse' strategy is an answer to this imperative call where antibiotic are by far sneaked into the pathogenic cell via the siderophore receptors at cell and outer membrane. This antibiotic once gets inside, generates a 'black hole' scenario within the opportunistic pathogens via iron scarcity. For pathogens whose siderophore are not compatible to smuggle drug due to their complex conformation and stiff valence bonds, there is another approach. By means of the siderophore biosynthesis pathways, potential targets for inhibition of these siderophores in pathogenic bacteria could be achieved and thus control pathogenic virulence. Method to design artificial exogenous siderophores for pathogens that would compete and succeed the battle of intake is also covered with this review. These manipulated siderophore would enter pathogenic cell like any other siderophore but will not disperse iron due to which iron inadequacy and hence pathogens control be accomplished. The aim of this review is to offer strategies to overcome the microbial infections/pathogens using siderophore.
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Affiliation(s)
- Kalyani Dhusia
- Deptartment of Computational Biology and Bioinformatics, Jacob Institute of Biotechnology and Bio-Engineering, Sam Higginbottom University of Agriculture, Technology and Sciences (SHUATS), Allahabad-211007 (U.P.), India
| | - Archana Bajpai
- Laboratory for Disease Systems Modeling, Center for Integrative Medical Sciences, RIKEN, Yokohama City, Kanagawa, 230-0045, Japan
| | - P W Ramteke
- Deptartment of Computational Biology and Bioinformatics, Jacob Institute of Biotechnology and Bio-Engineering, Sam Higginbottom University of Agriculture, Technology and Sciences (SHUATS), Allahabad-211007 (U.P.), India
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13
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Quantitative Systems Biology to decipher design principles of a dynamic cell cycle network: the "Maximum Allowable mammalian Trade-Off-Weight" (MAmTOW). NPJ Syst Biol Appl 2017; 3:26. [PMID: 28944079 PMCID: PMC5605530 DOI: 10.1038/s41540-017-0028-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2017] [Revised: 08/18/2017] [Accepted: 08/24/2017] [Indexed: 12/11/2022] Open
Abstract
Network complexity is required to lend cellular processes flexibility to respond timely to a variety of dynamic signals, while simultaneously warranting robustness to protect cellular integrity against perturbations. The cell cycle serves as a paradigm for such processes; it maintains its frequency and temporal structure (although these may differ among cell types) under the former, but accelerates under the latter. Cell cycle molecules act together in time and in different cellular compartments to execute cell type-specific programs. Strikingly, the timing at which molecular switches occur is controlled by abundance and stoichiometry of multiple proteins within complexes. However, traditional methods that investigate one effector at a time are insufficient to understand how modulation of protein complex dynamics at cell cycle transitions shapes responsiveness, yet preserving robustness. To overcome this shortcoming, we propose a multidisciplinary approach to gain a systems-level understanding of quantitative cell cycle dynamics in mammalian cells from a new perspective. By suggesting advanced experimental technologies and dedicated modeling approaches, we present innovative strategies (i) to measure absolute protein concentration in vivo, and (ii) to determine how protein dosage, e.g., altered protein abundance, and spatial (de)regulation may affect timing and robustness of phase transitions. We describe a method that we name “Maximum Allowable mammalian Trade–Off–Weight” (MAmTOW), which may be realized to determine the upper limit of gene copy numbers in mammalian cells. These aspects, not covered by current systems biology approaches, are essential requirements to generate precise computational models and identify (sub)network-centered nodes underlying a plethora of pathological conditions.
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14
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Frumkin JP, Patra BN, Sevold A, Ganguly K, Patel C, Yoon S, Schmid MB, Ray A. The interplay between chromosome stability and cell cycle control explored through gene-gene interaction and computational simulation. Nucleic Acids Res 2016; 44:8073-85. [PMID: 27530428 PMCID: PMC5041493 DOI: 10.1093/nar/gkw715] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2016] [Accepted: 08/05/2016] [Indexed: 02/02/2023] Open
Abstract
Chromosome stability models are usually qualitative models derived from molecular-genetic mechanisms for DNA repair, DNA synthesis, and cell division. While qualitative models are informative, they are also challenging to reformulate as precise quantitative models. In this report we explore how (A) laboratory experiments, (B) quantitative simulation, and (C) seriation algorithms can inform models of chromosome stability. Laboratory experiments were used to identify 19 genes that when over-expressed cause chromosome instability in the yeast Saccharomyces cerevisiae To better understand the molecular mechanisms by which these genes act, we explored their genetic interactions with 18 deletion mutations known to cause chromosome instability. Quantitative simulations based on a mathematical model of the cell cycle were used to predict the consequences of several genetic interactions. These simulations lead us to suspect that the chromosome instability genes cause cell-cycle perturbations. Cell-cycle involvement was confirmed using a seriation algorithm, which was used to analyze the genetic interaction matrix to reveal an underlying cyclical pattern. The seriation algorithm searched over 10(14) possible arrangements of rows and columns to find one optimal arrangement, which correctly reflects events during cell cycle phases. To conclude, we illustrate how the molecular mechanisms behind these cell cycle events are consistent with established molecular interaction maps.
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Affiliation(s)
- Jesse P Frumkin
- School of Applied Life Sciences, Keck Graduate Institute, Claremont, CA 91711, USA Mathematics Department, Claremont Graduate University, Claremont, CA 91711, USA
| | - Biranchi N Patra
- School of Applied Life Sciences, Keck Graduate Institute, Claremont, CA 91711, USA
| | - Anthony Sevold
- School of Applied Life Sciences, Keck Graduate Institute, Claremont, CA 91711, USA
| | - Kumkum Ganguly
- Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
| | - Chaya Patel
- School of Applied Life Sciences, Keck Graduate Institute, Claremont, CA 91711, USA
| | - Stephanie Yoon
- School of Applied Life Sciences, Keck Graduate Institute, Claremont, CA 91711, USA
| | - Molly B Schmid
- School of Applied Life Sciences, Keck Graduate Institute, Claremont, CA 91711, USA
| | - Animesh Ray
- School of Applied Life Sciences, Keck Graduate Institute, Claremont, CA 91711, USA Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
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15
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Cell-cycle involvement in autophagy and apoptosis in yeast. Mech Ageing Dev 2016; 161:211-224. [PMID: 27450768 DOI: 10.1016/j.mad.2016.07.006] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2016] [Revised: 06/16/2016] [Accepted: 07/17/2016] [Indexed: 12/14/2022]
Abstract
Regulation of the cell cycle and apoptosis are two eukaryotic processes required to ensure maintenance of genomic integrity, especially in response to DNA damage. The ease with which yeast, amongst other eukaryotes, can switch from cellular proliferation to cell death may be the result of a common set of biochemical factors which play dual roles depending on the cell's physiological state. A wide variety of homologues are shared between different yeasts and metazoans and this conservation confirms their importance. This review gives an overview of key molecular players involved in yeast cell-cycle regulation, and those involved in mechanisms which are induced by cell-cycle dysregulation. One such mechanism is autophagy which, depending on the severity and type of DNA damage, may either contribute to the cell's survival or death. Cell-cycle dysregulation due to checkpoint deficiency leads to mitotic catastrophe which in turn leads to programmed cell death. Molecular players implicated in the yeast apoptotic pathway were shown to play important roles in the cell cycle. These include the metacaspase Yca1p, the caspase-like protein Esp1p, the cohesin subunit Mcd1p, as well as the inhibitor of apoptosis protein Bir1p. The roles of these molecular players are discussed.
