Georg Basler is supported by a Marie Curie Intra European Fellowship within the 7th European Community Framework Programme, ERC grant agreement number 329682. Evangelos Simeonidis is supported by the Luxembourg Centre for Systems Biomedicine.Peer reviewedPeer Reviewe

Basler, Georg

Simeonidis, Evangelos

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GENERAL COMMENTARYpublished: 03 February 2015doi: 10.3389/fgene.2015.00020Integrating food webs with metabolic networks: modelingcontaminant degradation in marine ecosystemsGeorg Basler1 and Evangelos Simeonidis2,3*1 Department of Environmental Protection, Estación Experimental del Zaidín Consejo Superior de Investigaciones Científicas, Granada, Spain2 Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg3 Institute for Systems Biology, Seattle, WA, USA*Correspondence: evangelos.simeonidis@uni.luEdited by:Damien Eveillard, Université de Nantes, FranceReviewed by:Lionel Guidi, Centre National de la Recherche Scientifique, FranceKeywords: flux balance analysis, ecosystem modeling, food webs, biodegradation, PCBs, marine ecosystems, network analysis, genome-scale metabolicmodelingA commentary onBioremediation in marine ecosystems:a computational study combiningecological modeling and flux balanceanalysisby Taffi, M., Paoletti, N., Angione, C.,Pucciarelli, S., Marini, M., and Liò,P. (2014). Front. Genet. 5:319. doi:10.3389/fgene.2014.00319The seas are continuously pervaded bya broad range of contaminants enteringthe marine environment from pollutedsoils, the atmosphere, sewage, water trans-port or river streams (Shahidul Islamand Tanaka, 2004). Organic pollutantsare of particular concern, because oftheir tendency to accumulate in specificorganisms, thus threatening both ecosys-tem stability and human health (Fleminget al., 2006; Johnston and Roberts, 2009).Among those, polychlorinated biphenyls(PCBs) are synthetic compounds pro-duced by the chemical industry and foundthroughout global environments (Beyerand Biziuk, 2009). Due to their hydropho-bicity, PCBs accumulate in the lipids ofmarine species, leading to bioaccumula-tion predominantly at higher trophic levels(Perugini et al., 2004). On the other hand,PCBs can be degraded by the sequentialanaerobic and aerobic metabolic pro-cesses of microorganisms (Borja et al.,2005). Consequently, the accumulationand fate of these pollutants within ecosys-tems depend not only on their uptake byand transfer among marine species, butalso on microbial biodegradation. Thebiostimulation of degrading bacteria ortheir insertion (bioaugmentation) at con-taminated sites may represent a promisingstrategy for bioremediation (Tyagi et al.,2011).Biomass transfer among species of afood web can be modeled using allometricscaling rules describing body size, con-sumption and metabolism (Yodzis andInnes, 1992; Berlow et al., 2009). Similarly,the flow of contaminants through a foodweb can be estimated by mass-balancemodeling of chemical transfer and adsorp-tion (Wania and Mackay, 1999; Arnotand Gobas, 2004; Breivik et al., 2007;Nichols et al., 2009; Taffi et al., in press).Such modeling approaches can be com-plemented by measurements of contam-inant concentrations (Kelly et al., 2007).Recently, a food web representing themajor ecological groups of the Adriatic Seaand their predator-prey interactions (Collet al., 2007) was integrated with PCB con-centration data obtained from an extensiveliterature review (Taffi et al., in press).The resulting model allowed predictionof the flow rates of PCBs among ecolog-ical groups and reproduced the findingthat PCBs accumulate mostly in species athigher trophic levels and with lower totalbiomass. Further, the model allowed esti-mation of the fate of contaminants, such astheir bioaccumulation in marine species.The described efforts facilitated genericestimations of contaminant flows inecosystems, but largely neglected the con-tribution of microorganisms to pollutantdegradation. Specifically, PCBs can bedechlorinated and degraded by a rangeof bacteria (Borja et al., 2005). Thus,biodegradation may be an importantfactor for the persistence of a pollutantwithin an ecosystem and, moreover, mayprovide hints for bioremediation strate-gies based on the aforementioned bacteria.The uptake, degradation and excretionof compounds by microorganisms canbe predicted from the knowledge of theirmetabolic capabilities using constraint-based approaches (Bordbar et al., 2014).Today, detailed metabolic reconstruc-tions are available for a broad range oforganisms (Monk et al., 2014), includingseveral bacteria known for their biore-mediation capabilities, such as Geobacterspp. (Mahadevan et al., 2011), Shewanellaoneidensis (Fredrickson et al., 2008), andPseudomonas putida (Nogales et al., 2008);and new reconstructions for more organ-isms are published regularly. Thus, anintriguing challenge is the combinationof ecological and metabolic modelingapproaches to integrate population-levelsimulations of ecosystems with cellularmodeling of microbial metabolism, simi-lar to the previous integration of reactivetransport models with metabolic models(Fang et al., 2011).Taffi et al. (2014) have recently inte-grated a comprehensive food web of theAdriatic Sea with PCB concentration dataand a metabolic model of P. putida.First, the authors conducted an exten-sive literature review to complement afood web reconstruction (Coll et al.,2007) with data of PCB