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Xiao Y, Lv H, Wang X. Implementation of an Ultrasensitive Biomolecular Controller for Enzymatic Reaction Processes With Delay Using DNA Strand Displacement. IEEE Trans Nanobioscience 2023; 22:967-977. [PMID: 37159315 DOI: 10.1109/tnb.2023.3274573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
In this article, a set of abstract chemical reactions has been employed to construct a novel nonlinear biomolecular controller, i.e, the Brink controller (BC) with direct positive autoregulation (DPAR) (namely BC-DPAR controller). In comparison to dual rail representation-based controllers such as the quasi sliding mode (QSM) controller, the BC-DPAR controller directly reduces the number of CRNs required for realizing an ultrasensitive input-output response because it does not involve the subtraction module, reducing the complexity of DNA implementations. Then, the action mechanism and steady-state condition constraints of two nonlinear controllers, BC-DPAR controller and QSM controller, are investigated further. Considering the mapping relationship between CRNs and DNA implementation, a CRNs-based enzymatic reaction process with delay is constructed, and a DNA strand displacement (DSD) scheme representing time delay is proposed. The BC-DPAR controller, when compared to the QSM controller, can reduce the number of abstract chemical reactions and DSD reactions required by 33.3% and 31.8%, respectively. Finally, an enzymatic reaction scheme with BC-DPAR controller is designed using DSD reactions. According to the findings, the enzymatic reaction process's output substance can approach the target level at a quasi-steady state in both delay-free and non-zero delay conditions, but the target level can only be achieved during a finite-time period, mainly due to the fuel stand depletion.
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2
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Ponsiglione AM, Montefusco F, Donisi L, Tedesco A, Cosentino C, Merola A, Romano M, Amato F. A General Approach for the Modelling of Negative Feedback Physiological Control Systems. Bioengineering (Basel) 2023; 10:835. [PMID: 37508862 PMCID: PMC10376068 DOI: 10.3390/bioengineering10070835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/23/2023] [Accepted: 07/12/2023] [Indexed: 07/30/2023] Open
Abstract
Mathematical models can improve the understanding of physiological systems behaviour, which is a fundamental topic in the bioengineering field. Having a reliable model enables researchers to carry out in silico experiments, which require less time and resources compared to their in vivo and in vitro counterparts. This work's objective is to capture the characteristics that a nonlinear dynamical mathematical model should exhibit, in order to describe physiological control systems at different scales. The similarities among various negative feedback physiological systems have been investigated and a unique general framework to describe them has been proposed. Within such a framework, both the existence and stability of equilibrium points are investigated. The model here introduced is based on a closed-loop topology, on which the homeostatic process is based. Finally, to validate the model, three paradigmatic examples of physiological control systems are illustrated and discussed: the ultrasensitivity mechanism for achieving homeostasis in biomolecular circuits, the blood glucose regulation, and the neuromuscular reflex arc (also referred to as muscle stretch reflex). The results show that, by a suitable choice of the modelling functions, the dynamic evolution of the systems under study can be described through the proposed general nonlinear model. Furthermore, the analysis of the equilibrium points and dynamics of the above-mentioned systems are consistent with the literature.
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Affiliation(s)
- Alfonso Maria Ponsiglione
- Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli, Italy
| | - Francesco Montefusco
- Dipartimento di Scienze Economiche, Giuridiche, Informatiche e Motorie, Università degli Studi di Napoli Parthenope, 80035 Nola, Italy
| | - Leandro Donisi
- Dipartimento di Scienze Mediche e Chirurgiche Avanzate, Università degli studi della Campania "Luigi Vanvitelli", P.zza L. Miraglia 2, 80138 Napoli, Italy
| | - Annarita Tedesco
- Dipartimento di Ingegneria per l'Innovazione, Universitá del Salento, 73100 Lecce, Italy
| | - Carlo Cosentino
- School of Computer and Biomedical Engineering, Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi Magna Græcia di Catanzaro, Campus di Germaneto "Salvatore Venuta", 88100 Catanzaro, Italy
| | - Alessio Merola
- School of Computer and Biomedical Engineering, Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi Magna Græcia di Catanzaro, Campus di Germaneto "Salvatore Venuta", 88100 Catanzaro, Italy
| | - Maria Romano
- Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli, Italy
| | - Francesco Amato
- Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli, Italy
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Akman OE, Doherty K, Wareham BJ. BDEtools: A MATLAB Package for Boolean Delay Equation Modeling. J Comput Biol 2023; 30:52-69. [PMID: 36099206 DOI: 10.1089/cmb.2021.0658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Boolean Delay Equations (BDEs) can simulate surprisingly complex behavior, despite their relative simplicity. In addition to steady-state dynamics, BDEs can also generate periodic and quasiperiodic oscillations, m:n frequency locking, and even chaos. Further, the enumerability of Boolean update functions and their compact parametrization means that BDEs can be leveraged to generate low-level descriptions of biological networks, from which more detailed formulations (e.g., differential equation models) can be constructed. However, although several studies have demonstrated the utility of BDE modeling in computational biology, a current barrier to the wider adoption of the BDE approach is the absence of freely available simulation software. In this work, we present BDEtools-an open-source MATLAB package for numerically solving BDE models. After giving a brief introduction to BDE modeling, we describe the package's solver algorithms, together with several utility functions that can be used to provide solver inputs and to process solver outputs. We also demonstrate the functionality of BDEtools by illustrating its application to an established model of a gene regulatory network that controls circadian rhythms. BDEtools makes it straightforward for researchers to quickly build reliable BDE models of biological networks. We hope that its ease of use and free availability will encourage more researchers to explore BDE formulations of their systems of interest. Through the continued use of BDEs by the computational biology community, we will, no doubt, discover their potential applicability to a broader class of biological networks.
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Affiliation(s)
- Ozgur E Akman
- Department of Mathematics, The University of Exeter, Exeter, United Kingdom
| | - Kevin Doherty
- Department of Mathematics, The University of Exeter, Exeter, United Kingdom
| | - Benjamin J Wareham
- Department of Mathematics, The University of Exeter, Exeter, United Kingdom
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4
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Sootla A, Delalez N, Alexis E, Norman A, Steel H, Wadhams GH, Papachristodoulou A. Dichotomous feedback: a signal sequestration-based feedback mechanism for biocontroller design. J R Soc Interface 2022; 19:20210737. [PMID: 35440202 PMCID: PMC9019519 DOI: 10.1098/rsif.2021.0737] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
We introduce a new design framework for implementing negative feedback regulation in synthetic biology, which we term ‘dichotomous feedback’. Our approach is different from current methods, in that it sequesters existing fluxes in the process to be controlled, and in this way takes advantage of the process’s architecture to design the control law. This signal sequestration mechanism appears in many natural biological systems and can potentially be easier to realize than ‘molecular sequestration’ and other comparison motifs that are nowadays common in biomolecular feedback control design. The loop is closed by linking the strength of signal sequestration to the process output. Our feedback regulation mechanism is motivated by two-component signalling systems, where a second response regulator could be competing with the natural response regulator thus sequestering kinase activity. Here, dichotomous feedback is established by increasing the concentration of the second response regulator as the level of the output of the natural process increases. Extensive analysis demonstrates how this type of feedback shapes the signal response, attenuates intrinsic noise while increasing robustness and reducing crosstalk.
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Affiliation(s)
- Aivar Sootla
- Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
| | - Nicolas Delalez
- Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
| | - Emmanouil Alexis
- Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
| | - Arthur Norman
- Department of Biochemistry, University of Oxford, Oxford OX1 3PJ, UK
| | - Harrison Steel
- Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
| | - George H Wadhams
- Department of Biochemistry, University of Oxford, Oxford OX1 3PJ, UK
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Hancock EJ, Oyarzún DA. Stabilization of antithetic control via molecular buffering. J R Soc Interface 2022; 19:20210762. [PMID: 35259958 PMCID: PMC8905164 DOI: 10.1098/rsif.2021.0762] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A key goal in synthetic biology is the construction of molecular circuits that robustly adapt to perturbations. Although many natural systems display perfect adaptation, whereby stationary molecular concentrations are insensitive to perturbations, its de novo engineering has proven elusive. The discovery of the antithetic control motif was a significant step towards a universal mechanism for engineering perfect adaptation. Antithetic control provides perfect adaptation in a wide range of systems, but it can lead to oscillatory dynamics due to loss of stability; moreover, it can lose perfect adaptation in fast growing cultures. Here, we introduce an extended antithetic control motif that resolves these limitations. We show that molecular buffering, a widely conserved mechanism for homeostatic control in Nature, stabilizes oscillations and allows for near-perfect adaptation during rapid growth. We study multiple buffering topologies and compare their performance in terms of their stability and adaptation properties. We illustrate the benefits of our proposed strategy in exemplar models for biofuel production and growth rate control in bacterial cultures. Our results provide an improved circuit for robust control of biomolecular systems.
