The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments
Open accessAbstract
The advent of rapid complete genome sequencing, and the potential to capture this information in genome-scale metabolic models, provide the possibility of comprehensively modeling microbial community interactions. For example, Rhodoferax and Geobacter species are acetate-oxidizing Fe(III)-reducers that compete in anoxic subsurface environments and this competition may have an influence on the in situ bioremediation of uranium-contaminated groundwater. Therefore, genome-scale models of Geobacter sulfurreducens and Rhodoferax ferrireducens were used to evaluate how Geobacter and Rhodoferax species might compete under diverse conditions found in a uranium-contaminated aquifer in Rifle, CO. The model predicted that at the low rates of acetate flux expected under natural conditions at the site, Rhodoferax will outcompete Geobacter as long as sufficient ammonium is available. The model also predicted that when high concentrations of acetate are added during in situ bioremediation, Geobacter species would predominate, consistent with field-scale observations. This can be attributed to the higher expected growth yields of Rhodoferax and the ability of Geobacter to fix nitrogen. The modeling predicted relative proportions of Geobacter and Rhodoferax in geochemically distinct zones of the Rifle site that were comparable to those that were previously documented with molecular techniques. The model also predicted that under nitrogen fixation, higher carbon and electron fluxes would be diverted toward respiration rather than biomass formation in Geobacter, providing a potential explanation for enhanced in situ U(VI) reduction in low-ammonium zones. These results show that genome-scale modeling can be a useful tool for predicting microbial interactions in subsurface environments and shows promise for designing bioremediation strategies.
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Cites
Network biology: understanding the cell's functional organization
Barabási, A.-L., & Oltvai, Z. N. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1272 · Cited by 7,903
Hierarchical structure and the prediction of missing links in networks
Clauset, A., Moore, C., & Newman, M. E. J. (2008) · Nature · doi:10.1038/nature06830 · Cited by 2,171
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.308 · Cited by 1,835
Genome-Scale Reconstruction of the Saccharomyces cerevisiae Metabolic Network
Förster, J., Famili, I., Fu, P., Palsson, B. Ø., & Nielsen, J. (2003) · Genome Research · doi:10.1101/gr.234503 · Cited by 1,069
Lovley, D. R., Giovannoni, S. J., White, D. C., Champine, J. E., Phillips, E. J. P., Gorby, Y. A., & Goodwin, S. (1993) · Archives of Microbiology · doi:10.1007/bf00290916 · Cited by 983
Self-citationDynamic flux balance analysis of diauxic growth in Escherichia coli
Mahadevan, R., Edwards, J. S., & Doyle, F. J. (2002) · Biophysical Journal · doi:10.1016/s0006-3495(02)73903-9 · Cited by 945
Self-citationEscherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth
Ibarra, R. U., Edwards, J. S., & Palsson, B. O. (2002) · Nature · doi:10.1038/nature01149 · Cited by 857 · cited 2×
“Genome-scale flux balance analysis models of pure cultures, such as Escherichia coli (Ibarra et al., 2002; Reed and Palsson, 2003; Reed et al., 2003; Feist et al., 2007; Feist and Palsson, 2008) and Geobacter species (Mahadevan et al.”
BackgroundMetabolic network structure determines key aspects of functionality and regulation
Stelling, J., Klamt, S., Bettenbrock, K., Schuster, S., & Gilles, E. D. (2002) · Nature · doi:10.1038/nature01166 · Cited by 802
Integrating high-throughput and computational data elucidates bacterial networks
Covert, M. W., Knight, E. M., Reed, J. L., Herrgard, M. J., & Palsson, B. O. (2004) · Nature · doi:10.1038/nature02456 · Cited by 792
The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli
Feist, A. M., & Palsson, B. Ø. (2008) · Nature Biotechnology · doi:10.1038/nbt1401 · Cited by 545 · cited 3×
“Genome-scale flux balance analysis models of pure cultures, such as Escherichia coli (Ibarra et al., 2002; Reed and Palsson, 2003; Reed et al., 2003; Feist et al., 2007; Feist and Palsson, 2008) and Geobacter species (Mahadevan et al.”
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Caspi, R., Billington, R., Ferrer, L., Foerster, H., Fulcher, C. A., Keseler, I. M., Kothari, A., Krummenacker, M., Latendresse, M., Mueller, L. A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1164 · Cited by 3,395
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Lewis, N. E., Nagarajan, H., & Palsson, B. O. (2012) · Nature Reviews Microbiology · doi:10.1038/nrmicro2737 · Cited by 779
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Hu, R., Zhao, H., Xu, X., Wang, Z., Yu, K., Shu, L., Yan, Q., Wu, B., Mo, C., He, Z., et al. (2021) · Environment International · doi:10.1016/j.envint.2021.106560 · Cited by 176
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Metadata
- Authors
- Zhuang, K., Izallalen, M., Mouser, P., Richter, H., Risso, C., Mahadevan, R., & Lovley, D. R.
- Venue
- The ISME Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-07-29
- Volume
- 5
- Issue
- 2
- Pages
- 305-316
- ISSN
- 1751-7362 (ISSN-L)
- 1751-7370
- OpenAlex
- W1966497610
- Cited by
- 319
- References
- 12
- FWCI
- 17.66
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Zhuang, K., Izallalen, M., Mouser, P., Richter, H., Risso, C., Mahadevan, R., & Lovley, D. R. (2011). Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments. The ISME Journal. https://doi.org/10.1038/ismej.2010.117
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