Microbiological Research · 2020 · 32 citations · 52 references
AgriculturePlant BiologyPlant SciencesMicrobial EcologyPlant-microbe InteractionsSoil MicrobiologyMicrobial Community ProfilingPlant Growth-promoting MicroorganismsPlant Growth-promoting RhizobacteriaPlant-associated Microbial CommunitiesPlant-pathogenic FungiSoil Pathogens16S Ribosomal Ribonucleic Acid (Rrna) SequencingBacterial Operational Taxonomic UnitsCrop Growth PromotionCulture-dependent Microbial EcologyCulture-dependent Microbial IdentificationEndophytic Microbial CommunitiesMaize MicrobiologyOperational Taxonomic Unit Profiling
Endophytic microbial-communities have specific beneficial functions and are considered key drivers for host plant health. The removing-PCR (R-PCR) is a simple culture-independent cost-effective method to identify endophytic microbial-communities. Microbial communities from maize plant grown in different soil types were identified and characterized via the R-PCR and 16S rRNA sequencing. Culture-dependent microbial community identified through 16S rRNA gene sequencing, further these bacterial communities screened for antagonistic assay against Rhizoctonia solani WH1, in vitro compatibility tests, plant-growth-promoting traits and BIOLOG identification. After that, synthetic-communities (SycomA and SycomB) were prepared by mixing different compatible bacterial-strains to use as an inoculant to suppress pathogens of maize. We identified 167 bacterial operational taxonomic units (OTUs) and unexpected 8 fungal OTUs through the R-PCR, whereas, 95 bacterial OTUs via 16S rRNA sequencing from maize leaves and roots. SycomA and SycomB treatments suppressed the disease level and promoted growth attributes more effectively as compare to the single bacterial-strain and control treatments. This study establishes an efficient approach to isolate, identify and characterize diverse endophytic microbial-community assembly in maize leaves and roots, to successfully apply particular microbes to improve crop growth in soils affected by soil-borne-pathogens.
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Edward Simpson · Nature · 1949 · 14K citations · Full text
PyNAST: a flexible tool for aligning sequences to a template alignment
J. Gregory Caporaso, Kyle Bittinger, Frederic D. Bushman et al. · Bioinformatics · 2009 · 3.5K citations · Full text