concentrationsamong marine species (Taffi et al., inpress). Next, linear inverse modeling waswww.frontiersin.org February 2015 | Volume 6 | Article 20 | 1Basler and Simeonidis Food webs and metabolic modelingused to infer unknown contaminant flowsand concentrations based on the massbalance principle. Finally, the ecologicalnetwork was integrated with the genome-scale metabolic network of P. putida forconstraint-based simulation of microbialPCB degradation. The study integratedtwo methodologically similar modelingapproaches within a reaction-based eco-logical/microbial network representation,relying on the parallels between repre-senting PCB concentrations and flows onthe ecosystem level, and metabolite con-centrations and reaction fluxes on themicrobial cellular level. Therein, marinespecies groups resemble the representationof metabolites, while contaminant flowsare modeled as reactions. This approachenabled the seamless integration of ecolog-ical and metabolic modeling techniques,providing the basis for multi-scale simula-tions of ecosystems.The modeling approach was used topredict the influence of different micro-bial bioremediation strategies on the fateand distribution of PCBs in marine speciesof the Adriatic Sea. The effect of varyingoxygen levels on microbial PCB degra-dation revealed a tradeoff between PCBuptake and growth of P. putida. Further,the impact of different bioremediation sce-narios on global and local network indiceswas assessed. Importantly, the generalityof the proposed approach facilitates theintegration of measured data, the incor-poration of established techniques fromecological and metabolic modeling andthe direct application of the methodol-ogy to other ecological and microbial net-works. Thus, it can be used to guidethe selection of appropriate bacteria andconsortia (Thompson et al., 2005), orthe design of genetically engineered bac-teria for bioremediation (Singh et al.,2011). The approach will stimulate newdevelopments in ecological modeling andoffer insights into the multi-level inter-play among ecosystems, microbial net-works and biodegradation.ACKNOWLEDGMENTSWe thank Alejandro Acosta-González forcritical comments on the manuscript.Georg Basler is supported by a MarieCurie Intra European Fellowship withinthe 7th European Community FrameworkProgramme, ERC grant agreementnumber 329682. Evangelos Simeonidisis supported by the Luxembourg Centrefor Systems Biomedicine.REFERENCESArnot, J. A., and Gobas, F. A. P. C. (2004). A foodweb bioaccumulation model for organic chemicalsin aquatic ecosystems. Environ. Toxicol. Chem. 23,2343–2355. doi: 10.1897/03-438Berlow, E. L., Dunne, J. A., Martinez, N. D., Stark,P. B., Williams, R. J., and Brose, U. (2009).Simple prediction of interaction strengths in com-plex food webs. Proc. Natl. Acad. Sci. U.S.A. 106,187–191. doi: 10.1073/pnas.0806823106Beyer, A., and Biziuk, M. (2009). 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Bioremediationin marine ecosystems: a computational studycombining ecological modeling and fluxbalance analysis. Front. Genet. 5:319. doi:10.3389/fgene.2014.00319Taffi, M., Paoletti, N., Liò, P., Pucciarelli, S., andMarini, M. (in press). Bioaccumulation modellingand sensitivity analysis for discovering key play-ers in contaminated food webs: the case studyof PCBs in the Adriatic Sea. Ecol. Modell. doi:10.1016/j.ecolmodel.2014.11.030Thompson, I. P., Van Der Gast, C. J., Ciric, L.,and Singer, A. C. (2005). Bioaugmentationfor bioremediation: the challenge of strainselection. Environ. Microbiol. 7, 909–915. doi:10.1111/j.1462-2920.2005.00804.xTyagi, M., Da Fonseca, M. M. R., and De Carvalho,C. C. C. R. (2011). Bioaugmentation and bios-timulation strategies to improve the effectivenessof bioremediation processes. Biodegradation 22,231–241. doi: 10.1007/s10532-010-9394-4Wania, F., and Mackay, D. (1999). The evolutionof mass balance models of persistent organicpollutant fate in the environment. Environ.Pollut. 100, 223–240. doi: 10.1016/S0269-7491(99)00093-7Yodzis, P., and Innes, S. (1992). Body size andconsumer-resource dynamics. Am. Nat. 139,1151–1175. doi: 10.1086/285380Conflict of Interest Statement: The authors declarethat the research was conducted in the absence of anycommercial or financial relationships that could beconstrued as a potential conflict of interest.Frontiers in Genetics | Systems Biology February 2015 | Volume 6 | Article 20 | 2Basler and Simeonidis Food webs and metabolic modelingReceived: 03 December 2014; accepted: 15 January 2015;published online: 03 February 2015.Citation: Basler G and Simeonidis E (2015) Integratingfood webs with metabolic networks: modeling contam-inant degradation in marine ecosystems. Front. Genet.6:20. doi: 10.3389/fgene.2015.00020This article was submitted to Systems Biology, a sectionof the journal Frontiers in Genetics.Copyright © 2015 Basler and Simeonidis. This is anopen-access article distributed under the terms of theCreative Commons Attribution License (CC BY). Theuse, distribution or reproduction in other forums ispermitted, provided the original author(s) or licen-sor are credited and that the original publicationin this journal is cited, in accordance with acceptedacademic practice. No use, distribution or reproduc-tion is permitted which does not comply with theseterms.www.frontiersin.org February 2015 | Volume 6 | Article 20 | 3

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