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Affiliation(s)
- Edward J Hancock
- School of Mathematics and Statistics, The University of Sydney, New South Wales 2006, Australia.,Charles Perkins Centre, The University of Sydney, New South Wales 2006, Australia
| | - Diego A Oyarzún
- School of Informatics, The University of Edinburgh, Edinburgh, UK.,School of Biological Sciences, The University of Edinburgh, Edinburgh, UK.,The Alan Turing Institute, London, UK
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6
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Foo M, Akman OE, Bates DG. Restoring circadian gene profiles in clock networks using synthetic feedback control. NPJ Syst Biol Appl 2022; 8:7. [PMID: 35169147 PMCID: PMC8847486 DOI: 10.1038/s41540-022-00216-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 01/24/2022] [Indexed: 11/29/2022] Open
Abstract
The circadian system—an organism’s built-in biological clock—is responsible for orchestrating biological processes to adapt to diurnal and seasonal variations. Perturbations to the circadian system (e.g., pathogen attack, sudden environmental change) often result in pathophysiological responses (e.g., jetlag in humans, stunted growth in plants, etc.) In view of this, synthetic biologists are progressively adapting the idea of employing synthetic feedback control circuits to alleviate the effects of perturbations on circadian systems. To facilitate the design of such controllers, suitable models are required. Here, we extend our recently developed model for the plant circadian clock—termed the extended S-System model—to model circadian systems across different kingdoms of life. We then use this modeling strategy to develop a design framework, based on an antithetic integral feedback (AIF) controller, to restore a gene’s circadian profile when it is subject to loss-of-function due to external perturbations. The use of the AIF controller is motivated by its recent successful experimental implementation. Our findings provide circadian biologists with a systematic and general modeling and design approach for implementing synthetic feedback control of circadian systems.
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Affiliation(s)
- Mathias Foo
- School of Mechanical, Aerospace and Automotive Engineering, Coventry University, Coventry, CV1 5FB, UK.,School of Engineering, University of Warwick, Coventry, CV4 7AL, UK
| | - Ozgur E Akman
- College of Engineering, Mathematics and Physical Science, University of Exeter, Exeter, EX4 4QF, UK
| | - Declan G Bates
- Warwick Integrative Synthetic Biology Centre, School of Engineering, University of Warwick, Coventry, CV4 7AL, UK.
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Jeynes-Smith C, Araujo RP. Ultrasensitivity and bistability in covalent-modification cycles with positive autoregulation. Proc Math Phys Eng Sci 2021; 477:20210069. [PMID: 35153570 PMCID: PMC8331239 DOI: 10.1098/rspa.2021.0069] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 07/02/2021] [Indexed: 12/17/2022] Open
Abstract
Switch-like behaviours in biochemical networks are of fundamental significance in biological signal processing, and exist as two distinct types: ultra-sensitivity and bistability. Here we propose two new models of a reversible covalent-modification cycle with positive autoregulation (PAR), a motif structure that is thought to be capable of both ultrasensitivity and bistability in different parameter regimes. These new models appeal to a modelling framework that we call complex-complete, which accounts fully for the molecular complexities of the underlying signalling mechanisms. Each of the two new models encodes a specific molecular mechanism for PAR. We demonstrate that the modelling simplifications for PAR models that have been used in previous work, which rely on Michaelian approximations, are unable to accurately recapitulate the qualitative signalling responses supported by our detailed models. Strikingly, we show that complex-complete PAR models are capable of new qualitative responses such as one-way switches and a 'prozone' effect, depending on the specific PAR-encoding mechanism, which are not supported by Michaelian simplifications. Our results highlight the critical importance of accurately representing the molecular details of biochemical signalling mechanisms, and strongly suggest that the Michaelian approximation is inadequate for predictive models of enzyme-mediated chemical reactions with added regulations such as PAR.
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Affiliation(s)
- Cailan Jeynes-Smith
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
- Institute of Health and Biomedical Innovation (IHBI), Brisbane, Australia
| | - Robyn P. Araujo
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
- Institute of Health and Biomedical Innovation (IHBI), Brisbane, Australia
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8
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Cuba Samaniego C, Franco E. Ultrasensitive molecular controllers for quasi-integral feedback. Cell Syst 2021; 12:272-288.e3. [PMID: 33539724 DOI: 10.1016/j.cels.2021.01.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 09/22/2020] [Accepted: 01/11/2021] [Indexed: 12/24/2022]
Abstract
Feedback control has enabled the success of automated technologies by mitigating the effects of variability, unknown disturbances, and noise. While it is known that biological feedback loops reduce the impact of noise and help shape kinetic responses, many questions remain about how to design molecular integral controllers. Here, we propose a modular strategy to build molecular quasi-integral feedback controllers, which involves following two design principles. The first principle is to utilize an ultrasensitive response, which determines the gain of the controller and influences the steady-state error. The second is to use a tunable threshold of the ultrasensitive response, which determines the equilibrium point of the system. We describe a reaction network, named brink controller, that satisfies these conditions by combining molecular sequestration and an activation/deactivation cycle. With computational models, we examine potential biological implementations of brink controllers, and we illustrate different example applications.