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16
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Palumbo P, Vanoni M, Cusimano V, Busti S, Marano F, Manes C, Alberghina L. Whi5 phosphorylation embedded in the G1/S network dynamically controls critical cell size and cell fate. Nat Commun 2016; 7:11372. [PMID: 27094800 PMCID: PMC4843020 DOI: 10.1038/ncomms11372] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Accepted: 03/18/2016] [Indexed: 01/23/2023] Open
Abstract
In budding yeast, overcoming of a critical size to enter S phase and the mitosis/mating switch--two central cell fate events--take place in the G1 phase of the cell cycle. Here we present a mathematical model of the basic molecular mechanism controlling the G1/S transition, whose major regulatory feature is multisite phosphorylation of nuclear Whi5. Cln3-Cdk1, whose nuclear amount is proportional to cell size, and then Cln1,2-Cdk1, randomly phosphorylate both decoy and functional Whi5 sites. Full phosphorylation of functional sites releases Whi5 inhibitory activity, activating G1/S transcription. Simulation analysis shows that this mechanism ensures coherent release of Whi5 inhibitory action and accounts for many experimentally observed properties of mitotically growing or conjugating G1 cells. Cell cycle progression and transcriptional analyses of a Whi5 phosphomimetic mutant verify the model prediction that coherent transcription of the G1/S regulon and ensuing G1/S transition requires full phosphorylation of Whi5 functional sites.
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Affiliation(s)
- Pasquale Palumbo
- SYSBIO.IT Center for Systems Biology, Italy.,CNR-IASI, Italian National Research Council - Institute for Systems Analysis and Computer Science, Via dei Taurini 19, 00185 Rome, Italy
| | - Marco Vanoni
- SYSBIO.IT Center for Systems Biology, Italy.,Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milan, Italy
| | - Valerio Cusimano
- SYSBIO.IT Center for Systems Biology, Italy.,CNR-IASI, Italian National Research Council - Institute for Systems Analysis and Computer Science, Via dei Taurini 19, 00185 Rome, Italy
| | - Stefano Busti
- SYSBIO.IT Center for Systems Biology, Italy.,Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milan, Italy
| | - Francesca Marano
- SYSBIO.IT Center for Systems Biology, Italy.,Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milan, Italy
| | - Costanzo Manes
- CNR-IASI, Italian National Research Council - Institute for Systems Analysis and Computer Science, Via dei Taurini 19, 00185 Rome, Italy.,Department of Information Engineering, Computer Science and Mathematics, University of L'Aquila, Via Vetoio, 67100 Coppito (L'Aquila), Italy
| | - Lilia Alberghina
- SYSBIO.IT Center for Systems Biology, Italy.,Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milan, Italy
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17
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Kawakami E, Singh VK, Matsubara K, Ishii T, Matsuoka Y, Hase T, Kulkarni P, Siddiqui K, Kodilkar J, Danve N, Subramanian I, Katoh M, Shimizu-Yoshida Y, Ghosh S, Jere A, Kitano H. Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways. NPJ Syst Biol Appl 2016; 2:15018. [PMID: 28725465 PMCID: PMC5516916 DOI: 10.1038/npjsba.2015.18] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Revised: 09/08/2015] [Accepted: 10/13/2015] [Indexed: 11/09/2022] Open
Abstract
Cellular stress responses require exquisite coordination between intracellular signaling molecules to integrate multiple stimuli and actuate specific cellular behaviors. Deciphering the web of complex interactions underlying stress responses is a key challenge in understanding robust biological systems and has the potential to lead to the discovery of targeted therapeutics for diseases triggered by dysregulation of stress response pathways. We constructed large-scale molecular interaction maps of six major stress response pathways in Saccharomyces cerevisiae (baker's or budding yeast). Biological findings from over 900 publications were converted into standardized graphical formats and integrated into a common framework. The maps are posted at http://www.yeast-maps.org/yeast-stress-response/ for browse and curation by the research community. On the basis of these maps, we undertook systematic analyses to unravel the underlying architecture of the networks. A series of network analyses revealed that yeast stress response pathways are organized in bow-tie structures, which have been proposed as universal sub-systems for robust biological regulation. Furthermore, we demonstrated a potential role for complexes in stabilizing the conserved core molecules of bow-tie structures. Specifically, complex-mediated reversible reactions, identified by network motif analyses, appeared to have an important role in buffering the concentration and activity of these core molecules. We propose complex-mediated reactions as a key mechanism mediating robust regulation of the yeast stress response. Thus, our comprehensive molecular interaction maps provide not only an integrated knowledge base, but also a platform for systematic network analyses to elucidate the underlying architecture in complex biological systems.
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Affiliation(s)
- Eiryo Kawakami
- Laboratory for Disease Systems Modeling, RIKEN-IMS, Kanagawa, Japan
| | | | | | - Takashi Ishii
- Laboratory for Disease Systems Modeling, RIKEN-IMS, Kanagawa, Japan
| | | | | | | | | | | | | | | | | | - Yuki Shimizu-Yoshida
- Laboratory for Disease Systems Modeling, RIKEN-IMS, Kanagawa, Japan.,Sony Computer Science Laboratories, Inc., Tokyo, Japan
| | | | - Abhay Jere
- LABS, Persistent Systems Limited, Pune, India
| | - Hiroaki Kitano
- Laboratory for Disease Systems Modeling, RIKEN-IMS, Kanagawa, Japan.,The Systems Biology Institute, Tokyo, Japan.,Sony Computer Science Laboratories, Inc., Tokyo, Japan.,Integrated Open Systems Unit, Okinawa Institute of Science and Technology, Okinawa, Japan
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18
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Csikász-Nagy A, Mura I. Role of Computational Modeling in Understanding Cell Cycle Oscillators. Methods Mol Biol 2016; 1342:59-70. [PMID: 26254917 DOI: 10.1007/978-1-4939-2957-3_3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The periodic oscillations in the activity of the cell cycle regulatory program, drives the timely activation of key cell cycle events. Interesting dynamical systems, such as oscillators, have been investigated by various theoretical and computational modeling methods. Thanks to the insights achieved by these modeling efforts we have gained considerable insights about the underlying molecular regulatory networks that can drive cell cycle oscillations. Here we review the basic features and characteristics of biological oscillators, discussing from a computational modeling point of view their specific architectures and the current knowledge about the dynamics that the life evolution selected to drive cell cycle oscillations.
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Affiliation(s)
- Attila Csikász-Nagy
- Randall Division of Cell and Molecular Biophysics, King's College London, Strand, London, SE1 1UL, UK,
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19
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Lubitz T, Welkenhuysen N, Shashkova S, Bendrioua L, Hohmann S, Klipp E, Krantz M. Network reconstruction and validation of the Snf1/AMPK pathway in baker's yeast based on a comprehensive literature review. NPJ Syst Biol Appl 2015; 1:15007. [PMID: 28725459 PMCID: PMC5516868 DOI: 10.1038/npjsba.2015.7] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2015] [Revised: 06/19/2015] [Accepted: 07/14/2015] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND/OBJECTIVES The SNF1/AMPK protein kinase has a central role in energy homeostasis in eukaryotic cells. It is activated by energy depletion and stimulates processes leading to the production of ATP while it downregulates ATP-consuming processes. The yeast SNF1 complex is best known for its role in glucose derepression. METHODS We performed a network reconstruction of the Snf1 pathway based on a comprehensive literature review. The network was formalised in the rxncon language, and we used the rxncon toolbox for model validation and gap filling. RESULTS We present a machine-readable network definition that summarises the mechanistic knowledge of the Snf1 pathway. Furthermore, we used the known input/output relationships in the network to identify and fill gaps in the information transfer through the pathway, to produce a functional network model. Finally, we convert the functional network model into a rule-based model as a proof-of-principle. CONCLUSIONS The workflow presented here enables large scale reconstruction, validation and gap filling of signal transduction networks. It is analogous to but distinct from that established for metabolic networks. We demonstrate the workflow capabilities, and the direct link between the reconstruction and dynamic modelling, with the Snf1 network. This network is a distillation of the knowledge from all previous publications on the Snf1/AMPK pathway. The network is a knowledge resource for modellers and experimentalists alike, and a template for similar efforts in higher eukaryotes. Finally, we envisage the workflow as an instrumental tool for reconstruction of large signalling networks across Eukaryota.
