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Nanda P, Budak M, Michael CT, Krupinsky K, Kirschner DE. Development and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.13.566861. [PMID: 38014103 PMCID: PMC10680629 DOI: 10.1101/2023.11.13.566861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Although infectious disease dynamics are often analyzed at the macro-scale, increasing numbers of drug-resistant infections highlight the importance of within-host modeling that simultaneously solves across multiple scales to effectively respond to epidemics. We review multiscale modeling approaches for complex, interconnected biological systems and discuss critical steps involved in building, analyzing, and applying such models within the discipline of model credibility. We also present our two tools: CaliPro, for calibrating multiscale models (MSMs) to datasets, and tunable resolution, for fine- and coarse-graining sub-models while retaining insights. We include as an example our work simulating infection with Mycobacterium tuberculosis to demonstrate modeling choices and how predictions are made to generate new insights and test interventions. We discuss some of the current challenges of incorporating novel datasets, rigorously training computational biologists, and increasing the reach of MSMs. We also offer several promising future research directions of incorporating within-host dynamics into applications ranging from combinatorial treatment to epidemic response.
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Abraha BW, Marchisio MA. Design of Gene Boolean Gates and Circuits with Convergent Promoters. Methods Mol Biol 2023; 2553:121-154. [PMID: 36227542 DOI: 10.1007/978-1-0716-2617-7_7] [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] [Indexed: 06/16/2023]
Abstract
Gene digital circuits are the subject of many research works due to their various potential applications, from hazard detection to medical diagnostic. Moreover, a remarkable number of techniques, developed in electronics, can be used for the construction of biological digital systems. In our previous works, we showed how to automatize the design and modeling of gene digital circuits whose gates were based on transcription and translation regulation. In this chapter, we illustrate how Boolean gates could be implemented by following a particular architecture, the convergent promoter one, rather diffuse in nature but seldom adopted in Synthetic Biology. Beside gate design, we also explain how to extend our previous modeling approach, based on composable parts and pools of molecules, to quantitatively describe and simulate this particular kind of digital biological devices.
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Affiliation(s)
- Biruck Woldai Abraha
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
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Abraha BW, Marchisio MA. NOT Gates Based on Protein Degradation as a Case Study for a New Modular Modeling via SBML Level 3—Comp Package. Front Bioeng Biotechnol 2022; 10:845240. [PMID: 35360404 PMCID: PMC8961978 DOI: 10.3389/fbioe.2022.845240] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 02/21/2022] [Indexed: 11/13/2022] Open
Abstract
In 2008, we were among the first to propose a method for the visual design and modular modeling of synthetic gene circuits, mimicking the way electronic circuits are realized in silico. Basic components were DNA sequences that could be composed, first, into transcription units (TUs) and, then, circuits by exchanging fluxes of molecules, such as PoPS (polymerase per second) and RiPS (ribosomes per seconds) as suggested by Drew Endy. However, it became clear soon that such fluxes were not measurable, which highlighted the limit of using some concepts from electronics to represent biological systems. SBML Level 3 with the comp package permitted us to revise circuit modularity, especially for the modeling of eukaryotic networks. By using the libSBML Python API, TUs—rather than single parts—are encoded in SBML Level 3 files that contain species, reactions, and ports, i.e., the interfaces that permit to wire TUs into circuits. A circuit model consists of a collection of SBML Level 3 files associated with the different TUs plus a “main” file that delineates the circuit structure. Within this framework, there is no more need for any flux of molecules. Here, we present the SBML Level 3-based models and the wet-lab implementations of Boolean NOT gates that make use, in the yeast Saccharomyces cerevisiae, of the bacterial ClpX-ClpP system for protein degradation. This work is the starting point towards a new piece of software for the modular design of eukaryotic gene circuits and shows an alternative way to build genetic Boolean gates.
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Wang X, Marchisio MA. Synthetic polycistronic sequences in eukaryotes. Synth Syst Biotechnol 2021; 6:254-261. [PMID: 34584993 PMCID: PMC8449083 DOI: 10.1016/j.synbio.2021.09.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 08/31/2021] [Accepted: 09/02/2021] [Indexed: 12/18/2022] Open
Abstract
The need for co-ordinate, high-level, and stable expression of multiple genes is essential for the engineering of biosynthetic circuits and metabolic pathways. This work outlines the functionality and design of IRES- and 2 A-peptide-based constructs by comparing different strategies for co-expression in polycistronic vectors. In particular, 2 A sequences are small peptides, mostly derived from viral polyproteins, that mediate a ribosome-skipping event such that several, different, separate proteins can be generated from a single open reading frame. When applied to metabolic engineering and synthetic gene circuits, 2 A peptides permit to achieve co-regulated and reliable expression of various genes in eukaryotic cells.