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Affiliation(s)
- Christian Cuba Samaniego
- Mechanical and Aerospace Engineering, University of California at Los Angeles, Los Angeles, CA 90095, USA
| | - Elisa Franco
- Mechanical and Aerospace Engineering, University of California at Los Angeles, Los Angeles, CA 90095, USA; Molecular Biology Institute, University of California at Los Angeles, Los Angeles, CA 90095, USA; Bioengineering, University of California at Los Angeles, Los Angeles, CA 90095, USA; Mechanical Engineering, University of California at Riverside, Riverside, CA 92521, USA.
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9
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Lai W, Xiong X, Wang F, Li Q, Li L, Fan C, Pei H. Nonlinear Regulation of Enzyme-Free DNA Circuitry with Ultrasensitive Switches. ACS Synth Biol 2019; 8:2106-2112. [PMID: 31461263 DOI: 10.1021/acssynbio.9b00208] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
DNA is used to construct synthetic chemical reaction networks (CRNs), such as inorganic oscillators and gene regulatory networks. Nonlinear regulation with a simpler molecular mechanism is particularly important in large-scale CRNs with complex dynamics, such as bistability, adaptation, and oscillation of cellular functions. Here we introduce a new approach based on ultrasensitive switches as modular regulatory elements to nonlinearly regulate DNA-based CRNs. The nonlinear behavior of the systems can be finely tuned by programmable regulation of the linker length and the ligand binding sites, of which the Hill coefficients (nH) are in the range of 1.00-2.32. By integrating two different strand displacement reactions with low-order nonlinearities (nH ≈ 1.44 and 1.54), we could construct CRNs exhibiting high-order nonlinearities with Hill coefficients of up to ∼2.70. In addition, this could provide an efficient approach for designing CRNs at will with complex chemical dynamics by incorporating our design with previously developed enzyme-free DNA circuits.
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Affiliation(s)
- Wei Lai
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, 500 Dongchuan Road, Shanghai 200241, P. R. China
| | - Xiewei Xiong
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, 500 Dongchuan Road, Shanghai 200241, P. R. China
| | - Fei Wang
- School of Chemistry and Chemical Engineering and Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Qian Li
- School of Chemistry and Chemical Engineering and Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Li Li
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, 500 Dongchuan Road, Shanghai 200241, P. R. China
| | - Chunhai Fan
- School of Chemistry and Chemical Engineering and Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Hao Pei
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, 500 Dongchuan Road, Shanghai 200241, P. R. China
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Pasotti L, Bellato M, Politi N, Casanova M, Zucca S, Cusella De Angelis MG, Magni P. A Synthetic Close-Loop Controller Circuit for the Regulation of an Extracellular Molecule by Engineered Bacteria. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019; 13:248-258. [PMID: 30489274 DOI: 10.1109/tbcas.2018.2883350] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Feedback control is ubiquitous in biological systems. It can also play a crucial role in the design of synthetic circuits implementing novel functions in living systems, to achieve self-regulation of gene expression, noise reduction, rise time decrease, or adaptive pathway control. Despite in vitro, in vivo, and ex vivo implementations have been successfully reported, the design of biological close-loop systems with quantitatively predictable behavior is still a major challenge. In this work, we tested a model-based bottom-up design of a synthetic close-loop controller in engineered Escherichia coli, aimed to automatically regulate the concentration of an extracellular molecule, N-(3-oxohexanoyl)-L-homoserine lactone (HSL), by rewiring the elements of heterologous quorum sensing/quenching networks. The synthetic controller was successfully constructed and experimentally validated. Relying on mathematical model and experimental characterization of individual regulatory parts and enzymes, we evaluated the predictability of the interconnected system behavior in vivo. The culture was able to reach an HSL steady-state level of 72 nM, accurately predicted by the model, and showed superior capabilities in terms of robustness against cell density variation and disturbance rejection, compared with a corresponding open-loop circuit. This engineering-inspired design approach may be adopted for the implementation of other close-loop circuits for different applications and contribute to decreasing trial-and-error steps.
