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Cited by 578

The DOI matches its Crossref record; 114 of the 114 references it cites were found in a registry or an index.

Synthetic Biology Tools to Engineer Microbial Communities for Biotechnology

Open access
McCarty, Nicholas S., Ledesma-Amaro, Rodrigo·2019·Trends in Biotechnology

Abstract

Microbial consortia have been used in biotechnology processes, including fermentation, waste treatment, and agriculture, for millennia. Today, synthetic biologists are increasingly engineering microbial consortia for diverse applications, including the bioproduction of medicines, biofuels, and biomaterials from inexpensive carbon sources. An improved understanding of natural microbial ecosystems, and the development of new tools to construct synthetic consortia and program their behaviors, will vastly expand the functions that can be performed by communities of interacting microorganisms. Here, we review recent advancements in synthetic biology tools and approaches to engineer synthetic microbial consortia, discuss ongoing and emerging efforts to apply consortia for various biotechnological applications, and suggest future applications.

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Crossref · 10.1016/j.tibtech.2018.11.002

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Metadata

Authors
McCarty, N. S., & Ledesma-Amaro, R.
Venue
Trends in Biotechnology
Publisher
Elsevier BV
Published
2019-02
Volume
37
Issue
2
Pages
181-197
ISSN
0167-7799 (ISSN-L)
OpenAlex
W2903216094
Cited by
578
References
114
FWCI
2.66
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Synthetic Biology Tools to Engineer Microbial Communities for Biotechnology. https://app.cochat.ai/papers/10.1016/j.tibtech.2018.11.002
The paper
McCarty, N. S., & Ledesma-Amaro, R. (2019). Synthetic Biology Tools to Engineer Microbial Communities for Biotechnology. Trends in Biotechnology. https://doi.org/10.1016/j.tibtech.2018.11.002

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.