FEMS Microbiology Ecology · 2020 · 10 citations · 54 references
Life SciencesEcologyMicrobiologyMicrobial EcologyMicrobiome ResearchPlant-microbe InteractionsBacterial EcologyPlant Growth-promoting MicroorganismsPlant MicrobiomePlant-associated Microbial CommunitiesRoot MicrobiomeRoot-microbe InteractionsEndophyte ColonizationEndophyte EcologyEndophytic ColonizationEndophytic Plant Growth PromotionEndophytic Root MicrobiomeMicrobial Colonization Of RootsRhizosphere Bacterial CommunitiesRoot Growth Promotion
Root endophytes are a promising tool for increasing plant growth, but it is unclear whether they perform consistently across plant hosts. We characterized the blue grama (Bouteloua gracilis) root microbiome using two sequencing methods, quantified the effects of root endophytes in the original host (blue grama) and an agricultural recipient, corn (Zea mays), under drought and well-watered conditions and examined in vitro mechanisms for plant growth promotion. 16S rRNA amplicon sequencing revealed that the blue grama root microbiome was similar across an elevation gradient, with the exception of four genera. Culturing and Sanger sequencing revealed eight unique endophytes belonging to the genera Bacillus, Lysinibacillus and Pseudomonas. All eight endophytes colonized corn roots, but had opposing effects on aboveground and belowground biomass in each plant species: they increased blue grama shoot mass by 45% (19) (mean +/- SE) while decreasing corn shoot mass by 10% (19), and increased corn root:shoot by 44% (7), while decreasing blue grama root:shoot by 17% (7). Furthermore, contrary to our expectations, endophytes had stronger effects on plant growth under well-watered conditions rather than drought conditions. Collectively, these results suggest that ecological features, including host identity, bacterial traits, climate conditions and morphological outcomes, should be carefully considered in the design and implementation of agricultural inocula.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Douglas M. Bates, Martin Mächler, Benjamin M. Bolker et al. · Journal of Statistical Software · 2015 · 85.6K citations · Full text
Search and clustering orders of magnitude faster than BLAST
R. C. Edgar · Bioinformatics · 2010 · 21.7K citations · Full text