Genetic Memory Devices to Detect Specialized Metabolites in Plant and Soil Microbiomes

Root-associated microbiomes significantly influence plant growth and resilience through intricate chemical dialogues mediated by plant- and microbe-derived specialized metabolites. These metabolites play pivotal roles in shaping the assembly, dynamics, and ecological functions of soil microbiomes. Despite advances in <i>in vitro</i> and DNA sequencing studies, a comprehensive understanding of <i>in situ</i> chemical signaling within plant and soil microbiomes remains elusive due to experimental constraints. To address this gap, we developed and tuned a set of five whole-cell biosensors in <i>Escherichia coli</i> for spatiotemporal, nondisruptive detection of biologically relevant specialized metabolites, including 2,4-diacetylphloroglucinol, pyoluteorin, tetracycline, salicylic acid, and naringenin. Four of these biosensors were successfully adapted to the soil-compatible <i>Pseudomonas putida</i> KT2440 Δall-Φ strain. Additionally, the four sensors were shown to respond to their cognate ligand in a nonsterile soil extract medium containing a diverse microbiome extracted from soil. By employing genetic memory devices with DNA barcodes for readouts, our approach provides a scalable platform for sensing additional specialized metabolites in the future. This work demonstrates the potential of biosensor technologies to unravel the complex chemical interactions driving soil microbiome ecology, with implications for sustainable agricultural practices.

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Publication Details

Journal
ACS Synthetic Biology
Published
2025-08-14
DOI
https://doi.org/10.1021/acssynbio.5c00073
Citations
2
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
1.61
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article

Genetic Memory Devices to Detect Specialized Metabolites in Plant and Soil Microbiomes

Morten Dencker Schostag, Johan Peter Bredal Jørgensen, Morten Lindqvist Hansen, Mikael Lenz Strube et al.
2 citations
ACS Synthetic Biology
Gene expression and cancer classification
1.61
article

Genetic Memory Devices to Detect Specialized Metabolites in Plant and Soil Microbiomes

Morten Dencker Schostag, Johan Peter Bredal Jørgensen, Morten Lindqvist Hansen, Mikael Lenz Strube, Lars Jelsbak, Lei Yang, Kristoffer Ioannis Tang Kordatos, Jens-Jakob Krogh Nørgaard
article en
2 citations

Abstract

Root-associated microbiomes significantly influence plant growth and resilience through intricate chemical dialogues mediated by plant- and microbe-derived specialized metabolites. These metabolites play pivotal roles in shaping the assembly, dynamics, and ecological functions of soil microbiomes. Despite advances in <i>in vitro</i> and DNA sequencing studies, a comprehensive understanding of <i>in situ</i> chemical signaling within plant and soil microbiomes remains elusive due to experimental constraints. To address this gap, we developed and tuned a set of five whole-cell biosensors in <i>Escherichia coli</i> for spatiotemporal, nondisruptive detection of biologically relevant specialized metabolites, including 2,4-diacetylphloroglucinol, pyoluteorin, tetracycline, salicylic acid, and naringenin. Four of these biosensors were successfully adapted to the soil-compatible <i>Pseudomonas putida</i> KT2440 Δall-Φ strain. Additionally, the four sensors were shown to respond to their cognate ligand in a nonsterile soil extract medium containing a diverse microbiome extracted from soil. By employing genetic memory devices with DNA barcodes for readouts, our approach provides a scalable platform for sensing additional specialized metabolites in the future. This work demonstrates the potential of biosensor technologies to unravel the complex chemical interactions driving soil microbiome ecology, with implications for sustainable agricultural practices.

ACS Synthetic BiologyVol. 14(9)
Novo Nordisk Foundation (DK), Technical University of Denmark (DK)
Openalex Percentile: Top 15%
Gene expression and cancer classification
1.61
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