Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 Jun 16;9(6):e99641.
doi: 10.1371/journal.pone.0099641. eCollection 2014.

Understanding cultivar-specificity and soil determinants of the cannabis microbiome

Affiliations

Understanding cultivar-specificity and soil determinants of the cannabis microbiome

Max E Winston et al. PLoS One. .

Erratum in

  • PLoS One. 2014;9(9):e107415. Hartsel, Josh [corrected to Hartsel, Joshua A]

Abstract

Understanding microbial partnerships with the medicinally and economically important crop Cannabis has the potential to affect agricultural practice by improving plant fitness and production yield. Furthermore, Cannabis presents an interesting model to explore plant-microbiome interactions as it produces numerous secondary metabolic compounds. Here we present the first description of the endorhiza-, rhizosphere-, and bulk soil-associated microbiome of five distinct Cannabis cultivars. Bacterial communities of the endorhiza showed significant cultivar-specificity. When controlling cultivar and soil type the microbial community structure was significantly different between plant cultivars, soil types, and between the endorhiza, rhizosphere and soil. The influence of soil type, plant cultivar and sample type differentiation on the microbial community structure provides support for a previously published two-tier selection model, whereby community composition across sample types is determined mainly by soil type, while community structure within endorhiza samples is determined mainly by host cultivar.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: Despite the fact that authors Josh Hartsel and Suzanne Kennedy work for commercial companies Cannavest and MO BIO Laboratories, respectively, this does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. PCoA plots of microbial community similarity in first experiment for unweighted analysis (A–B) and weighted analysis (C–D).
Plots for unweighted analysis are based on unweighted UniFrac distance, and demonstrate relationship between sample type (A), strain (B), and the major PC axes (PC 1 = 26.46% variance, PC 2 = 7.36% variance). Plots for weighted analysis are based on weighted UniFrac distances, and demonstrate relationship between sample type (C), strain (D), and the major PC axes (PC 1 = 62.98% variance, PC 2 = 15.43% variance). Abbreviations for strains are denoted by B (Burmese), BK (BooKoo Kush), and D (Sour Diesel).
Figure 2
Figure 2. PCoA plots of microbial community similarity in second experiment for unweighted analysis (A–C) and weighted analysis (D–F).
Plots for unweighted analysis are based on unweighted UniFrac distances, and demonstrate relationship between soil type (A), sample type (B), strain (C), and the major PC axes (PC 1 = 32.06% variance, PC 2 = 11.34% variance, PC 3 = 5.67% variance). Plots for weighted analysis are based on weighted UniFrac distances, and demonstrate relationship between soil type (D), sample type (E), strain (F), and the major PC axes (PC 1 = 34.51% variance, PC 2 = 25.41% variance, PC 3 = 19.31% variance). Note that PC 1 in the unweighted analysis is dominated by variation in soil type (A), but PC 1 in weighted analysis is dominated by strain (F). Grey points (Fig. 2c, 2f) represent bulk soil samples that aren't associated with either strain. Abbreviations for strains are denoted by MW (Mauie Wowie) and WW (White Widow), and abbreviations for soil type are denoted by MB (Mo-Bio soil) and OC (Orange County soil).
Figure 3
Figure 3. PCoA plots of microbial community similarity in pooled experiments for unweighted analysis (A–C) and weighted analysis (D–F).
Plots for unweighted analysis are based on unweighted UniFrac distance, and demonstrate relationship between soil type (A), sample type (B), strain (C), and the major PC axes (PC 1 = 13.27% variance, PC 2 = 10.15% variance, PC 3 = 6.15% variance). Plots for weighted analysis are based on weighted UniFrac distances, and demonstrate relationship between soil type (D) sample type (E), strain (F), and the major PC axes (PC 1 = 37.69% variance, PC 2 = 13.95% variance, PC 3 = 11.07% variance). Abbreviations for strains are denoted by B (Burmese), BK (BooKoo Kush), D (Sour Diesel), MW (Mauie Wowie) and WW (White Widow). Abbreviations for soil type are denoted by MB1 (Mo-Bio soil from the first experiment), MB2 (Mo-Bio soil from the second experiment) and OC (Orange County soil).
Figure 4
Figure 4. Ternary plot of distribution of bacterial taxonomic groups among sample types in the second experiment.
Size of circles proportional to the log of the total abundance, taxonomic groups are all phylum-level, except for Proteobacteria, which is by class.
Figure 5
Figure 5. Box plots of beta-diversity distances between communities for both weighted and unweighted analyses.
Initials (i.e. B vs. C) stand for comparisons of beta-distances for samples within groups (R =  rhizosphere, C =  Cannabis endorhiza, B =  bulk soil).
Figure 6
Figure 6. Box plots of alpha diversity (observed species) for endorhiza, rhizosphere, and bulk soil from two separate soil types in the second eperiment.
MB  =  Mo-Bio soil, OC  =  Orange County soil. Note the significant differences between alpha diversity in the bulk soil and rhizosphere but negligible differences between endorhiza alpha diversity between soil types.

Similar articles

Cited by

References

    1. Swift MJ, Izac MN, van Noordwijk M (2004) Biodiversity and ecosystem services in agricultural landscapes—are we asking the right questions? Agricult Ecosys Environ 104: 113–134.
    1. Mendes R, Kruijt M, de Bruijn I, Dekkers E, van der Voort M, et al. (2011) Deciphering the rhizosphere microbiome for disease-suppressive bacteria. Science 332: 1097–100. - PubMed
    1. Doornbos RF, Loon LCV, Bakker PAHM (2011) Impact of induced systemic resistance on the bacterial microbiome of Arabidopsis thaliana. Multitrophic Interactions in Soil 71: 169–172.
    1. Berendsen RL, Pieterse CMJ, Bakker PHM (2012) The rhizosphere microbiome and plant health. Trends Plant Sci 1–9. - PubMed
    1. Whipps JM (2001) Microbial interactions and biocontrol in the rhizosphere. J Exp Bot 52: 487–511. - PubMed

Publication types