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Affiliation(s)
- Timo Lubitz
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Niek Welkenhuysen
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Sviatlana Shashkova
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Loubna Bendrioua
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Stefan Hohmann
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Edda Klipp
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Marcus Krantz
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany
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20
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Tripathi S, Flobak Å, Chawla K, Baudot A, Bruland T, Thommesen L, Kuiper M, Lægreid A. The gastrin and cholecystokinin receptors mediated signaling network: a scaffold for data analysis and new hypotheses on regulatory mechanisms. BMC SYSTEMS BIOLOGY 2015. [PMID: 26205660 PMCID: PMC4513977 DOI: 10.1186/s12918-015-0181-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background The gastrointestinal peptide hormones cholecystokinin and gastrin exert their biological functions via cholecystokinin receptors CCK1R and CCK2R respectively. Gastrin, a central regulator of gastric acid secretion, is involved in growth and differentiation of gastric and colonic mucosa, and there is evidence that it is pro-carcinogenic. Cholecystokinin is implicated in digestion, appetite control and body weight regulation, and may play a role in several digestive disorders. Results We performed a detailed analysis of the literature reporting experimental evidence on signaling pathways triggered by CCK1R and CCK2R, in order to create a comprehensive map of gastrin and cholecystokinin-mediated intracellular signaling cascades. The resulting signaling map captures 413 reactions involving 530 molecular species, and incorporates the currently available knowledge into one integrated signaling network. The decomposition of the signaling map into sub-networks revealed 18 modules that represent higher-level structures of the signaling map. These modules allow a more compact mapping of intracellular signaling reactions to known cell behavioral outcomes such as proliferation, migration and apoptosis. The integration of large-scale protein-protein interaction data to this literature-based signaling map in combination with topological analyses allowed us to identify 70 proteins able to increase the compactness of the map. These proteins represent experimentally testable hypotheses for gaining new knowledge on gastrin- and cholecystokinin receptor signaling. The CCKR map is freely available both in a downloadable, machine-readable SBML-compatible format and as a web resource through PAYAO (http://sblab.celldesigner.org:18080/Payao11/bin/). Conclusion We have demonstrated how a literature-based CCKR signaling map together with its protein interaction extensions can be analyzed to generate new hypotheses on molecular mechanisms involved in gastrin- and cholecystokinin-mediated regulation of cellular processes. Electronic supplementary material The online version of this article (doi:10.1186/s12918-015-0181-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sushil Tripathi
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), N-7489, Trondheim, Norway.
| | - Åsmund Flobak
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), N-7489, Trondheim, Norway.
| | - Konika Chawla
- Department of Biology, Norwegian University of Science and Technology (NTNU), N-7491, Trondheim, Norway.
| | - Anaïs Baudot
- I2M, Marseilles Institute of Mathematics CNRS - AMU, Case 907, 13288, Marseille, Cedex 9, France.
| | - Torunn Bruland
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), N-7489, Trondheim, Norway.
| | - Liv Thommesen
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), N-7489, Trondheim, Norway. .,Department of Technology, Sør-Trøndelag University College, N-7004, Trondheim, Norway.
| | - Martin Kuiper
- Department of Biology, Norwegian University of Science and Technology (NTNU), N-7491, Trondheim, Norway.
| | - Astrid Lægreid
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), N-7489, Trondheim, Norway. .,Institute of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), N-7489, Trondheim, Norway.
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21
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Pyysalo S, Ohta T, Rak R, Rowley A, Chun HW, Jung SJ, Choi SP, Tsujii J, Ananiadou S. Overview of the Cancer Genetics and Pathway Curation tasks of BioNLP Shared Task 2013. BMC Bioinformatics 2015; 16 Suppl 10:S2. [PMID: 26202570 PMCID: PMC4511510 DOI: 10.1186/1471-2105-16-s10-s2] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Since their introduction in 2009, the BioNLP Shared Task events have been instrumental in advancing the development of methods and resources for the automatic extraction of information from the biomedical literature. In this paper, we present the Cancer Genetics (CG) and Pathway Curation (PC) tasks, two event extraction tasks introduced in the BioNLP Shared Task 2013. The CG task focuses on cancer, emphasizing the extraction of physiological and pathological processes at various levels of biological organization, and the PC task targets reactions relevant to the development of biomolecular pathway models, defining its extraction targets on the basis of established pathway representations and ontologies. RESULTS Six groups participated in the CG task and two groups in the PC task, together applying a wide range of extraction approaches including both established state-of-the-art systems and newly introduced extraction methods. The best-performing systems achieved F-scores of 55% on the CG task and 53% on the PC task, demonstrating a level of performance comparable to the best results achieved in similar previously proposed tasks. CONCLUSIONS The results indicate that existing event extraction technology can generalize to meet the novel challenges represented by the CG and PC task settings, suggesting that extraction methods are capable of supporting the construction of knowledge bases on the molecular mechanisms of cancer and the curation of biomolecular pathway models. The CG and PC tasks continue as open challenges for all interested parties, with data, tools and resources available from the shared task homepage.
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Affiliation(s)
- Sampo Pyysalo
- Department of Information technology, University of Turku, Turku, Finland
| | | | - Rafal Rak
- National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK
| | - Andrew Rowley
- National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK
| | - Hong-Woo Chun
- Software Research Center, Korea Institute of Science and Technology Information (KISTI), Daejeon, South Korea
| | - Sung-Jae Jung
- Software Research Center, Korea Institute of Science and Technology Information (KISTI), Daejeon, South Korea
- Department of Applied Information Science, University of Science and Technology (UST), Daejeon, South Korea
| | - Sung-Pil Choi
- Department of Library and Information Science, Kyonggi University, Suwon, South Korea
| | | | - Sophia Ananiadou
- National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK
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22
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Cuba CE, Valle AR, Ayala-Charca G, Villota ER, Coronado AM. Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models. SYSTEMS AND SYNTHETIC BIOLOGY 2015; 9:77-84. [PMID: 26279702 DOI: 10.1007/s11693-015-9173-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2015] [Revised: 05/16/2015] [Accepted: 05/30/2015] [Indexed: 10/23/2022]
Abstract
Biomolecular networks that present oscillatory behavior are ubiquitous in nature. While some design principles for robust oscillations have been identified, it is not well understood how these oscillations are affected when the kinetic parameters are constantly changing or are not precisely known, as often occurs in cellular environments. Many models of diverse complexity level, for systems such as circadian rhythms, cell cycle or the p53 network, have been proposed. Here we assess the influence of hundreds of different parameter sets on the sensitivities of two configurations of a well-known oscillatory system, the p53 core network. We show that, for both models and all parameter sets, the parameter related to the p53 positive feedback, i.e. self-promotion, is the only one that presents sizeable sensitivities on extrema, periods and delay. Moreover, varying the parameter set values to change the dynamical characteristics of the response is more restricted in the simple model, whereas the complex model shows greater tunability. These results highlight the importance of the presence of specific network patterns, in addition to the role of parameter values, when we want to characterize oscillatory biochemical systems.
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Affiliation(s)
- Christian E Cuba
- Faculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru
| | - Alexander R Valle
- Faculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru
| | - Giancarlo Ayala-Charca
- Faculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru
| | - Elizabeth R Villota
- Faculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru
| | - Alberto M Coronado
- Faculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru
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23
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Abstract
We define a measure of coherent activity for gene regulatory networks, a property that reflects the unity of purpose between the regulatory agents with a common target. We propose that such harmonious regulatory action is desirable under a demand for energy efficiency and may be selected for under evolutionary pressures. We consider two recent models of the cell-cycle regulatory network of the yeast, Saccharomyces cerevisiae as a case study and calculate their degree of coherence. A comparison with random networks of similar size and composition reveals that the yeast's cell-cycle regulation is wired to yield an exceptionally high level of coherent regulatory activity. We also investigate the mean degree of coherence as a function of the network size, connectivity and the fraction of repressory/activatory interactions.
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Affiliation(s)
- Neşe Aral
- Department of Physics, Koç University, Rumelifeneri Yolu Sarıyer 34450, Istanbul, Turkey
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24
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Spiesser TW, Kühn C, Krantz M, Klipp E. Bud-Localization of CLB2 mRNA Can Constitute a Growth Rate Dependent Daughter Sizer. PLoS Comput Biol 2015; 11:e1004223. [PMID: 25910075 PMCID: PMC4429581 DOI: 10.1371/journal.pcbi.1004223] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2014] [Accepted: 03/03/2015] [Indexed: 11/19/2022] Open
Abstract
Maintenance of cellular size is a fundamental systems level process that requires balancing of cell growth with proliferation. This is achieved via the cell division cycle, which is driven by the sequential accumulation and destruction of cyclins. The regulatory network around these cyclins, particularly in G1, has been interpreted as a size control network in budding yeast, and cell size as being decisive for the START transition. However, it is not clear why disruptions in the G1 network may lead to altered size rather than loss of size control, or why the S-G2-M duration also depends on nutrients. With a mathematical population model comprised of individually growing cells, we show that cyclin translation would suffice to explain the observed growth rate dependence of cell volume at START. Moreover, we assess the impact of the observed bud-localisation of the G2 cyclin CLB2 mRNA, and find that localised cyclin translation could provide an efficient mechanism for measuring the biosynthetic capacity in specific compartments: The mother in G1, and the growing bud in G2. Hence, iteration of the same principle can ensure that the mother cell is strong enough to grow a bud, and that the bud is strong enough for independent life. Cell sizes emerge in the model, which predicts that a single CDK-cyclin pair per growth phase suffices for size control in budding yeast, despite the necessity of the cell cycle network around the cyclins to integrate other cues. Size control seems to be exerted twice, where the G2/M control affects bud size through bud-localized translation of CLB2 mRNA, explaining the dependence of the S-G2-M duration on nutrients. Taken together, our findings suggest that cell size is an emergent rather than a regulatory property of the network linking growth and proliferation.
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Affiliation(s)
- Thomas W. Spiesser
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany
- * E-mail: (TWS); (EK)
| | - Clemens Kühn
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Marcus Krantz
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Edda Klipp
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany
- * E-mail: (TWS); (EK)
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25
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Ghosh S, Matsuoka Y, Asai Y, Hsin KY, Kitano H. Toward an integrated software platform for systems pharmacology. Biopharm Drug Dispos 2014; 34:508-26. [PMID: 24150748 PMCID: PMC4253131 DOI: 10.1002/bdd.1875] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2013] [Accepted: 10/06/2013] [Indexed: 01/19/2023]
Abstract
Understanding complex biological systems requires the extensive support of computational tools. This is particularly true for systems pharmacology, which aims to understand the action of drugs and their interactions in a systems context. Computational models play an important role as they can be viewed as an explicit representation of biological hypotheses to be tested. A series of software and data resources are used for model development, verification and exploration of the possible behaviors of biological systems using the model that may not be possible or not cost effective by experiments. Software platforms play a dominant role in creativity and productivity support and have transformed many industries, techniques that can be applied to biology as well. Establishing an integrated software platform will be the next important step in the field. © 2013 The Authors. Biopharmaceutics & Drug Disposition published by John Wiley & Sons, Ltd.
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Affiliation(s)
- Samik Ghosh
- The Systems Biology Institute5F Falcon Building, 5-6-9 Shirokanedai, Minato, Tokyo, 108-0071, Japan
- Disease Systems Modeling Laboratory, RIKEN Center for Integrative Medical Sciences1-7-22 Suehiro-Cho, Tsurumi, Yokohama, 230-0045, Japan
- * Correspondence to: The Systems Biology Institute, 5F Falcon Building, 5-6-9 Shirokanedai, Minato, Tokyo 108–0071 Japan., E-mail: ;
| | - Yukiko Matsuoka
- The Systems Biology Institute5F Falcon Building, 5-6-9 Shirokanedai, Minato, Tokyo, 108-0071, Japan
- JST ERATO Kawaoka Infection-induced Host Response Project4-6-1 Shirokanedai, Minato, Tokyo, 108-8639, Japan
| | - Yoshiyuki Asai
- Okinawa Institute of Science and Technology1919-1, Tancha, Onna-son, Kunigami, Okinawa, 904-0412, Japan
| | - Kun-Yi Hsin
- Okinawa Institute of Science and Technology1919-1, Tancha, Onna-son, Kunigami, Okinawa, 904-0412, Japan
| | - Hiroaki Kitano
- The Systems Biology Institute5F Falcon Building, 5-6-9 Shirokanedai, Minato, Tokyo, 108-0071, Japan
- Disease Systems Modeling Laboratory, RIKEN Center for Integrative Medical Sciences1-7-22 Suehiro-Cho, Tsurumi, Yokohama, 230-0045, Japan
- Okinawa Institute of Science and Technology1919-1, Tancha, Onna-son, Kunigami, Okinawa, 904-0412, Japan
- * Correspondence to: The Systems Biology Institute, 5F Falcon Building, 5-6-9 Shirokanedai, Minato, Tokyo 108–0071 Japan., E-mail: ;
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Weis MC, Avva J, Jacobberger JW, Sreenath SN. A data-driven, mathematical model of mammalian cell cycle regulation. PLoS One 2014; 9:e97130. [PMID: 24824602 PMCID: PMC4019653 DOI: 10.1371/journal.pone.0097130] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Accepted: 04/15/2014] [Indexed: 12/15/2022] Open
Abstract
Few of >150 published cell cycle modeling efforts use significant levels of data for tuning and validation. This reflects the difficultly to generate correlated quantitative data, and it points out a critical uncertainty in modeling efforts. To develop a data-driven model of cell cycle regulation, we used contiguous, dynamic measurements over two time scales (minutes and hours) calculated from static multiparametric cytometry data. The approach provided expression profiles of cyclin A2, cyclin B1, and phospho-S10-histone H3. The model was built by integrating and modifying two previously published models such that the model outputs for cyclins A and B fit cyclin expression measurements and the activation of B cyclin/Cdk1 coincided with phosphorylation of histone H3. The model depends on Cdh1-regulated cyclin degradation during G1, regulation of B cyclin/Cdk1 activity by cyclin A/Cdk via Wee1, and transcriptional control of the mitotic cyclins that reflects some of the current literature. We introduced autocatalytic transcription of E2F, E2F regulated transcription of cyclin B, Cdc20/Cdh1 mediated E2F degradation, enhanced transcription of mitotic cyclins during late S/early G2 phase, and the sustained synthesis of cyclin B during mitosis. These features produced a model with good correlation between state variable output and real measurements. Since the method of data generation is extensible, this model can be continually modified based on new correlated, quantitative data.
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Affiliation(s)
- Michael C. Weis
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Jayant Avva
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - James W. Jacobberger
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail:
| | - Sree N. Sreenath
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, United States of America
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Zhang Y, Smolen P, Baxter DA, Byrne JH. Computational analyses of synergism in small molecular network motifs. PLoS Comput Biol 2014; 10:e1003524. [PMID: 24651495 PMCID: PMC3961176 DOI: 10.1371/journal.pcbi.1003524] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Accepted: 02/06/2014] [Indexed: 12/21/2022] Open
Abstract
Cellular functions and responses to stimuli are controlled by complex regulatory networks that comprise a large diversity of molecular components and their interactions. However, achieving an intuitive understanding of the dynamical properties and responses to stimuli of these networks is hampered by their large scale and complexity. To address this issue, analyses of regulatory networks often focus on reduced models that depict distinct, reoccurring connectivity patterns referred to as motifs. Previous modeling studies have begun to characterize the dynamics of small motifs, and to describe ways in which variations in parameters affect their responses to stimuli. The present study investigates how variations in pairs of parameters affect responses in a series of ten common network motifs, identifying concurrent variations that act synergistically (or antagonistically) to alter the responses of the motifs to stimuli. Synergism (or antagonism) was quantified using degrees of nonlinear blending and additive synergism. Simulations identified concurrent variations that maximized synergism, and examined the ways in which it was affected by stimulus protocols and the architecture of a motif. Only a subset of architectures exhibited synergism following paired changes in parameters. The approach was then applied to a model describing interlocked feedback loops governing the synthesis of the CREB1 and CREB2 transcription factors. The effects of motifs on synergism for this biologically realistic model were consistent with those for the abstract models of single motifs. These results have implications for the rational design of combination drug therapies with the potential for synergistic interactions. Cellular responses to stimuli are controlled by complex regulatory networks that comprise many molecular components. Understanding such networks is critical for understanding normal cellular functions and pathological conditions. Because the complexity of these networks often precludes intuitive insights, a useful approach is to study mathematical models of small network motifs having reduced complexity yet consisting of key regulatory components of the more complex networks. Computational studies have analyzed the behavior of small motifs, and have begun to describe the ways in which variations in parameters affect their functional properties. Here, we investigated how variations in pairs of parameters act synergistically (or antagonistically) to alter responses of ten common network motifs. Simulations identified parameter variations that maximized synergism, and examined the ways in which synergism was affected by stimulus protocols and motif architecture. The results have implications for the rational design of combination drug therapies where a goal is to identify drugs that when administered together have a greater effect than would be predicted by simple addition of single-drug effects (i.e., super-additive effects), thereby allowing for lower drug doses, minimizing undesirable effects.
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Affiliation(s)
- Yili Zhang
- Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America
| | - Paul Smolen
- Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America
| | - Douglas A. Baxter
- Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America
| | - John H. Byrne
- Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America
- * E-mail:
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Wannige CT, Kulasiri D, Samarasinghe S. A nutrient dependant switch explains mutually exclusive existence of meiosis and mitosis initiation in budding yeast. J Theor Biol 2014; 341:88-101. [PMID: 24099720 DOI: 10.1016/j.jtbi.2013.09.030] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2013] [Accepted: 09/20/2013] [Indexed: 10/26/2022]
Abstract
Nutrients from living environment are vital for the survival and growth of any organism. Budding yeast diploid cells decide to grow by mitosis type cell division or decide to create unique, stress resistant spores by meiosis type cell division depending on the available nutrient conditions. To gain a molecular systems level understanding of the nutrient dependant switching between meiosis and mitosis initiation in diploid cells of budding yeast, we develop a theoretical model based on ordinary differential equations (ODEs) including the mitosis initiator and its relations to budding yeast meiosis initiation network. Our model accurately and qualitatively predicts the experimentally revealed temporal variations of related proteins under different nutrient conditions as well as the diverse mutant studies related to meiosis and mitosis initiation. Using this model, we show how the meiosis and mitosis initiators form an all-or-none type bistable switch in response to available nutrient level (mainly nitrogen). The transitions to and from meiosis or mitosis initiation states occur via saddle node bifurcation. This bidirectional switch helps the optimal usage of available nutrients and explains the mutually exclusive existence of meiosis and mitosis pathways.
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Affiliation(s)
- C T Wannige
- Centre for Advanced Computational Solutions (C-fACS), Department of Molecular Biosciences, Lincoln University, Christchurch, New Zealand
| | - D Kulasiri
- Centre for Advanced Computational Solutions (C-fACS), Department of Molecular Biosciences, Lincoln University, Christchurch, New Zealand.
| | - S Samarasinghe
- Centre for Advanced Computational Solutions (C-fACS), Department of Molecular Biosciences, Lincoln University, Christchurch, New Zealand
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Hasan MM, Brocca S, Sacco E, Spinelli M, Papaleo E, Lambrughi M, Alberghina L, Vanoni M. A comparative study of Whi5 and retinoblastoma proteins: from sequence and structure analysis to intracellular networks. Front Physiol 2014; 4:315. [PMID: 24478706 PMCID: PMC3897220 DOI: 10.3389/fphys.2013.00315] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2013] [Accepted: 10/13/2013] [Indexed: 11/18/2022] Open
Abstract
Cell growth and proliferation require a complex series of tight-regulated and well-orchestrated events. Accordingly, proteins governing such events are evolutionary conserved, even among distant organisms. By contrast, it is more singular the case of “core functions” exerted by functional analogous proteins that are not homologous and do not share any kind of structural similarity. This is the case of proteins regulating the G1/S transition in higher eukaryotes–i.e., the retinoblastoma (Rb) tumor suppressor Rb—and budding yeast, i.e., Whi5. The interaction landscape of Rb and Whi5 is quite large, with more than one hundred proteins interacting either genetically or physically with each protein. The Whi5 interactome has been used to construct a concept map of Whi5 function and regulation. Comparison of physical and genetic interactors of Rb and Whi5 allows highlighting a significant core of conserved, common functionalities associated with the interactors indicating that structure and function of the network—rather than individual proteins—are conserved during evolution. A combined bioinformatics and biochemical approach has shown that the whole Whi5 protein is highly disordered, except for a small region containing the protein family signature. The comparison with Whi5 homologs from Saccharomycetales has prompted the hypothesis of a modular organization of structural disorder, with most evolutionary conserved regions alternating with highly variable ones. The finding of a consensus sequence points to the conservation of a specific phosphorylation rhythm along with two disordered sequence motifs, probably acting as phosphorylation-dependent seeds in Whi5 folding/unfolding. Thus, the widely disordered Whi5 appears to act as a hierarchical, “date hub” that has evolutionary assayed an original way of modular organization before being supplanted by the globular, multi-domain structured Rb, more suitable to cover the role of a “party hub”.
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Affiliation(s)
- Md Mehedi Hasan
- SYSBIO Centre for Systems Biology Milano, Italy ; Department of Biotechnology and Biosciences, University of Milano-Bicocca Milano, Italy
| | - Stefania Brocca
- SYSBIO Centre for Systems Biology Milano, Italy ; Department of Biotechnology and Biosciences, University of Milano-Bicocca Milano, Italy
| | - Elena Sacco
- SYSBIO Centre for Systems Biology Milano, Italy ; Department of Biotechnology and Biosciences, University of Milano-Bicocca Milano, Italy
| | - Michela Spinelli
- SYSBIO Centre for Systems Biology Milano, Italy ; Department of Biotechnology and Biosciences, University of Milano-Bicocca Milano, Italy
| | - Elena Papaleo
- Department of Biotechnology and Biosciences, University of Milano-Bicocca Milano, Italy
| | - Matteo Lambrughi
- Department of Biotechnology and Biosciences, University of Milano-Bicocca Milano, Italy
| | - Lilia Alberghina
- SYSBIO Centre for Systems Biology Milano, Italy ; Department of Biotechnology and Biosciences, University of Milano-Bicocca Milano, Italy
| | - Marco Vanoni
- SYSBIO Centre for Systems Biology Milano, Italy ; Department of Biotechnology and Biosciences, University of Milano-Bicocca Milano, Italy
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Matsuoka Y, Funahashi A, Ghosh S, Kitano H. Modeling and simulation using CellDesigner. Methods Mol Biol 2014; 1164:121-45. [PMID: 24927840 DOI: 10.1007/978-1-4939-0805-9_11] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
In silico modeling and simulation are effective means to understand how the regulatory systems function in life. In this chapter, we explain how to build a model and run the simulation using CellDesigner, adopting the standards such as SBML and SBGN.
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Affiliation(s)
- Yukiko Matsuoka
- The Systems Biology Institute, 5-6-9 Shirokanedai, Minato-ku, Tokyo, 108-0071, Japan
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31
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Kriete A, Noguchi E, Sell C. Introductory review of computational cell cycle modeling. Methods Mol Biol 2014; 1170:267-75. [PMID: 24906317 DOI: 10.1007/978-1-4939-0888-2_12] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Recent advances in the modeling of the cell cycle through computer simulation demonstrate the power of systems biology. By definition, systems biology has the goal to connect a parts list, prioritized through experimental observation or high-throughput screens, by the topology of interactions defining intracellular networks to predict system function. Computer modeling of biological systems is often compared to a process of reverse engineering. Indeed, designed or engineered technical systems share many systems-level properties with biological systems; thus studying biological systems within an engineering framework has proven successful. Here we review some aspects of this process as it pertains to cell cycle modeling.