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11
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Sagar A, LeCover R, Shoemaker C, Varner J. Dynamic Optimization with Particle Swarms (DOPS): a meta-heuristic for parameter estimation in biochemical models. BMC SYSTEMS BIOLOGY 2018; 12:87. [PMID: 30314484 PMCID: PMC6186122 DOI: 10.1186/s12918-018-0610-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Accepted: 09/17/2018] [Indexed: 01/28/2023]
Abstract
BACKGROUND Mathematical modeling is a powerful tool to analyze, and ultimately design biochemical networks. However, the estimation of the parameters that appear in biochemical models is a significant challenge. Parameter estimation typically involves expensive function evaluations and noisy data, making it difficult to quickly obtain optimal solutions. Further, biochemical models often have many local extrema which further complicates parameter estimation. Toward these challenges, we developed Dynamic Optimization with Particle Swarms (DOPS), a novel hybrid meta-heuristic that combined multi-swarm particle swarm optimization with dynamically dimensioned search (DDS). DOPS uses a multi-swarm particle swarm optimization technique to generate candidate solution vectors, the best of which is then greedily updated using dynamically dimensioned search. RESULTS We tested DOPS using classic optimization test functions, biochemical benchmark problems and real-world biochemical models. We performed [Formula: see text] = 25 trials with [Formula: see text] = 4000 function evaluations per trial, and compared the performance of DOPS with other commonly used meta-heuristics such as differential evolution (DE), simulated annealing (SA) and dynamically dimensioned search (DDS). On average, DOPS outperformed other common meta-heuristics on the optimization test functions, benchmark problems and a real-world model of the human coagulation cascade. CONCLUSIONS DOPS is a promising meta-heuristic approach for the estimation of biochemical model parameters in relatively few function evaluations. DOPS source code is available for download under a MIT license at http://www.varnerlab.org .
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Affiliation(s)
- Adithya Sagar
- Robert Fredrick Smith School of Chemical and Biomolecular Engineering, Cornell University, 244 Olin Hall, Ithaca, NY, USA
| | - Rachel LeCover
- Robert Fredrick Smith School of Chemical and Biomolecular Engineering, Cornell University, 244 Olin Hall, Ithaca, NY, USA
| | - Christine Shoemaker
- School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, USA
| | - Jeffrey Varner
- Robert Fredrick Smith School of Chemical and Biomolecular Engineering, Cornell University, 244 Olin Hall, Ithaca, NY, USA.
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Anderson WD, Greenhalgh AD, Takwale A, David S, Vadigepalli R. Novel Influences of IL-10 on CNS Inflammation Revealed by Integrated Analyses of Cytokine Networks and Microglial Morphology. Front Cell Neurosci 2017; 11:233. [PMID: 28855862 PMCID: PMC5557777 DOI: 10.3389/fncel.2017.00233] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 07/25/2017] [Indexed: 01/16/2023] Open
Abstract
Coordinated interactions between cytokine signaling and morphological dynamics of microglial cells regulate neuroinflammation in CNS injury and disease. We found that pro-inflammatory cytokine gene expression in vivo showed a pronounced recovery following systemic LPS. We performed a novel multivariate analysis of microglial morphology and identified changes in specific morphological properties of microglia that matched the expression dynamics of pro-inflammatory cytokine TNFα. The adaptive recovery kinetics of TNFα expression and microglial soma size showed comparable profiles and dependence on anti-inflammatory cytokine IL-10 expression. The recovery of cytokine variations and microglial morphology responses to inflammation were negatively regulated by IL-10. Our novel morphological analysis of microglia is able to detect subtle changes and can be used widely. We implemented in silico simulations of cytokine network dynamics which showed—counter-intuitively, but in line with our experimental observations—that negative feedback from IL-10 was sufficient to impede the adaptive recovery of TNFα-mediated inflammation. Our integrative approach is a powerful tool to study changes in specific components of microglial morphology for insights into their functional states, in relation to cytokine network dynamics, during CNS injury and disease.
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Affiliation(s)
- Warren D Anderson
- Daniel Baugh Institute for Functional Genomics/Computational Biology, Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson UniversityPhiladelphia, PA, United States
| | - Andrew D Greenhalgh
- Center for Research in Neuroscience, The Research Institute of the McGill University Health CenterMontreal, QC, Canada
| | - Aditya Takwale
- Center for Research in Neuroscience, The Research Institute of the McGill University Health CenterMontreal, QC, Canada
| | - Samuel David
- Center for Research in Neuroscience, The Research Institute of the McGill University Health CenterMontreal, QC, Canada
| | - Rajanikanth Vadigepalli
- Daniel Baugh Institute for Functional Genomics/Computational Biology, Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson UniversityPhiladelphia, PA, United States
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13
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Cuba Samaniego C, Franco E. An ultrasensitive biomolecular network for robust feedback control. ACTA ACUST UNITED AC 2017. [DOI: 10.1016/j.ifacol.2017.08.2466] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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