A Single Bacterial Genus Maintains Root Growth in a Complex Microbiome
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Article A single bacterial genus maintains root growth in a complex microbiome https://doi.org/10.1038/s41586-020-2778-7 Omri M. Finkel1,2,9,12, Isai Salas-González1,2,3,12, Gabriel Castrillo1,2,10,12, Jonathan M. Conway1,2,12, Theresa F. Law1,2, Paulo José Pereira Lima Teixeira1,2,11, Ellie D. Wilson1,2, Connor R. Fitzpatrick1,2, Received: 17 January 2020 Corbin D. Jones1,3,4,5,6,7 & Jeffery L. Dangl1,2,3,6,7,8 ✉ Accepted: 3 July 2020 Published online: xx xx xxxx Plants grow within a complex web of species that interact with each other and with the Check for updates plant1–10. These interactions are governed by a wide repertoire of chemical signals, and the resulting chemical landscape of the rhizosphere can strongly afect root health and development7–9,11–18. Here, to understand how interactions between microorganisms infuence root growth in Arabidopsis, we established a model system for interactions between plants, microorganisms and the environment. We inoculated seedlings with a 185-member bacterial synthetic community, manipulated the abiotic environment and measured bacterial colonization of the plant. This enabled us to classify the synthetic community into four modules of co-occurring strains. We deconstructed the synthetic community on the basis of these modules, and identifed interactions between microorganisms that determine root phenotype. These interactions primarily involve a single bacterial genus (Variovorax), which completely reverses the severe inhibition of root growth that is induced by a wide diversity of bacterial strains as well as by the entire 185-member community. We demonstrate that Variovorax manipulates plant hormone levels to balance the efects of our ecologically realistic synthetic root community on root growth. We identify an auxin-degradation operon that is conserved in all available genomes of Variovorax and is necessary and sufcient for the reversion of root growth inhibition. Therefore, metabolic signal interference shapes bacteria–plant communication networks and is essential for maintaining the stereotypic developmental programme of the root. Optimizing the feedbacks that shape chemical interaction networks in the rhizosphere provides a promising ecological strategy for developing more resilient and productive crops. Plant phenotypes, and ultimately fitness, are influenced by the micro- Plant hormones—in particular, auxins—are both produced and organisms that live in close association with them1–3. These micro- degraded by an abundance of plant-associated microorganisms15–18. organisms—collectively termed the plant microbiota—assemble on Microbially derived auxins can have effects on plants that range from the basis of plant and environmentally derived cues1,4–6, resulting in growth promotion to the induction of disease, depending on context myriad interactions between plants and microorganisms. Beneficial and concentration9. The intrinsic root developmental patterns of the and detrimental microbial effects on plants can be either direct3,7–9, or plant are dependent on finely calibrated auxin and ethylene concentra- an indirect consequence of microorganism–microorganism interac- tion gradients with fine differences across tissues and cell types19; it is tions2,10. Although antagonistic interactions between microorganisms not known how the plant integrates exogenous, microbially derived are known to have an important role in shaping plant microbiota and auxin fluxes into its developmental plan. protecting plants from pathogens2, another potentially important class Here we apply a synthetic community to axenic plants as a proxy of interactions is metabolic signal interference11,12: rather than direct for root-associated microbiomes in natural soils to investigate how antagonism, microorganisms interfere with the delivery of chemical interactions between microorganisms shape plant growth. We estab- signals produced by other microorganisms, which alters plant–micro- lish plant colonization patterns across 16 abiotic conditions to guide organism signalling12–14. stepwise deconstruction of the synthetic community, which led to the 1Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 2Howard Hughes Medical Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 3Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 4Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 5Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 6Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 7Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 8Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 9Present address: Department of Plant and Environmental Sciences, Institute of Life Science, The Hebrew University of Jerusalem, Jerusalem, Israel. 10Present address: Future Food Beacon of Excellence, School of Biosciences, University of Nottingham, Sutton Bonington, UK. 11Present address: Department of Biology, ‘Luiz de Queiroz’ College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, Brazil. 12These authors contributed equally: Omri M. Finkel, Isai Salas-González, Gabriel Castrillo, Jonathan M. Conway. ✉e-mail: [email protected] Nature | www.nature.com | 1 Article IQR IQR Cut-off RGI abRoot versus Shoot versus No bacteria Full substrate substrate NB Full Single modules Module pairs Pi NaClpH Pi NaClpH 8 Temp Temp T U Phosphate Salinity VW V UV UV 0 μM 50 mM W Module A 10 M 100 mM 6 μ X 30 μM 150 mM YZ 50 M 200 mM 4 YZ μ Y 100 μM Temperature Z 1,000 μM 10 °C 2 pH 21 °C 5.5 31 °C 7.0 0 8.2 Primary root elongation (cm) NB ABCD ABCD AB AC AD BC BD CD Module B cdSingle modules Module pairs Representative root growth inhibitors Module ABCDStrain Genus MF455 Mycobacterium MF220A Sphingomonas CL71 Acinetobacter MF45 Module C MF397 Pseudomonas ACDAC AD CL144 e Agar Soil Ralstonia CL21 8 YY MF384 Burkholderia CL11 6 YY MF4 Module D CL14 4 MF369 Z Z MF349 Variovorax 2 Module A isolates MF110 MF350 0 Primary root elongation (cm) MF160 Signicance q < 0.05 and MF375 CL14 CL28CL14CL28 CL14CL28CL14CL28 estimate > 2 5 MF278 Signicance –5.02.5 0 2. 5.0 True Actinobacteria Alphaproteobacteria Self q < 0.05 Bacteroidetes Firmicutes Fold change Gammaproteobacteria Primary root elongation (cm) CL28 MF48 MF107 MF224 Module A Module B Module C Module D Bacillus Burkholderiaceae Bacillaceae Rhizobiaceae Microbacteriaceae 0 2 4 6 8 Comamonadaceae Paenibacillaceae Micrococcaceae Arthrobacter Pseudomonas Moraxellaceae Streptomycetaceae Mycobacteriaceae Agrobacterium Nocardiaceae Fig. 1 | Arabidopsis root length is governed by bacteria–bacteria correspond to a Tukey post hoc test. n = 75, 89, 68, 94, 87, 77, 76, 96, 82, 84, 89 interactions within a community. a, Fraction enrichment patterns of the and 77 (from left to right) biological replicates across 2 independent synthetic community across abiotic gradients. Each row represents a unique experiments. c, Binarized image of representative seedlings inoculated with sequence. The four modules of co-occurring strains (A, B, C and D) are modules A, C and D, and with module combinations A–C and A–D. d, Heat map represented. Dendrogram tips are coloured by taxonomy. Heat maps are coloured by average primary root elongation of seedlings inoculated with four coloured by log2-transformed fold changes derived from a fitted generalized representative RGI-inducing strains from each module (columns A–D) in linear model and represent enrichments in plant tissue (root or shoot) combination with isolates from module A (rows) or alone (self). Significance compared with substrate. Comparisons with false-discovery-rate was determined via ANOVA. e, Primary root elongation of seedlings inoculated (FDR)-corrected q-value < 0.05 are contoured in black. Enriched families within with Arthrobacter CL28 and Variovorax CL14 individually or jointly across two each module are listed below the heat map. n = 6 biological replicates across substrates. Significance was determined via ANOVA, letters are the results of a 2 independent experiments. Pi, inorganic phosphate; temp, temperature. Tukey post hoc test. n = 64, 64, 63, 17, 36 and 33 (from left to right) biological b, Primary root elongation of seedlings grown axenically (no bacteria, NB), with replicates across 2 independent experiments. In all box plots, the centre line the full synthetic community (ABCD) or its subsets: modules A, B, C and D alone represents the median, box edges show the 25th and 75th percentiles, and (single modules), and all pairwise combination of modules (module pairs). whiskers extend to 1.5× the interquartile range (IQR). Significance was determined via analysis of variance (ANOVA); letters identification of multiple levels of microorganism–microorganism composed of the major root-associated phyla1,4–6,20 (Extended Data Fig. 1a, interaction that interfere with the additivity of bacterial effects on root Supplementary Table 1). We exposed this microcosm to each of 16 abiotic growth. We demonstrate that a single bacterial genus (Variovorax) is contexts by manipulating one of four variables (salinity, temperature, a required for maintaining the intrinsically controlled developmental previously reported phosphate concentration gradient5 and