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Affiliation(s)
- Andres Kriete
- School of Biomedical Engineering, Science and Health Systems, Bossone Research Center, Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104, USA,
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Katzir Y, Elhanati Y, Averbukh I, Braun E. Dynamics of the cell-cycle network under genome-rewiring perturbations. Phys Biol 2013; 10:066001. [PMID: 24162518 DOI: 10.1088/1478-3975/10/6/066001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
The cell-cycle progression is regulated by a specific network enabling its ordered dynamics. Recent experiments supported by computational models have shown that a core of genes ensures this robust cycle dynamics. However, much less is known about the direct interaction of the cell-cycle regulators with genes outside of the cell-cycle network, in particular those of the metabolic system. Following our recent experimental work, we present here a model focusing on the dynamics of the cell-cycle core network under rewiring perturbations. Rewiring is achieved by placing an essential metabolic gene exclusively under the regulation of a cell-cycle's promoter, forcing the cell-cycle network to function under a multitasking challenging condition; operating in parallel the cell-cycle progression and a metabolic essential gene. Our model relies on simple rate equations that capture the dynamics of the relevant protein-DNA and protein-protein interactions, while making a clear distinction between these two different types of processes. In particular, we treat the cell-cycle transcription factors as limited 'resources' and focus on the redistribution of resources in the network during its dynamics. This elucidates the sensitivity of its various nodes to rewiring interactions. The basic model produces the correct cycle dynamics for a wide range of parameters. The simplicity of the model enables us to study the interface between the cell-cycle regulation and other cellular processes. Rewiring a promoter of the network to regulate a foreign gene, forces a multitasking regulatory load. The higher the load on the promoter, the longer is the cell-cycle period. Moreover, in agreement with our experimental results, the model shows that different nodes of the network exhibit variable susceptibilities to the rewiring perturbations. Our model suggests that the topology of the cell-cycle core network ensures its plasticity and flexible interface with other cellular processes, without a need for an optimal setting of the kinetic parameters.
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Affiliation(s)
- Yair Katzir
- Faculty of Medicine, Technion, Haifa, Israel
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33
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Matsuoka Y, Matsumae H, Katoh M, Eisfeld AJ, Neumann G, Hase T, Ghosh S, Shoemaker JE, Lopes TJS, Watanabe T, Watanabe S, Fukuyama S, Kitano H, Kawaoka Y. A comprehensive map of the influenza A virus replication cycle. BMC SYSTEMS BIOLOGY 2013; 7:97. [PMID: 24088197 PMCID: PMC3819658 DOI: 10.1186/1752-0509-7-97] [Citation(s) in RCA: 81] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Accepted: 09/24/2013] [Indexed: 02/05/2023]
Abstract
Background Influenza is a common infectious disease caused by influenza viruses. Annual epidemics cause severe illnesses, deaths, and economic loss around the world. To better defend against influenza viral infection, it is essential to understand its mechanisms and associated host responses. Many studies have been conducted to elucidate these mechanisms, however, the overall picture remains incompletely understood. A systematic understanding of influenza viral infection in host cells is needed to facilitate the identification of influential host response mechanisms and potential drug targets. Description We constructed a comprehensive map of the influenza A virus (‘IAV’) life cycle (‘FluMap’) by undertaking a literature-based, manual curation approach. Based on information obtained from publicly available pathway databases, updated with literature-based information and input from expert virologists and immunologists, FluMap is currently composed of 960 factors (i.e., proteins, mRNAs etc.) and 456 reactions, and is annotated with ~500 papers and curation comments. In addition to detailing the type of molecular interactions, isolate/strain specific data are also available. The FluMap was built with the pathway editor CellDesigner in standard SBML (Systems Biology Markup Language) format and visualized as an SBGN (Systems Biology Graphical Notation) diagram. It is also available as a web service (online map) based on the iPathways+ system to enable community discussion by influenza researchers. We also demonstrate computational network analyses to identify targets using the FluMap. Conclusion The FluMap is a comprehensive pathway map that can serve as a graphically presented knowledge-base and as a platform to analyze functional interactions between IAV and host factors. Publicly available webtools will allow continuous updating to ensure the most reliable representation of the host-virus interaction network. The FluMap is available at http://www.influenza-x.org/flumap/.
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Affiliation(s)
- Yukiko Matsuoka
- JST ERATO Kawaoka infection-induced host responses project, Minato-ku, Tokyo 108-8639, Japan.
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Rother M, Münzner U, Thieme S, Krantz M. Information content and scalability in signal transduction network reconstruction formats. MOLECULAR BIOSYSTEMS 2013; 9:1993-2004. [PMID: 23636168 DOI: 10.1039/c3mb00005b] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
One of the first steps towards holistic understanding of cellular networks is the integration of the available information in a human and machine readable format. This network reconstruction process is well established for metabolic networks, and numerous genome wide metabolic reconstructions are already available. Extending these strategies to signalling networks has proven difficult, primarily due to the combinatorial nature of regulatory modifications. The combinatorial nature of possible protein-protein interactions and post translational modifications affects both network size and the correspondence between the reconstructed network and the underlying empirical data. Here, we discuss different approaches to reconstruction of signal transduction networks. We divide the current approaches into topological, specific state based and reaction-contingency based, and discuss their different information content and scalability. The discussion focusses on graphical formats but the points are in general applicable also to mathematical models and databases. While the formats have complementary strengths especially for small networks, reaction-contingency based formats have a number of advantages in the light of global network reconstruction. In particular, they minimise the need for assumptions, maximise the congruence with empirical data, and scale efficiently with network size.
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Affiliation(s)
- Magdalena Rother
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
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35
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Gupta MK, Misra K. Modeling and simulation analysis of propyl-thiouracil (PTU), an anti-thyroid drug on thyroid peroxidase (TPO), thyroid stimulating hormone receptor (TSHR), and sodium iodide (NIS) symporter based on systems biology approach. ACTA ACUST UNITED AC 2013. [DOI: 10.1007/s13721-013-0023-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Spiesser TW, Müller C, Schreiber G, Krantz M, Klipp E. Size homeostasis can be intrinsic to growing cell populations and explained without size sensing or signalling. FEBS J 2012; 279:4213-30. [PMID: 23013467 DOI: 10.1111/febs.12014] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2012] [Revised: 09/12/2012] [Accepted: 09/20/2012] [Indexed: 12/19/2022]
Abstract
The cell division cycle orchestrates cellular growth and division. The machinery underpinning the cell division cycle is well characterized, but the actual cue(s) driving the cell division cycle remains unknown. In rapidly growing and dividing yeast cells, this cue has been proposed to be cell size. Presumably, a mechanism communicating cell size acts as gatekeeper for the cell division cycle via the G(1) network, which triggers G(1) exit only when a critical size has been reached. Here, we evaluate this hypothesis with a minimal core model linking metabolism, growth and the cell division cycle. Using this model, we (a) present support for coordinated regulation of G(1)/S and G(2)/M transition in Saccharomyces cerevisiae in response to altered growth conditions, (b) illustrate the intrinsic antagonism between G(1) progression and cell size and (c) provide evidence that the coupling of growth and division is sufficient to allow for size homeostasis without directly communicating or measuring cell size. We show that even with a rudimentary version of the G(1) network consisting of a single unregulated cyclin, size homeostasis is maintained in populations during autocatalytic growth when the geometric constraint on nutrient supply is considered. Taken together, our results support the notion that cell size is a consequence rather than a regulator of growth and division.
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Kim D, Kim MS, Cho KH. The core regulation module of stress-responsive regulatory networks in yeast. Nucleic Acids Res 2012; 40:8793-802. [PMID: 22784859 PMCID: PMC3467048 DOI: 10.1093/nar/gks649] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2012] [Revised: 05/22/2012] [Accepted: 06/11/2012] [Indexed: 01/23/2023] Open
Abstract
How does a cell respond to numerous external stresses with a limited number of internal molecular components? It has been observed that there are some common responses of yeast to various stresses, but most observations were based on gene-expression profiles and only some part of the common responses were intensively investigated. So far there has been no system-level analysis to identify commonly responsive or regulated genes against various stresses. In this study, we identified a core regulation module (CRM), a commonly involved regulation structure in the regulatory networks of yeast, which cells reuse in response to an array of environmental stresses. We found that regulators in the CRM constitute a hierarchical backbone of the yeast regulatory network and that the CRM is evolutionarily well conserved, stable against genetic variations and crucial for cell growth. All these findings were consistently held up to considerable noise levels that we introduced to address experimental noise and the resulting false positives of regulatory interactions. We conclude that the CRM of yeast might be an evolutionarily conserved information processing unit that endows a cell with enhanced robustness and efficiency in dealing with numerous environmental stresses with a limited number of internal elements.
