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Massively parallel screening of synthetic microbial communities.
Kehe, Jared; Kulesa, Anthony; Ortiz, Anthony; Ackerman, Cheri M; Thakku, Sri Gowtham; Sellers, Daniel; Kuehn, Seppe; Gore, Jeff; Friedman, Jonathan; Blainey, Paul C.
Affiliation
  • Kehe J; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.
  • Kulesa A; The Broad Institute of MIT and Harvard, Cambridge, MA 02142.
  • Ortiz A; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.
  • Ackerman CM; The Broad Institute of MIT and Harvard, Cambridge, MA 02142.
  • Thakku SG; Physics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139.
  • Sellers D; The Broad Institute of MIT and Harvard, Cambridge, MA 02142.
  • Kuehn S; The Broad Institute of MIT and Harvard, Cambridge, MA 02142.
  • Gore J; Program in Health Sciences and Technology, MIT and Harvard, Cambridge, MA 02139.
  • Friedman J; The Broad Institute of MIT and Harvard, Cambridge, MA 02142.
  • Blainey PC; Department of Chemical and Biological Engineering, Tufts University, Medford, MA 02155.
Proc Natl Acad Sci U S A ; 116(26): 12804-12809, 2019 06 25.
Article in En | MEDLINE | ID: mdl-31186361
Microbial communities have numerous potential applications in biotechnology, agriculture, and medicine. Nevertheless, the limited accuracy with which we can predict interspecies interactions and environmental dependencies hinders efforts to rationally engineer beneficial consortia. Empirical screening is a complementary approach wherein synthetic communities are combinatorially constructed and assayed in high throughput. However, assembling many combinations of microbes is logistically complex and difficult to achieve on a timescale commensurate with microbial growth. Here, we introduce the kChip, a droplets-based platform that performs rapid, massively parallel, bottom-up construction and screening of synthetic microbial communities. We first show that the kChip enables phenotypic characterization of microbes across environmental conditions. Next, in a screen of ∼100,000 multispecies communities comprising up to 19 soil isolates, we identified sets that promote the growth of the model plant symbiont Herbaspirillum frisingense in a manner robust to carbon source variation and the presence of additional species. Broadly, kChip screening can identify multispecies consortia possessing any optically assayable function, including facilitation of biocontrol agents, suppression of pathogens, degradation of recalcitrant substrates, and robustness of these functions to perturbation, with many applications across basic and applied microbial ecology.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Soil Microbiology / Bacteriological Techniques / High-Throughput Screening Assays / Microbial Consortia Type of study: Diagnostic_studies / Prognostic_studies / Screening_studies Language: En Journal: Proc Natl Acad Sci U S A Year: 2019 Document type: Article Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Soil Microbiology / Bacteriological Techniques / High-Throughput Screening Assays / Microbial Consortia Type of study: Diagnostic_studies / Prognostic_studies / Screening_studies Language: En Journal: Proc Natl Acad Sci U S A Year: 2019 Document type: Article Country of publication: