Dynamic carbon flux network of a diverse marine microbial community

dc.contributor.authorMayerhofer, Marvin M.
dc.contributor.authorEigemann, Falk
dc.contributor.authorLackner, Carsten
dc.contributor.authorHoffmann, Jutta
dc.contributor.authorHellweger, Ferdi L.
dc.date.accessioned2021-12-13T07:11:33Z
dc.date.available2021-12-13T07:11:33Z
dc.date.issued2021-09-25
dc.description.abstractThe functioning of microbial ecosystems has important consequences from global climate to human health, but quantitative mechanistic understanding remains elusive. The components of microbial ecosystems can now be observed at high resolution, but interactions still have to be inferred e.g., a time-series may show a bloom of bacteria X followed by virus Y suggesting they interact. Existing inference approaches are mostly empirical, like correlation networks, which are not mechanistically constrained and do not provide quantitative mass fluxes, and thus have limited utility. We developed an inference method, where a mechanistic model with hundreds of species and thousands of parameters is calibrated to time series data. The large scale, nonlinearity and feedbacks pose a challenging optimization problem, which is overcome using a novel procedure that mimics natural speciation or diversification e.g., stepwise increase of bacteria species. The method allows for curation using species-level information from e.g., physiological experiments or genome sequences. The product is a mass-balancing, mechanistically-constrained, quantitative representation of the ecosystem. We apply the method to characterize phytoplankton—heterotrophic bacteria interactions via dissolved organic matter in a marine system. The resulting model predicts quantitative fluxes for each interaction and time point (e.g., 0.16 µmolC/L/d of chrysolaminarin to Polaribacter on April 16, 2009). At the system level, the flux network shows a strong correlation between the abundance of bacteria species and their carbon flux during blooms, with copiotrophs being relatively more important than oligotrophs. However, oligotrophs, like SAR11, are unexpectedly high carbon processors for weeks into blooms, due to their higher biomass. The fraction of exudates (vs. grazing/death products) in the DOM pool decreases during blooms, and they are preferentially consumed by oligotrophs. In addition, functional similarity of phytoplankton i.e., what they produce, decouples their association with heterotrophs. The methodology is applicable to other microbial ecosystems, like human microbiome or wastewater treatment plants.en
dc.description.sponsorshipDFG, 248198858, GRK 2032: Grenzzonen in urbanen Wassersystemenen
dc.description.sponsorshipTU Berlin, Open-Access-Mittel – 2021en
dc.identifier.eissn2730-6151
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/14033
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-12806
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc570 Biowissenschaften; Biologiede
dc.subject.otherbiogeochemistryen
dc.subject.otherecologyen
dc.subject.othermicrobiologyen
dc.subject.otherFluxNeten
dc.subject.otherorganic matteren
dc.titleDynamic carbon flux network of a diverse marine microbial communityen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber50en
dcterms.bibliographicCitation.doi10.1038/s43705-021-00055-7en
dcterms.bibliographicCitation.journaltitleISME Communicationsen
dcterms.bibliographicCitation.originalpublishernameSpringer Natureen
dcterms.bibliographicCitation.originalpublisherplaceLondonen
dcterms.bibliographicCitation.volume1en
tub.accessrights.dnbfreeen
tub.affiliationFak. 3 Prozesswissenschaften>Inst. Technischen Umweltschutz>FG Wasserreinhaltungde
tub.affiliation.facultyFak. 3 Prozesswissenschaften
tub.affiliation.groupFG Wasserreinhaltung
tub.affiliation.instituteInst. Technischen Umweltschutz
tub.publisher.universityorinstitutionTechnische Universität Berlinen
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