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Affiliation(s)
- Xuekun Wang
- School of Pharmaceutical Science and Technology, Tianjin University, 92 Weijin Road, 300072, Tianjin, China
| | - Mario Andrea Marchisio
- School of Pharmaceutical Science and Technology, Tianjin University, 92 Weijin Road, 300072, Tianjin, China
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Marchisio MA. Computational Gene Circuit Design. INTRODUCTION IN SYNTHETIC BIOLOGY 2018:109-129. [DOI: 10.1007/978-981-10-8752-3_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
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Marchisio MA. Rule-Based Modeling. INTRODUCTION IN SYNTHETIC BIOLOGY 2018:91-107. [DOI: 10.1007/978-981-10-8752-3_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
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Nucleotides upstream of the Kozak sequence strongly influence gene expression in the yeast S. cerevisiae. J Biol Eng 2017; 11:25. [PMID: 28835771 PMCID: PMC5563945 DOI: 10.1186/s13036-017-0068-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Accepted: 06/13/2017] [Indexed: 11/25/2022] Open
Abstract
Background In the yeast Saccharomyces cerevisiae, as in every eukaryotic organism, the mRNA 5′-untranslated region (UTR) is important for translation initiation. However, the patterns and mechanisms that determine the efficiency with which ribozomes bind mRNA, the elongation of ribosomes through the 5′-UTR, and the formation of a stable translation initiation complex are not clear. Genes that are highly expressed in S. cerevisiae seem to prefer a 5′-UTR rich in adenine and poor in guanine, particularly in the Kozak sequence, which occupies roughly the first six nucleotides upstream of the START codon. Results We measured the fluorescence produced by 58 synthetic versions of the S. cerevisiae minimal CYC1 promoter (pCYC1min), each containing a different 5′-UTR. First, we replaced with adenine the last 15 nucleotides of the original pCYC1min 5′-UTR—a theoretically optimal configuration for high gene expression. Next, we carried out single and multiple point mutations on it. Protein synthesis was highly affected by both single and multiple point mutations upstream of the Kozak sequence. RNAfold simulations revealed that significant changes in the mRNA secondary structures occur by mutating more than three adenines into guanines between positions −15 and −9. Furthermore, the effect of point mutations turned out to be strongly context-dependent, indicating that adenines placed just upstream of the START codon do not per se guarantee an increase in gene expression, as previously suggested. Conclusions New synthetic eukaryotic promoters, which differ for their translation initiation rate, can be built by acting on the nucleotides upstream of the Kozak sequence. Translation efficiency could, potentially, be influenced by another portion of the 5′-UTR further upstream of the START codon. A deeper understanding of the role of the 5′-UTR in gene expression would improve criteria for choosing and using promoters inside yeast synthetic gene circuits. Electronic supplementary material The online version of this article (doi:10.1186/s13036-017-0068-1) contains supplementary material, which is available to authorized users.
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Chylek LA, Harris LA, Faeder JR, Hlavacek WS. Modeling for (physical) biologists: an introduction to the rule-based approach. Phys Biol 2015; 12:045007. [PMID: 26178138 PMCID: PMC4526164 DOI: 10.1088/1478-3975/12/4/045007] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Models that capture the chemical kinetics of cellular regulatory networks can be specified in terms of rules for biomolecular interactions. A rule defines a generalized reaction, meaning a reaction that permits multiple reactants, each capable of participating in a characteristic transformation and each possessing certain, specified properties, which may be local, such as the state of a particular site or domain of a protein. In other words, a rule defines a transformation and the properties that reactants must possess to participate in the transformation. A rule also provides a rate law. A rule-based approach to modeling enables consideration of mechanistic details at the level of functional sites of biomolecules and provides a facile and visual means for constructing computational models, which can be analyzed to study how system-level behaviors emerge from component interactions.
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Affiliation(s)
- Lily A Chylek
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
- Theoretical Biology and Biophysics Group, Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
| | - Leonard A Harris
- Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN 37212, USA
| | - James R Faeder
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA
| | - William S Hlavacek
- Theoretical Biology and Biophysics Group, Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
- New Mexico Consortium, Los Alamos, NM 87544, USA
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Andreeva K, Soliman MM, Cooper NGF. Regulatory networks in retinal ischemia-reperfusion injury. BMC Genet 2015; 16:43. [PMID: 25902940 PMCID: PMC4424502 DOI: 10.1186/s12863-015-0201-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2015] [Accepted: 04/14/2015] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Retinal function is ordered by interactions between transcriptional and posttranscriptional regulators at the molecular level. These regulators include transcription factors (TFs) and posttranscriptional factors such as microRNAs (miRs). Some studies propose that miRs predominantly target the TFs rather than other types of protein coding genes and such studies suggest a possible interconnection of these two regulators in co-regulatory networks. RESULTS Our lab has generated mRNA and miRNA microarray expression data to investigate time-dependent changes in gene expression, following induction of ischemia-reperfusion (IR) injury in the rat retina. Data from different reperfusion time points following retinal IR-injury were analyzed. Paired expression data for miRNA-target gene (TG), TF-TG, miRNA-TF were used to identify regulatory loop motifs whose expressions were altered by the IR injury paradigm. These loops were subsequently integrated into larger regulatory networks and biological functions were assayed. Systematic analyses of the networks have provided new insights into retinal gene regulation in the early and late periods of IR. We found both overlapping and unique patterns of molecular expression at the two time points. These patterns can be defined by their characteristic molecular motifs as well as their associated biological processes. We highlighted the regulatory elements of miRs and TFs associated with biological processes in the early and late phases of ischemia-reperfusion injury. CONCLUSIONS The etiology of retinal ischemia-reperfusion injury is orchestrated by complex and still not well understood gene networks. This work represents the first large network analysis to integrate miRNA and mRNA expression profiles in context of retinal ischemia. It is likely that an appreciation of such regulatory networks will have prognostic potential. In addition, the computational framework described in this study can be used to construct miRNA-TF interactive systems networks for various diseases/disorders of the retina and other tissues.
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Affiliation(s)
- Kalina Andreeva
- Department of Anatomical Science and Neurobiology, University of Louisville, School of Medicine, 500 S. Preston Street, Louisville, KY, 40292, USA.
| | - Maha M Soliman
- Department of Anatomical Science and Neurobiology, University of Louisville, School of Medicine, 500 S. Preston Street, Louisville, KY, 40292, USA.
| | - Nigel G F Cooper
- Department of Anatomical Science and Neurobiology, University of Louisville, School of Medicine, 500 S. Preston Street, Louisville, KY, 40292, USA.
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Chylek LA, Wilson BS, Hlavacek WS. Modeling biomolecular site dynamics in immunoreceptor signaling systems. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2015; 844:245-62. [PMID: 25480645 DOI: 10.1007/978-1-4939-2095-2_12] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The immune system plays a central role in human health. The activities of immune cells, whether defending an organism from disease or triggering a pathological condition such as autoimmunity, are driven by the molecular machinery of cellular signaling systems. Decades of experimentation have elucidated many of the biomolecules and interactions involved in immune signaling and regulation, and recently developed technologies have led to new types of quantitative, systems-level data. To integrate such information and develop nontrivial insights into the immune system, computational modeling is needed, and it is essential for modeling methods to keep pace with experimental advances. In this chapter, we focus on the dynamic, site-specific, and context-dependent nature of interactions in immunoreceptor signaling (i.e., the biomolecular site dynamics of immunoreceptor signaling), the challenges associated with capturing these details in computational models, and how these challenges have been met through use of rule-based modeling approaches.
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Affiliation(s)
- Lily A Chylek
- Department of Chemistry and Chemical Biology, Cornell University, 14853, Ithaca, NY, USA,
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Wilson-Kanamori J, Danos V, Thomson T, Honorato-Zimmer R. Kappa rule-based modeling in synthetic biology. Methods Mol Biol 2015; 1244:105-135. [PMID: 25487095 DOI: 10.1007/978-1-4939-1878-2_6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Rule-based modeling, an alternative to traditional reaction-based modeling, allows us to intuitively specify biological interactions while abstracting from the underlying combinatorial complexity. One such rule-based modeling formalism is Kappa, which we introduce to readers in this chapter. We discuss the application of Kappa to three modeling scenarios in synthetic biology: a unidirectional switch based on nitrosylase induction in Saccharomyces cerevisiae, the repressilator in Escherichia coli formed from BioBrick parts, and a light-mediated extension to said repressilator developed by the University of Edinburgh team during iGEM 2010. The second and third scenarios in particular form a case-based introduction to the Kappa BioBrick Framework, allowing us to systematically address the modeling of devices and circuits based on BioBrick parts in Kappa. Through the use of these examples, we highlight the ease with which Kappa can model biological interactions both at the genetic and the protein-protein interaction level, resulting in detailed stochastic models accounting naturally for transcriptional and translational resource usage. We also hope to impart the intuitively modular nature of the modeling processes involved, supported by the introduction of visual representations of Kappa models. Concluding, we explore future endeavors aimed at making modeling of synthetic biology more user-friendly and accessible, taking advantage of the strengths of rule-based modeling in Kappa.
