Feedback dynamics and cell function: Why systems biology is called Systems Biology

Wolkenhauer, Olaf; Mesarović, Mihajlo D.

doi:10.1039/b502088n

Cited by 86 publications

(65 citation statements)

References 3 publications

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“…A standard approach to the dynamics of cell signalling networks is the framework of chemical kinetics. Within this framework enzyme kinetic reaction (1) is represented as a system of four coupled ordinary differential equations [11,22] …”

Section: Assumptions Of the Studymentioning

confidence: 99%

Approximations and their consequences for dynamic modelling of signal transduction pathways

Millat

Bullinger

Rohwer

et al. 2007

Mathematical Biosciences

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This version is available at https://strathprints.strath.ac.uk/11996/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Signal transduction is the process by which the cell converts one kind of signal or stimulus into another. This involves a sequence of biochemical reactions, carried out by proteins. The dynamic response of complex cell signalling networks can be modelled and simulated in the framework of chemical kinetics. The mathematical formulation of chemical kinetics results in a system of coupled differential equations. Simplifications can arise through assumptions and approximations. The paper provides a critical discussion of frequently employed approximations in dynamic modelling of signal transduction pathways. We discuss the requirements for conservation laws, steady state approximations, and the neglect of components. We show how these approximations simplify the mathematical treatment of biochemical networks but we also demonstrate differences between the complete system and its approximations with respect to the transient and steady state behavior. Approximations and their Consequences for Dynamic Modelling of Signal Transduction Pathways

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Section: Assumptions Of the Studymentioning

confidence: 99%

Approximations and their consequences for dynamic modelling of signal transduction pathways

Millat

Bullinger

Rohwer

et al. 2007

Mathematical Biosciences

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“…In this approach, the focus is on quantitative analysis of the interactions between individual components in a biological system and how these interactions evolve with time. A recurrent theme in this field is the importance of feedback loops in generating spatiotemporal patterns (5). Pioneering work in the study of oocyte maturation, for instance, has demonstrated the critical role of positive feedback in cell fate decision (6).…”

mentioning

confidence: 99%

Bistable switches control memory and plasticity in cellular differentiation

Wang

Walker

Iannaccone

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

112

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Development of stem and progenitor cells into specialized tissues in multicellular organisms involves a series of cell fate decisions. Cellular differentiation in higher organisms is generally considered irreversible, and the idea of developmental plasticity in postnatal tissues is controversial. Here, we show that inhibition of mitogenactivated protein kinase (MAPK) in a human bone marrow stromal cell-derived myogenic subclone suppresses their myogenic ability and converts them into satellite cell-like precursors that respond to osteogenic stimulation. Clonal analysis of the induced osteogenic response reveals ultrasensitivity and an ''all-or-none'' behavior, hallmarks of a bistable switch mechanism with stochastic noise. The response demonstrates cellular memory, which is contingent on the accumulation of an intracellular factor and can be erased by factor dilution through cell divisions or inhibition of protein synthesis. The effect of MAPK inhibition also exhibits memory and appears to be controlled by another bistable switch further upstream that determines cell fate. Once the memory associated with osteogenic differentiation is erased, the cells regain their myogenic ability. These results support a model of cell fate decision in which a network of bistable switches controls inducible production of lineage-specific differentiation factors. A competitive balance between these factors determines cell fate. Our work underscores the dynamic nature of cellular differentiation and explains mechanistically the dual properties of stability and plasticity associated with the process.bistability ͉ MAPK signaling ͉ mesenchymal progenitors ͉ myogenic differentiation ͉ osteogenic differentiation I n multicellular organisms, differentiated cells perform a wide range of specialized functions. Understanding how multipotent stem and progenitor cells develop into these differentiated cells is a central question in biology. Cellular differentiation is assumed to involve a series of cell fate decisions, each of which is generally considered irreversible in higher organisms. The irreversibility in differentiation contributes to phenotypic stability of the specialized cells, which enable them to perform their respective functions (1). Recent reports have demonstrated that differentiated cells can also exhibit an extraordinary degree of developmental plasticity. Transfer of specific pluripotency genes into somatic cells, for example, can convert them into stem cell-like cells that can differentiate into diverse tissues (2). It remains controversial whether plasticity occurs in postnatal tissues of higher organisms in a physiological context (3). It is likely that cellular differentiation possesses the dual properties of stability and plasticity, and either might predominate, depending on the environmental milieu.In recent years, the application of the systems-biology approach in biological studies has been extraordinarily fruitful (4). In this approach, the focus is on quantitative analysis of the interactions between individual...

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“…Such regulatory networks often have downstream components that provide input to components that act earlier in a pathway, creating feedback loops (Langlois et al 1995) These feedback loops have the potential to greatly alter the properties of a pathway and how it responds to stimuli (Aronson et al 1994;Bliss et al 1982;Chen and Tan 2000;Lauffenburger 2001;Wolkenhauer and Mesarovic 2005). Positive and negative feedback loops around MAPK (Mitogenactivated protein kinase) cascades have been a topic of interest in biological literature.…”

Section: Introductionmentioning

confidence: 99%

“…For example, in (Ferrell and Machleder 1998), one finds the study of positive feedback (on Mos by ERK) in the context of progesterone-induced oocyte maturation in frogs. In another example, Kholodenko (2000) and Wolkenhauer and Mesarovic (2005) looked at negative feedback, also in an ERK cascade, but affecting upstream proteins. JNK activation is an autocatalytic, in his work Bagowski and Ferrell (2001) has proposed two possible feedbacks, one from MAPK to MAPKK (Mitogen-activated protein kinase kinase) and the other from MAPKK to MAP-KKK(Mitogen-activated protein kinase kinase kinase) in JNK cascade in xenopus oocytes.…”

Section: Introductionmentioning

confidence: 99%

Lose and gain: impacts of ERK5 and JNK cascades on each other

Pandurangan

Gakkhar

2010

Syst Synth Biol

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Kinase cascades in ERK5 (Extracellular signalregulated kinases) and JNK (c-Jun N-terminal kinases) signaling pathways mediate the sensing and processing of stimuli. Cross-talks between signaling cascades is a likely phenomenon that can cause apparently different biological responses from a single pathway, on its activation. Feedback loops have the potential to greatly alter the properties of a pathway and its response to stimuli. Based on enzyme kinetic reactions, mathematical models have been developed to predict and analyze the impacts of cross-talks and feedback loops in ERK5 and JNK cascades. It has been observed that, there is no significant impact on neither ERK5 activation nor JNKs' activation due to cross-talks between them. But it is due to cross-talks and feedback loops in ERK5 and JNK cascade, ERK5 gets activated in a transient manner in the absence of input signals. Planning to obtain the parameter values from the experimentalist and the result should be validated by experimental verification.

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Feedback dynamics and cell function: Why systems biology is called Systems Biology

Cited by 86 publications

References 3 publications

Approximations and their consequences for dynamic modelling of signal transduction pathways

Approximations and their consequences for dynamic modelling of signal transduction pathways

Bistable switches control memory and plasticity in cellular differentiation

Lose and gain: impacts of ERK5 and JNK cascades on each other

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