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dc.contributor.authorKreft, Jan-Ulrich
dc.contributor.authorPlugge, Caroline M.
dc.contributor.authorPrats Soler, Clara
dc.contributor.authorLeveau, Johan H. J.
dc.contributor.authorZhang, Weiwen
dc.contributor.authorHellweger, Ferdi L.
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Física
dc.date.accessioned2018-01-31T22:31:43Z
dc.date.available2018-01-31T22:31:43Z
dc.date.issued2017-11-27
dc.identifier.citationKreft, J.U., Plugge, C.M., Prats, C., Leveau, J.H.J., Zhang, W., Hellweger, F.L. From genes to ecosystems in microbiology: modeling approaches and the importance of individuality. "Frontiers in Microbiology", 27 Novembre 2017, vol. 8, p. 1-23.
dc.identifier.issn1664-302X
dc.identifier.urihttp://hdl.handle.net/2117/113503
dc.description.abstractModels are important tools in microbial ecology. They can be used to advance understanding by helping to interpret observations and test hypotheses, and to predict the effects of ecosystem management actions or a different climate. Over the past decades, biological knowledge and ecosystem observations have advanced to the molecular and in particular gene level. However, microbial ecology models have changed less and a current challenge is to make them utilize the knowledge and observations at the genetic level. We review published models that explicitly consider genes and make predictions at the population or ecosystem level. The models can be grouped into three general approaches, i.e., metabolic flux, gene-centric and agent-based. We describe and contrast these approaches by applying them to a hypothetical ecosystem and discuss their strengths and weaknesses. An important distinguishing feature is how variation between individual cells (individuality) is handled. In microbial ecosystems, individual heterogeneity is generated by a number of mechanisms including stochastic interactions of molecules (e.g., gene expression), stochastic and deterministic cell division asymmetry, small-scale environmental heterogeneity, and differential transport in a heterogeneous environment. This heterogeneity can then be amplified and transferred to other cell properties by several mechanisms, including nutrient uptake, metabolism and growth, cell cycle asynchronicity and the effects of age and damage. For example, stochastic gene expression may lead to heterogeneity in nutrient uptake enzyme levels, which in turn results in heterogeneity in intracellular nutrient levels. Individuality can have important ecological consequences, including division of labor, bet hedging, aging and sub-optimality. Understanding the importance of individuality and the mechanism(s) underlying it for the specific microbial system and question investigated is essential for selecting the optimal modeling strategy.
dc.format.extent23 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Microbiologia
dc.subject.lcshMicrobial genetics
dc.subject.lcshMicrobiology
dc.subject.othermicrobial ecology
dc.subject.othergene-centric modeling
dc.subject.othermetabolic flux modeling
dc.subject.otheragent-based modeling
dc.subject.otherindividuality
dc.subject.otherheterogeneity
dc.subject.othersingle cell.
dc.titleFrom genes to ecosystems in microbiology: modeling approaches and the importance of individuality
dc.typeArticle
dc.subject.lemacMicrobiologia
dc.subject.lemacGenètica microbiana
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOCOM-SC - Grup de Biologia Computacional i Sistemes Complexos
dc.identifier.doi10.3389/fmicb.2017.02299
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
drac.iddocument21638082
dc.description.versionPostprint (published version)
upcommons.citation.authorKreft, J.U.; Plugge, C.M.; Prats, C.; Leveau, J.H.J.; Zhang, W.; Hellweger, F.L.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameFrontiers in Microbiology
upcommons.citation.volume8
upcommons.citation.startingPage1
upcommons.citation.endingPage23
dc.identifier.pmid29230200


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial 3.0 Spain