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Affiliation(s)
- John Wilson-Kanamori
- School of Informatics, University of Edinburgh, Informatics Forum IF-5.30, 10 Crichton Street, Edinburgh, EH8 9AB, Scotland, UK,
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Marchisio MA. Modular design of synthetic gene circuits with biological parts and pools. Methods Mol Biol 2015; 1244:137-65. [PMID: 25487096 DOI: 10.1007/978-1-4939-1878-2_7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Synthetic gene circuits can be designed in an electronic fashion by displaying their basic components-Standard Biological Parts and Pools of molecules-on the computer screen and connecting them with hypothetical wires. This procedure, achieved by our add-on for the software ProMoT, was successfully applied to bacterial circuits. Recently, we have extended this design-methodology to eukaryotic cells. Here, highly complex components such as promoters and Pools of mRNA contain hundreds of species and reactions whose calculation demands a rule-based modeling approach. We showed how to build such complex modules via the joint employment of the software BioNetGen (rule-based modeling) and ProMoT (modularization). In this chapter, we illustrate how to utilize our computational tool for synthetic biology with the in silico implementation of a simple eukaryotic gene circuit that performs the logic AND operation.
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Affiliation(s)
- Mario Andrea Marchisio
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zurich, Mattenstrasse 26, 4058, Basel, Switzerland,
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Marchisio MA. Parts & pools: a framework for modular design of synthetic gene circuits. Front Bioeng Biotechnol 2014; 2:42. [PMID: 25340051 PMCID: PMC4186347 DOI: 10.3389/fbioe.2014.00042] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2014] [Accepted: 09/16/2014] [Indexed: 01/27/2023] Open
Abstract
Published in 2008, Parts & Pools represents one of the first attempts to conceptualize the modular design of bacterial synthetic gene circuits with Standard Biological Parts (DNA segments) and Pools of molecules referred to as common signal carriers (e.g., RNA polymerases and ribosomes). The original framework for modeling bacterial components and designing prokaryotic circuits evolved over the last years and brought, first, to the development of an algorithm for the automatic design of Boolean gene circuits. This is a remarkable achievement since gene digital circuits have a broad range of applications that goes from biosensors for health and environment care to computational devices. More recently, Parts & Pools was enabled to give a proper formal description of eukaryotic biological circuit components. This was possible by employing a rule-based modeling approach, a technique that permits a faithful calculation of all the species and reactions involved in complex systems such as eukaryotic cells and compartments. In this way, Parts & Pools is currently suitable for the visual and modular design of synthetic gene circuits in yeast and mammalian cells too.
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Abstract
Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behavior of biological molecules or complexes that can adopt a large number of possible functional states. Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: the problem of how to describe and specify a multi-state system (the “specification problem”) and the problem of how to use a computer to simulate the progress of the system over time (the “computation problem”). To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus [1], BioNetGen [2]–[5], the Allosteric Network Compiler [6], and others [7], [8]. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm[9], [10]. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators fall into two further categories: nonspatial simulators, such as StochSim [11], DYNSTOC [12], RuleMonkey [9], [13], and the Network-Free Stochastic Simulator (NFSim) [14], and spatial simulators, including Meredys [15], SRSim [16], [17], and MCell [18]–[20]. Modelers can thus choose from a variety of tools, the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future.
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Affiliation(s)
- Melanie I. Stefan
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
- * E-mail: (MIS); (MBK)
| | - Thomas M. Bartol
- Salk Institute for Biological Studies, La Jolla, California, United States of America
| | - Terrence J. Sejnowski
- Salk Institute for Biological Studies, La Jolla, California, United States of America
| | - Mary B. Kennedy
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
- * E-mail: (MIS); (MBK)
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Otero-Muras I, Banga JR. Multicriteria global optimization for biocircuit design. BMC SYSTEMS BIOLOGY 2014; 8:113. [PMID: 25248337 PMCID: PMC4180256 DOI: 10.1186/s12918-014-0113-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/06/2014] [Accepted: 09/16/2014] [Indexed: 11/10/2022]
Abstract
Background One of the challenges in Synthetic Biology is to design circuits with increasing levels of complexity. While circuits in Biology are complex and subject to natural tradeoffs, most synthetic circuits are simple in terms of the number of regulatory regions, and have been designed to meet a single design criterion. Results In this contribution we introduce a multiobjective formulation for the design of biocircuits. We set up the basis for an advanced optimization tool for the modular and systematic design of biocircuits capable of handling high levels of complexity and multiple design criteria. Our methodology combines the efficiency of global Mixed Integer Nonlinear Programming solvers with multiobjective optimization techniques. Through a number of examples we show the capability of the method to generate non intuitive designs with a desired functionality setting up a priori the desired level of complexity. Conclusions The methodology presented here can be used for biocircuit design and also to explore and identify different design principles for synthetic gene circuits. The presence of more than one competing objective provides a realistic design setting where every solution represents an optimal trade-off between different criteria. Electronic supplementary material The online version of this article (doi:10.1186/s12918-014-0113-3) contains supplementary material, which is available to authorized users.
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Kirschner DE, Hunt CA, Marino S, Fallahi-Sichani M, Linderman JJ. Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2014; 6:289-309. [PMID: 24810243 PMCID: PMC4102180 DOI: 10.1002/wsbm.1270] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2013] [Revised: 03/14/2014] [Accepted: 03/19/2014] [Indexed: 01/19/2023]
Abstract
The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. WIREs Syst Biol Med 2014, 6:225–245. doi:10.1002/wsbm.1270 How to cite this article:WIREs Syst Biol Med 2014, 6:289–309. doi:10.1002/wsbm.1270
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Affiliation(s)
- Denise E Kirschner
- Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA
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Marchisio MA. In silico design and in vivo implementation of yeast gene Boolean gates. J Biol Eng 2014; 8:6. [PMID: 24485181 PMCID: PMC3926364 DOI: 10.1186/1754-1611-8-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2013] [Accepted: 01/25/2014] [Indexed: 12/05/2022] Open
Abstract
In our previous computational work, we showed that gene digital circuits can be automatically designed in an electronic fashion. This demands, first, a conversion of the truth table into Boolean formulas with the Karnaugh map method and, then, the translation of the Boolean formulas into circuit schemes organized into layers of Boolean gates and Pools of signal carriers. In our framework, gene digital circuits that take up to three different input signals (chemicals) arise from the composition of three kinds of basic Boolean gates, namely YES, NOT, and AND. Here we present a library of YES, NOT, and AND gates realized via plasmidic DNA integration into the yeast genome. Boolean behavior is reproduced via the transcriptional control of a synthetic bipartite promoter that contains sequences of the yeast VPH1 and minimal CYC1 promoters together with operator binding sites for bacterial (i.e. orthogonal) repressor proteins. Moreover, model-driven considerations permitted us to pinpoint a strategy for re-designing gates when a better digital performance is required. Our library of well-characterized Boolean gates is the basis for the assembly of more complex gene digital circuits. As a proof of concepts, we engineered two 2-input OR gates, designed by our software, by combining YES and NOT gates present in our library.
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Affiliation(s)
- Mario A Marchisio
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zurich, Mattenstrasse 26, Basel 4058, Switzerland.
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Chylek LA, Harris LA, Tung CS, Faeder JR, Lopez CF, Hlavacek WS. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems. WILEY INTERDISCIPLINARY REVIEWS. SYSTEMS BIOLOGY AND MEDICINE 2014; 6:13-36. [PMID: 24123887 PMCID: PMC3947470 DOI: 10.1002/wsbm.1245] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2013] [Revised: 08/20/2013] [Accepted: 08/21/2013] [Indexed: 01/04/2023]
Abstract
Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation).
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Affiliation(s)
- Lily A. Chylek
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, USA
| | - Leonard A. Harris
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA
| | - Chang-Shung Tung
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - James R. Faeder
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA
| | - Carlos F. Lopez
- Department of Cancer Biology and Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, Tennessee 37212, USA
| | - William S. Hlavacek
- Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
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