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Microbial single-cell RNA sequencing by split-pool barcoding.
Kuchina, Anna; Brettner, Leandra M; Paleologu, Luana; Roco, Charles M; Rosenberg, Alexander B; Carignano, Alberto; Kibler, Ryan; Hirano, Matthew; DePaolo, R William; Seelig, Georg.
Afiliación
  • Kuchina A; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA.
  • Brettner LM; Department of Bioengineering, University of Washington, Seattle, WA, USA.
  • Paleologu L; Center for Microbiome Sciences and Therapeutics, School of Medicine, University of Washington, Seattle, WA, USA.
  • Roco CM; Department of Microbiology, University of Washington, Seattle, WA, USA.
  • Rosenberg AB; Department of Biology, University of Washington, Seattle, WA, USA.
  • Carignano A; Department of Bioengineering, University of Washington, Seattle, WA, USA.
  • Kibler R; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA.
  • Hirano M; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA.
  • DePaolo RW; Biological Physics, Structure, and Design, University of Washington, Seattle, WA, USA.
  • Seelig G; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA.
Science ; 371(6531)2021 02 19.
Article en En | MEDLINE | ID: mdl-33335020
Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bacillus subtilis / Regulación Bacteriana de la Expresión Génica / Redes y Vías Metabólicas / Análisis de la Célula Individual / RNA-Seq Idioma: En Revista: Science Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bacillus subtilis / Regulación Bacteriana de la Expresión Génica / Redes y Vías Metabólicas / Análisis de la Célula Individual / RNA-Seq Idioma: En Revista: Science Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos