The functional potential of the rhizospheric microbiome of an invasive tree species, Acacia dealbata
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Date
Authors
Kamutando, Casper N.
Vikram, Surendra
Makhalanyane, Thulani Peter
Greve, Michelle
Le Roux, Johannes J.
Richardson, David M.
Cowan, Don A.
Valverde, Angel
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
Plant-microbe interactions mediate both the invasiveness of introduced plant species and the impacts that they have in invaded ecosystems. Although the phylogenetic composition of the rhizospheric microbiome of Acacia dealbata (an invasive Australian tree species) has been investigated, little is known about the functional potential of the constituents of these altered microbial communities. We used shotgun DNA sequencing to better understand the link between bacterial community composition and functional capacity in the rhizospheric microbiomes associated with invasive A. dealbata populations in South Africa. Our analysis showed that several genes associated with plant growth-promoting (PGP) traits were significantly overrepresented in the rhizospheric metagenomes compared to neighbouring bulk soils collected away from A. dealbata stands. The majority of these genes are involved in the metabolism of nitrogen, carbohydrates and vitamins, and in various membrane transport systems. Overrepresented genes were linked to a limited number of bacterial taxa, mostly Bradyrhizobium species, the preferred N-fixing rhizobial symbiont of Australian acacias. Overall, these findings suggest that A. dealbata enriches rhizosphere soils with potentially beneficial microbial taxa, and that members of the genus Bradyrhizobium may play an integral role in mediating PGP processes that may influence the success of this invader when colonizing novel environments.
Description
Fig. S1. Principal coordinate analyses (PCoA) plot showing differences in taxonomic structure of microbial communities between the rhizosphere and bulk metagenomes.
Fig. S2. Principal coordinate analyses (PCoA) plot showing differences in microbial functions between the rhizosphere and bulk soils metagenomes.
Fig. S3. Venn diagrams showing the number of KEGG Orthologues (KOs) shared between rhizosphere and bulk soil metagenomes before (a) and after (b) statistical differentiation of significant functions of rhizosphere and bulk soil samples using the STAMP package.
Table S1. Sequence counts of the rhizosphere and bulk soil metagenomes. The total number of sequences before and after quality filtering, and coverage data of contigs ≥500 bp.
Table S2. Relative frequencies of open-reading frame (ORF) hit counts for microorganisms (phylum level) in each metagenome.
Table S3. Operational taxonomic units showing microbial taxa which were significantly overrepresented in rhizosphere and bulk soil metagenomes, based on protein-coding ORF data using the STAMP package.
Table S4. Genes overrepresented in either, the rhizosphere or bulk soil metagenomes, based on ORF data analysis using the STAMP package.
Table S5. Overrepresented genes of the rhizosphere and bulk soil metagenomes, identified using STAMP analysis of ORF hit counts, linked to their associated microbial taxa.
Table S6. Statistical information of the CONCOCT genome bins as revelled by CheckM analysis.
Table S7. Statistical information of the Anvio’s refined genome bins as revelled by CheckM analysis.
Table S8. Functional potential of the Bradyrhizobium genome based on RAST and KAAS annotations.
Table S9. Functional potential of the Geodermatophilus genome based on RAST and KAAS annotations.
Table S10. Functional potential of the Kribbela genome based on RAST and KAAS annotations.
Table S11. Functional potential of the Sphaerobacter genome based on RAST and KAAS annotations.
Fig. S2. Principal coordinate analyses (PCoA) plot showing differences in microbial functions between the rhizosphere and bulk soils metagenomes.
Fig. S3. Venn diagrams showing the number of KEGG Orthologues (KOs) shared between rhizosphere and bulk soil metagenomes before (a) and after (b) statistical differentiation of significant functions of rhizosphere and bulk soil samples using the STAMP package.
Table S1. Sequence counts of the rhizosphere and bulk soil metagenomes. The total number of sequences before and after quality filtering, and coverage data of contigs ≥500 bp.
Table S2. Relative frequencies of open-reading frame (ORF) hit counts for microorganisms (phylum level) in each metagenome.
Table S3. Operational taxonomic units showing microbial taxa which were significantly overrepresented in rhizosphere and bulk soil metagenomes, based on protein-coding ORF data using the STAMP package.
Table S4. Genes overrepresented in either, the rhizosphere or bulk soil metagenomes, based on ORF data analysis using the STAMP package.
Table S5. Overrepresented genes of the rhizosphere and bulk soil metagenomes, identified using STAMP analysis of ORF hit counts, linked to their associated microbial taxa.
Table S6. Statistical information of the CONCOCT genome bins as revelled by CheckM analysis.
Table S7. Statistical information of the Anvio’s refined genome bins as revelled by CheckM analysis.
Table S8. Functional potential of the Bradyrhizobium genome based on RAST and KAAS annotations.
Table S9. Functional potential of the Geodermatophilus genome based on RAST and KAAS annotations.
Table S10. Functional potential of the Kribbela genome based on RAST and KAAS annotations.
Table S11. Functional potential of the Sphaerobacter genome based on RAST and KAAS annotations.
Keywords
Biological invasions, Bradyrhizobium, Plant growth-promoting traits, Rhizosphere microbiome, Shotgun sequencing, Tree invasions
Sustainable Development Goals
Citation
Kamutando, C.N., Vikram, S., Kamgan-Nkuekam, G. et al. The Functional Potential of the Rhizospheric Microbiome of an Invasive Tree Species, Acacia dealbata. Microbial Ecology (2019) 77: 191. https://doi.org/10.1007/s00248-018-1214-0.