The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
Design of synthetic bacterial communities for predictable plant phenotypes
Open accessAbstract
Specific members of complex microbiota can influence host phenotypes, depending on both the abiotic environment and the presence of other microorganisms. Therefore, it is challenging to define bacterial combinations that have predictable host phenotypic outputs. We demonstrate that plant-bacterium binary-association assays inform the design of small synthetic communities with predictable phenotypes in the host. Specifically, we constructed synthetic communities that modified phosphate accumulation in the shoot and induced phosphate starvation-responsive genes in a predictable fashion. We found that bacterial colonization of the plant is not a predictor of the plant phenotypes we analyzed. Finally, we demonstrated that characterizing a subset of all possible bacterial synthetic communities is sufficient to predict the outcome of untested bacterial consortia. Our results demonstrate that it is possible to infer causal relationships between microbiota membership and host phenotypes and to use these inferences to rationally design novel communities.
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A review on the plant microbiome: Ecology, functions, and emerging trends in microbial application
Compant, S., Samad, A., Faist, H., & Sessitsch, A. (2019) · Journal of Advanced Research · doi:10.1016/j.jare.2019.03.004 · Cited by 1,643
Harnessing the plant microbiome for sustainable crop production
Compant, S., Cassan, F., Kostić, T., Johnson, L., Brader, G., Trognitz, F., & Sessitsch, A. (2025) · Nature Reviews Microbiology · doi:10.1038/s41579-024-01079-1 · Cited by 365
Data-driven prediction of colonization outcomes for complex microbial communities
Wu, L., Wang, X.-W., Tao, Z., Wang, T., Zuo, W., Zeng, Y., Liu, Y.-Y., & Dai, L. (2024) · Nature Communications · doi:10.1038/s41467-024-46766-y · Cited by 44
Metadata
- Authors
- Herrera Paredes, S., Gao, T., Law, T. F., Finkel, O. M., Mucyn, T., Teixeira, P. J. P. L., Salas González, I., Feltcher, M. E., Powers, M. J., Shank, E. A., Jones, C. D., Jojic, V., Dangl, J. L., & Castrillo, G.
- Venue
- PLOS Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2018-02-20
- Volume
- 16
- Issue
- 2
- Pages
- e2003962
- ISSN
- 1544-9173 (ISSN-L)
- 1545-7885
- OpenAlex
- W2788354600
- Cited by
- 267
- References
- 68
- FWCI
- 21.24
- Type
- journal article
- Language
- en
- Open access
- gold
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- Herrera Paredes, S., Gao, T., Law, T. F., Finkel, O. M., Mucyn, T., Teixeira, P. J. P. L., Salas González, I., Feltcher, M. E., Powers, M. J., Shank, E. A., Jones, C. D., Jojic, V., Dangl, J. L., & Castrillo, G. (2018). Design of synthetic bacterial communities for predictable plant phenotypes. PLOS Biology. https://doi.org/10.1371/journal.pbio.2003962
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