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Spatial metatranscriptomics resolves host-bacteria-fungi interactomes.
Saarenpää, Sami; Shalev, Or; Ashkenazy, Haim; Carlos, Vanessa; Lundberg, Derek Severi; Weigel, Detlef; Giacomello, Stefania.
Afiliação
  • Saarenpää S; SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
  • Shalev O; Max Planck Institute for Biology Tübingen, Tübingen, Germany.
  • Ashkenazy H; Systems Biology of Microbial Communities, University of Tübingen, Tübingen, Germany.
  • Carlos V; Max Planck Institute for Biology Tübingen, Tübingen, Germany.
  • Lundberg DS; Max Planck Institute for Biology Tübingen, Tübingen, Germany.
  • Weigel D; Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany.
  • Giacomello S; Max Planck Institute for Biology Tübingen, Tübingen, Germany.
Nat Biotechnol ; 2023 Nov 20.
Article em En | MEDLINE | ID: mdl-37985875
The interactions of microorganisms among themselves and with their multicellular host take place at the microscale, forming complex networks and spatial patterns. Existing technology does not allow the simultaneous investigation of spatial interactions between a host and the multitude of its colonizing microorganisms, which limits our understanding of host-microorganism interactions within a plant or animal tissue. Here we present spatial metatranscriptomics (SmT), a sequencing-based approach that leverages 16S/18S/ITS/poly-d(T) multimodal arrays for simultaneous host transcriptome- and microbiome-wide characterization of tissues at 55-µm resolution. We showcase SmT in outdoor-grown Arabidopsis thaliana leaves as a model system, and find tissue-scale bacterial and fungal hotspots. By network analysis, we study inter- and intrakingdom spatial interactions among microorganisms, as well as the host response to microbial hotspots. SmT provides an approach for answering fundamental questions on host-microbiome interplay.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article