Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2016 Feb 10:3:3.
doi: 10.3389/fmolb.2016.00003. eCollection 2016.

Constraint Based Modeling Going Multicellular

Affiliations
Review

Constraint Based Modeling Going Multicellular

Patricia do Rosario Martins Conde et al. Front Mol Biosci. .

Abstract

Constraint based modeling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase the efficiency of microbial strains in chemical production pipelines. In addition, multiple models of multicellular organisms have been created including plants and humans. While initially the focus here was on modeling individual cell types of the multicellular organism, this focus recently started to switch. Models of microbial communities, as well as multi-tissue models of higher organisms have been constructed. These models thereby can include different parts of a plant, like root, stem, or different tissue types in the same organ. Such models can elucidate details of the interplay between symbiotic organisms, as well as the concerted efforts of multiple tissues and can be applied to analyse the effects of drugs or mutations on a more systemic level. In this review we give an overview of the recent development of multi-tissue models using constraint based techniques and the methods employed when investigating these models. We further highlight advances in combining constraint based models with dynamic and regulatory information and give an overview of these types of hybrid or multi-level approaches.

Keywords: constraint based modeling; metabolic modeling; multi-organism modeling; multi-scale modeling; multi-tissue modeling.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Timeline of the development of techniques for the integration of data and the simulation and analysis of complex systems. Please refer to the main text for details. ([1] Savinell and Palsson (1992); [2] Covert et al. (2001); [3] Mahadevan et al. (2002); [4] Mahadevan and Schilling (2003); [5] Covert et al. (2008); [6] Lee et al. (2008); [7] Vo et al. (2004); [8] Krauss et al. (2012); [9] Thiele et al. (2012); [10] Lerman et al. (2012); [11] Fisher et al. (2013)), Images for [8],[9], and [10] are derived from images taken from the respective publications which are provided under a Creative Commons attribution license (https://creativecommons.org/licenses/by/2.0/).
Figure 2
Figure 2
Timeline of development of reconstruction of metabolic models and realization of different models spanning multiple tissues or organisms. Except for the development of the initial genome scale reconstructions from various kingdoms of live, only multi-tissue or multi-compartment models are listed. ([1] Edwards and Palsson (1999); [2] Förster et al. (2003); [3] Sheikh et al. (2005); [4] Duarte et al. (2007); [5] Ma et al. (2007); [6] Stolyar et al. (2007); [7] Bordbar et al. (2010); [8] Lewis et al. (2010); [9] Bordbar et al. (2011); [10] Zomorrodi and Maranas (2012); [11] Heinken et al. (2013); [12] Grafahrend-Belau et al. (2013); [13] Cheung et al. (2014); [14] Kumar et al. (2014); [15] Gomes De Oliveira Dal'molin et al. (2015))

References

    1. Andreozzi S., Miskovic L., Hatzimanikatis V. (2015). ischrunk-in silico approach to characterization and reduction of uncertainty in the kinetic models of genome-scale metabolic networks. Metab. Eng. 33, 158–168. 10.1016/j.ymben.2015.10.002 - DOI - PubMed
    1. Beard D. A., Babson E., Curtis E., Qian H. (2004). Thermodynamic constraints for biochemical networks. J. Theor. Biol. 228, 327–333. 10.1016/j.jtbi.2004.01.008 - DOI - PubMed
    1. Becker S. A., Palsson B. Ø. (2008). Context-specific metabolic networks are consistent with experiments. PLoS Comput. Biol. 4:e1000082. 10.1371/journal.pcbi.1000082 - DOI - PMC - PubMed
    1. Berestovsky N., Zhou W., Nagrath D., Nakhleh L. (2013). Modeling integrated cellular machinery using hybrid petri-boolean networks. PLoS Comput. Biol. 9:e1003306. 10.1371/journal.pcbi.1003306 - DOI - PMC - PubMed
    1. Bordbar A., Feist A. M., Usaite-Black R., Woodcock J., Palsson B. Ø., Famili I. (2011). A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology. BMC Syst. Biol. 5:180. 10.1186/1752-0509-5-180 - DOI - PMC - PubMed

LinkOut - more resources