Crop host signatures reflected by co-association patterns of keystone Bacteria in the rhizosphere microbiota

Environ Microbiome. 2021 Oct 12;16(1):18. doi: 10.1186/s40793-021-00387-w.

Abstract

Background: The native crop bacterial microbiota of the rhizosphere is envisioned to be engineered for sustainable agriculture. This requires the identification of keystone rhizosphere Bacteria and an understanding on how these govern crop-specific microbiome assembly from soils. We identified the metabolically active bacterial microbiota (SSU RNA) inhabiting two compartments of the rhizosphere of wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), rye (Secale cereale), and oilseed rape (Brassica napus L.) at different growth stages.

Results: Based on metabarcoding analysis the bacterial microbiota was shaped by the two rhizosphere compartments, i.e. close and distant. Thereby implying a different spatial extent of bacterial microbiota acquirement by the cereals species versus oilseed rape. We derived core microbiota of each crop species. Massilia (barley and wheat) and unclassified Chloroflexi of group 'KD4-96' (oilseed rape) were identified as keystone Bacteria by combining LEfSe biomarker and network analyses. Subsequently, differential associations between networks of each crop species' core microbiota revealed host plant-specific interconnections for specific genera, such as the unclassified Tepidisphaeraceae 'WD2101 soil group'.

Conclusions: Our results provide keystone rhizosphere Bacteria derived from for crop hosts and revealed that cohort subnetworks and differential associations elucidated host species effect that was not evident from differential abundance of single bacterial genera enriched or unique to a specific plant host. Thus, we underline the importance of co-occurrence patterns within the rhizosphere microbiota that emerge in crop-specific microbiomes, which will be essential to modify native crop microbiomes for future agriculture and to develop effective bio-fertilizers.

Keywords: 16S rRNA; Amplicon sequencing; Barley; Co-occurrence network; LEfSe; Oilseed rape; RNA; Rye; Wheat.