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Affiliation(s)
| | | | - Kwang-Hyun Cho
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea
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Abstract
It has been suggested that irreducible sets of states in Probabilistic Boolean Networks correspond to cellular phenotype. In this study, we identify such sets of states for each phase of the budding yeast cell cycle. We find that these “ergodic sets” underly the cyclin activity levels during each phase of the cell cycle. Our results compare to the observations made in several laboratory experiments as well as the results of differential equation models. Dynamical studies of this model: (i) indicate that under stochastic external signals the continuous oscillating waves of cyclin activity and the opposing waves of CKIs emerge from the logic of a Boolean-based regulatory network without the need for specific biochemical/kinetic parameters; (ii) suggest that the yeast cell cycle network is robust to the varying behavior of cell size (e.g., cell division under nitrogen deprived conditions); (iii) suggest the irreversibility of the Start signal is a function of logic of the G1 regulon, and changing the structure of the regulatory network can render start reversible.
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Alberghina L, Gaglio D, Gelfi C, Moresco RM, Mauri G, Bertolazzi P, Messa C, Gilardi MC, Chiaradonna F, Vanoni M. Cancer cell growth and survival as a system-level property sustained by enhanced glycolysis and mitochondrial metabolic remodeling. Front Physiol 2012; 3:362. [PMID: 22988443 PMCID: PMC3440026 DOI: 10.3389/fphys.2012.00362] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2012] [Accepted: 08/23/2012] [Indexed: 12/14/2022] Open
Abstract
Systems Biology holds that complex cellular functions are generated as system-level properties endowed with robustness, each involving large networks of molecular determinants, generally identified by “omics” analyses. In this paper we describe four basic cancer cell properties that can easily be investigated in vitro: enhanced proliferation, evasion from apoptosis, genomic instability, and inability to undergo oncogene-induced senescence. Focusing our analysis on a K-ras dependent transformation system, we show that enhanced proliferation and evasion from apoptosis are closely linked, and present findings that indicate how a large metabolic remodeling sustains the enhanced growth ability. Network analysis of transcriptional profiling gives the first indication on this remodeling, further supported by biochemical investigations and metabolic flux analysis (MFA). Enhanced glycolysis, down-regulation of TCA cycle, decoupling of glucose and glutamine utilization, with increased reductive carboxylation of glutamine, so to yield a sustained production of growth building blocks and glutathione, are the hallmarks of enhanced proliferation. Low glucose availability specifically induces cell death in K-ras transformed cells, while PKA activation reverts this effect, possibly through at least two mitochondrial targets. The central role of mitochondria in determining the two investigated cancer cell properties is finally discussed. Taken together the findings reported herein indicate that a system-level property is sustained by a cascade of interconnected biochemical pathways that behave differently in normal and in transformed cells.
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Affiliation(s)
- Lilia Alberghina
- SysBio Centre for Systems Biology Milano and Rome, Italy ; Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza Milano, Italy
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Integration of cellular signals in chattering environments. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2012; 110:106-12. [DOI: 10.1016/j.pbiomolbio.2012.05.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2011] [Revised: 05/04/2012] [Accepted: 05/05/2012] [Indexed: 01/11/2023]
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A framework for mapping, visualisation and automatic model creation of signal-transduction networks. Mol Syst Biol 2012; 8:578. [PMID: 22531118 PMCID: PMC3361003 DOI: 10.1038/msb.2012.12] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
An intuitive formalism for reconstructing cellular networks from empirical data is presented, and used to build a comprehensive yeast MAP kinase network. The accompanying rxncon software tool can convert networks to a range of standard graphical formats and mathematical models. ![]()
Network mapping at the granularity of empirical data that largely avoids combinatorial complexity Automatic visualisation and model generation with the rxncon open source software tool Visualisation in a range of formats, including all three SBGN formats, as well as contingency matrix or regulatory graph Comprehensive and completely references map of the yeast MAP kinase network in the rxncon format
Intracellular signalling systems are highly complex. This complexity makes handling, analysis and visualisation of available knowledge a major challenge in current signalling research. Here, we present a novel framework for mapping signal-transduction networks that avoids the combinatorial explosion by breaking down the network in reaction and contingency information. It provides two new visualisation methods and automatic export to mathematical models. We use this framework to compile the presently most comprehensive map of the yeast MAP kinase network. Our method improves previous strategies by combining (I) more concise mapping adapted to empirical data, (II) individual referencing for each piece of information, (III) visualisation without simplifications or added uncertainty, (IV) automatic visualisation in multiple formats, (V) automatic export to mathematical models and (VI) compatibility with established formats. The framework is supported by an open source software tool that facilitates integration of the three levels of network analysis: definition, visualisation and mathematical modelling. The framework is species independent and we expect that it will have wider impact in signalling research on any system.
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Huard J, Mueller S, Gilles ED, Klingmüller U, Klamt S. An integrative model links multiple inputs and signaling pathways to the onset of DNA synthesis in hepatocytes. FEBS J 2012; 279:3290-313. [PMID: 22443451 PMCID: PMC3466406 DOI: 10.1111/j.1742-4658.2012.08572.x] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
During liver regeneration, quiescent hepatocytes re-enter the cell cycle to proliferate and compensate for lost tissue. Multiple signals including hepatocyte growth factor, epidermal growth factor, tumor necrosis factor α, interleukin-6, insulin and transforming growth factor β orchestrate these responses and are integrated during the G1 phase of the cell cycle. To investigate how these inputs influence DNA synthesis as a measure for proliferation, we established a large-scale integrated logical model connecting multiple signaling pathways and the cell cycle. We constructed our model based upon established literature knowledge, and successively improved and validated its structure using hepatocyte-specific literature as well as experimental DNA synthesis data. Model analyses showed that activation of the mitogen-activated protein kinase and phosphatidylinositol 3-kinase pathways was sufficient and necessary for triggering DNA synthesis. In addition, we identified key species in these pathways that mediate DNA replication. Our model predicted oncogenic mutations that were compared with the COSMIC database, and proposed intervention targets to block hepatocyte growth factor-induced DNA synthesis, which we validated experimentally. Our integrative approach demonstrates that, despite the complexity and size of the underlying interlaced network, logical modeling enables an integrative understanding of signaling-controlled proliferation at the cellular level, and thus can provide intervention strategies for distinct perturbation scenarios at various regulatory levels.
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Affiliation(s)
- Jérémy Huard
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
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Abstract
Communication is essential. It is vital between cells in multi-cellular organisms, and within cells. A signaling molecule binds to a receptor protein, and initiates a cascade of dynamic events. Signaling is a multistep pathway, which allows signal amplification: if some of the molecules in a pathway transmit the signal to multiple molecules, the result can be a large number of activated molecules across the cell and multiple reactions. That is how a small number of extracellular signaling molecules can produce a major cellular response. The pathway can relay signals from the extracellular space to the nucleus. How do signals travel efficiently over long-distances across the cell? Here we argue that evolution has utilized three properties: a modular functional organization of the cellular network; sequences in some key regions of proteins, such as linkers or loops, which were pre-encoded by evolution to facilitate signaling among domains; and compact interactions between proteins which is achieved via conformational disorder.
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Affiliation(s)
- Ruth Nussinov
- Basic Research Program, SAIC-Frederick, Inc., Center for Cancer Research Nanobiology Program, NCI-Frederick, Frederick, MD 21702, USA.
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Domedel-Puig N, Rué P, Pons AJ, García-Ojalvo J. Information routing driven by background chatter in a signaling network. PLoS Comput Biol 2011; 7:e1002297. [PMID: 22174668 PMCID: PMC3234210 DOI: 10.1371/journal.pcbi.1002297] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2011] [Accepted: 10/25/2011] [Indexed: 11/18/2022] Open
Abstract
Living systems are capable of processing multiple sources of information simultaneously. This is true even at the cellular level, where not only coexisting signals stimulate the cell, but also the presence of fluctuating conditions is significant. When information is received by a cell signaling network via one specific input, the existence of other stimuli can provide a background activity –or chatter– that may affect signal transmission through the network and, therefore, the response of the cell. Here we study the modulation of information processing by chatter in the signaling network of a human cell, specifically, in a Boolean model of the signal transduction network of a fibroblast. We observe that the level of external chatter shapes the response of the system to information carrying signals in a nontrivial manner, modulates the activity levels of the network outputs, and effectively determines the paths of information flow. Our results show that the interactions and node dynamics, far from being random, confer versatility to the signaling network and allow transitions between different information-processing scenarios. Far from being silent and static, the habitat of a cell is usually composed by multiple and simultaneous signals. We can consider nutrients, hormones, temperature, light, and other stimuli as elements building a default environment in which cells grow, divide and die. This environment, which has an intrinsically fluctuating nature, is the setting in which cells process all incoming stimuli. Here we examine the role that this background activity –or signaling chatter– plays in the transmission of information in a typical human cell. We address this question using a cellular model of signal transduction that we simulate using both random and periodic stimuli. We find that the level of background chatter determines the response of the whole signaling network to external stimuli. Different areas of the network are activated by specific levels of background activity, routing the information through chatter-dependent paths. In this way, different levels of chatter allow the network to select between different responses, given the same stimulus. These features depend on the architecture and functional connectivity of a truly biological network, since we find that randomized versions of the model are incapable of showing this behavior.
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Affiliation(s)
- Núria Domedel-Puig
- Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Terrassa, Barcelona, Spain
| | - Pau Rué
- Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Terrassa, Barcelona, Spain
| | - Antonio J. Pons
- Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Terrassa, Barcelona, Spain
| | - Jordi García-Ojalvo
- Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Terrassa, Barcelona, Spain
- * E-mail:
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Loewith R, Hall MN. Target of rapamycin (TOR) in nutrient signaling and growth control. Genetics 2011; 189:1177-201. [PMID: 22174183 PMCID: PMC3241408 DOI: 10.1534/genetics.111.133363] [Citation(s) in RCA: 642] [Impact Index Per Article: 49.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2011] [Accepted: 09/12/2011] [Indexed: 12/16/2022] Open
Abstract
TOR (Target Of Rapamycin) is a highly conserved protein kinase that is important in both fundamental and clinical biology. In fundamental biology, TOR is a nutrient-sensitive, central controller of cell growth and aging. In clinical biology, TOR is implicated in many diseases and is the target of the drug rapamycin used in three different therapeutic areas. The yeast Saccharomyces cerevisiae has played a prominent role in both the discovery of TOR and the elucidation of its function. Here we review the TOR signaling network in S. cerevisiae.
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Affiliation(s)
- Robbie Loewith
- Department of Molecular Biology and National Centers of Competence in Research and Frontiers in Genetics and Chemical Biology, University of Geneva, Geneva, CH-1211, Switzerland
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Abstract
Understanding complex biological systems requires extensive support from software tools. Such tools are needed at each step of a systems biology computational workflow, which typically consists of data handling, network inference, deep curation, dynamical simulation and model analysis. In addition, there are now efforts to develop integrated software platforms, so that tools that are used at different stages of the workflow and by different researchers can easily be used together. This Review describes the types of software tools that are required at different stages of systems biology research and the current options that are available for systems biology researchers. We also discuss the challenges and prospects for modelling the effects of genetic changes on physiology and the concept of an integrated platform.
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Waltermann C, Klipp E. Information theory based approaches to cellular signaling. Biochim Biophys Acta Gen Subj 2011; 1810:924-32. [PMID: 21798319 DOI: 10.1016/j.bbagen.2011.07.009] [Citation(s) in RCA: 77] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2010] [Revised: 06/08/2011] [Accepted: 07/13/2011] [Indexed: 01/26/2023]
Abstract
BACKGROUND Cells interact with their environment and they have to react adequately to internal and external changes such changes in nutrient composition, physical properties like temperature or osmolarity and other stresses. More specifically, they must be able to evaluate whether the external change is significant or just in the range of noise. Based on multiple external parameters they have to compute an optimal response. Cellular signaling pathways are considered as the major means of information perception and transmission in cells. SCOPE OF REVIEW Here, we review different attempts to quantify information processing on the level of individual cells. We refer to Shannon entropy, mutual information, and informal measures of signaling pathway cross-talk and specificity. MAJOR CONCLUSIONS Information theory in systems biology has been successfully applied to identification of optimal pathway structures, mutual information and entropy as system response in sensitivity analysis, and quantification of input and output information. GENERAL SIGNIFICANCE While the study of information transmission within the framework of information theory in technical systems is an advanced field with high impact in engineering and telecommunication, its application to biological objects and processes is still restricted to specific fields such as neuroscience, structural and molecular biology. However, in systems biology dealing with a holistic understanding of biochemical systems and cellular signaling only recently a number of examples for the application of information theory have emerged. This article is part of a Special Issue entitled Systems Biology of Microorganisms.
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Alberghina L, Mavelli G, Drovandi G, Palumbo P, Pessina S, Tripodi F, Coccetti P, Vanoni M. Cell growth and cell cycle in Saccharomyces cerevisiae: basic regulatory design and protein-protein interaction network. Biotechnol Adv 2011; 30:52-72. [PMID: 21821114 DOI: 10.1016/j.biotechadv.2011.07.010] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2011] [Revised: 06/23/2011] [Accepted: 07/06/2011] [Indexed: 10/18/2022]
Abstract
In this review we summarize the major connections between cell growth and cell cycle in the model eukaryote Saccharomyces cerevisiae. In S. cerevisiae regulation of cell cycle progression is achieved predominantly during a narrow interval in the late G1 phase known as START (Pringle and Hartwell, 1981). At START a yeast cell integrates environmental and internal signals (such as nutrient availability, presence of pheromone, attainment of a critical size, status of the metabolic machinery) and decides whether to enter a new cell cycle or to undertake an alternative developmental program. Several signaling pathways, that act to connect the nutritional status to cellular actions, are briefly outlined. A Growth & Cycle interaction network has been manually curated. More than one fifth of the edges within the Growth & Cycle network connect Growth and Cycle proteins, indicating a strong interconnection between the processes of cell growth and cell cycle. The backbone of the Growth & Cycle network is composed of middle-degree nodes suggesting that it shares some properties with HOT networks. The development of multi-scale modeling and simulation analysis will help to elucidate relevant central features of growth and cycle as well as to identify their system-level properties. Confident collaborative efforts involving different expertises will allow to construct consensus, integrated models effectively linking the processes of cell growth and cell cycle, ultimately contributing to shed more light also on diseases in which an altered proliferation ability is observed, such as cancer.
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Affiliation(s)
- Lilia Alberghina
- Dipartimento di Biotecnologie e Bioscienze, Università di Milano-Bicocca, Milano, Italy.
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Rietman EA, Colt JZ, Tuszynski JA. Interactomes, manufacturomes and relational biology: analogies between systems biology and manufacturing systems. Theor Biol Med Model 2011; 8:19. [PMID: 21689427 PMCID: PMC3145567 DOI: 10.1186/1742-4682-8-19] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2011] [Accepted: 06/20/2011] [Indexed: 11/18/2022] Open
Abstract
Background We review and extend the work of Rosen and Casti who discuss category theory with regards to systems biology and manufacturing systems, respectively. Results We describe anticipatory systems, or long-range feed-forward chemical reaction chains, and compare them to open-loop manufacturing processes. We then close the loop by discussing metabolism-repair systems and describe the rationality of the self-referential equation f = f (f). This relationship is derived from some boundary conditions that, in molecular systems biology, can be stated as the cardinality of the following molecular sets must be about equal: metabolome, genome, proteome. We show that this conjecture is not likely correct so the problem of self-referential mappings for describing the boundary between living and nonliving systems remains an open question. We calculate a lower and upper bound for the number of edges in the molecular interaction network (the interactome) for two cellular organisms and for two manufacturomes for CMOS integrated circuit manufacturing. Conclusions We show that the relevant mapping relations may not be Abelian, and that these problems cannot yet be resolved because the interactomes and manufacturomes are incomplete.
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Affiliation(s)
- Edward A Rietman
- Center for Cancer Systems Biology, Dana Farber Cancer Institute, Boston, MA 02115, USA
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