Current Insights into the Role of Rhizosphere Bacteria in Disease Suppressive Soils

Disease suppressive soils offer effective protection to plants against infection by soil-borne pathogens, including fungi, oomycetes, bacteria, and nematodes. The specific disease suppression that operates in these soils is, in most cases, microbial in origin. Therefore, suppressive soils are considered as a rich resource for the discovery of beneficial microorganisms with novel antimicrobial and other plant protective traits. To date, several microbial genera have been proposed as key players in disease suppressiveness of soils, but the complexity of the microbial interactions as well as the underlying mechanisms and microbial traits remain elusive for most disease suppressive soils. Recent developments in next generation sequencing and other ‘omics’ technologies have provided new insights into the microbial ecology of disease suppressive soils and the identification of microbial consortia and traits involved in disease suppressiveness. Here, we review the results of recent ‘omics’-based studies on the microbial basis of disease suppressive soils, with specific emphasis on the role of rhizosphere bacteria in this intriguing microbiological phenomenon

Synthetic Sequencing Standards : A Guide to Database Choice for Rumen Microbiota Amplicon Sequencing Analysis

Our understanding of complex microbial communities, such as those residing in the rumen, has drastically advanced through the use of high throughput sequencing (HTS) technologies. Indeed, with the use of barcoded amplicon sequencing, it is now cost effective and computationally feasible to identify individual rumen microbial genera associated with ruminant livestock nutrition, genetics, performance and greenhouse gas production. However, across all disciplines of microbial ecology, there is currently little reporting of the use of internal controls for validating HTS results. Furthermore, there is little consensus of the most appropriate reference database for analyzing rumen microbiota amplicon sequencing data. Therefore, in this study, a synthetic rumen-specific sequencing standard was used to assess the effects of database choice on results obtained from rumen microbial amplicon sequencing. Four DADA2 reference training sets (RDP, SILVA, GTDB, and RefSeq + RDP) were compared to assess their ability to correctly classify sequences included in the rumen-specific sequencing standard. In addition, two thresholds of phylogenetic bootstrapping, 50 and 80, were applied to investigate the effect of increasing stringency. Sequence classification differences were apparent amongst the databases. For example the classification of Clostridium differed between all databases, thus highlighting the need for a consistent approach to nomenclature amongst different reference databases. It is hoped the effect of database on taxonomic classification observed in this study, will encourage research groups across various microbial disciplines to develop and routinely use their own microbiome-specific reference standard to validate analysis pipelines and database choice.</p

Differently Pre-treated Alfalfa Silages Affect the in vitro Ruminal Microbiota Composition

Alfalfa (Medicago sativa L.) silage (AS) is an important feedstuff in ruminant nutrition. However, its high non-protein nitrogen content often leads to poor ruminal nitrogen retention. Various pre-ensiling treatments differing with respect to dry matter concentrations, wilting intensities and sucrose addition have been previously shown to improve the quality and true protein preservation of AS, and have substantial effects on in vitro ruminal fermentation of the resulting silages. However, it is unknown how these pre-ensiling treatments affect the ruminal microbiota composition, and whether alterations in the microbiota explain previously observed differences in ruminal fermentation. Therefore, during AS incubation in a rumen simulation system, liquid and solid phases were sampled 2 and 7 days after first incubating AS, representing an early (ET) and late (LT) time point, respectively. Subsequently, DNA was extracted and qPCR (bacteria, archaea, and anaerobic fungi) and prokaryotic 16S rRNA gene amplicon sequence analyses were performed. At the ET, high dry matter concentration and sucrose addition increased concentrations of archaea in the liquid phase (P = 0.001) and anaerobic fungi in the solid phase (P < 0.001). At the LT, only sucrose addition increased archaeal concentration in the liquid phase (P = 0.014) and anaerobic fungal concentration in the solid phase (P < 0.001). Bacterial concentrations were not affected by pre-ensiling treatments. The prokaryotic phylogenetic diversity index decreased in the liquid phase from ET to LT (P = 0.034), whereas the solid phase was not affected (P = 0.060). This is suggestive of a general adaption of the microbiota to the soluble metabolites released from the incubated AS, particularly regarding the sucrose-treated AS. Redundancy analysis of the sequence data at the genus level indicated that sucrose addition (P = 0.001), time point (P = 0.001), and their interaction (P = 0.001) affected microbial community composition in both phases. In summary, of the pre-ensiling treatments tested sucrose addition had the largest effect on the microbiota, and together with sampling time point affected microbiota composition in both phases of the rumen simulation system. Thus, microbiota composition analysis helped to understand the ruminal fermentation patterns, but could not fully explain them

Comparative genomics and metabolic profiling of the genus Lysobacter

Background: Lysobacter species are Gram-negative bacteria widely distributed in soil, plant and freshwater habitats. Lysobacter owes its name to the lytic effects on other microorganisms. To better understand their ecology and interactions with other (micro)organisms, five Lysobacter strains representing the four species L. enzymogenes, L. capsici, L. gummosus and L. antibioticus were subjected to genomics and metabolomics analyses. Results: Comparative genomics revealed a diverse genome content among the Lysobacter species with a core genome of 2,891 and a pangenome of 10,028 coding sequences. Genes encoding type I, II, III, IV, V secretion systems and type IV pili were highly conserved in all five genomes, whereas type VI secretion systems were only found in L. enzymogenes and L. gummosus. Genes encoding components of the flagellar apparatus were absent in the two sequenced L. antibioticus strains. The genomes contained a large number of genes encoding extracellular enzymes including chitinases, glucanases and peptidases. Various nonribosomal peptide synthase (NRPS) and polyketide synthase (PKS) gene clusters encoding putative bioactive metabolites were identified but only few of these clusters were shared between the different species. Metabolic profiling by imaging mass spectrometry complemented, in part, the in silico genome analyses and allowed visualisation of the spatial distribution patterns of several secondary metabolites produced by or induced in Lysobacter species during interactions with the soil-borne fungus Rhizoctonia solani. Conclusions: Our work shows that mining the genomes of Lysobacter species in combination with metabolic profiling provides novel insights into the genomic and metabolic potential of this widely distributed but understudied and versatile bacterial genus

Impact of the fungal pathogen Fusarium oxysporum on the taxonomic and functional diversity of the common bean root microbiome

Abstract Background Plants rely on their root microbiome as the first line of defense against soil-borne fungal pathogens. The abundance and activities of beneficial root microbial taxa at the time prior to and during fungal infection are key to their protective success. If and how invading fungal root pathogens can disrupt microbiome assembly and gene expression is still largely unknown. Here, we investigated the impact of the fungal pathogen Fusarium oxysporum (fox) on the assembly of rhizosphere and endosphere microbiomes of a fox-susceptible and fox-resistant common bean cultivar. Results Integration of 16S-amplicon, shotgun metagenome as well as metatranscriptome sequencing with community ecology analysis showed that fox infections significantly changed the composition and gene expression of the root microbiome in a cultivar-dependent manner. More specifically, fox infection led to increased microbial diversity, network complexity, and a higher proportion of the genera Flavobacterium, Bacillus, and Dyadobacter in the rhizosphere of the fox-resistant cultivar compared to the fox-susceptible cultivar. In the endosphere, root infection also led to changes in community assembly, with a higher abundance of the genera Sinorhizobium and Ensifer in the fox-resistant cultivar. Metagenome and metatranscriptome analyses further revealed the enrichment of terpene biosynthesis genes with a potential role in pathogen suppression in the fox-resistant cultivar upon fungal pathogen invasion. Conclusion Collectively, these results revealed a cultivar-dependent enrichment of specific bacterial genera and the activation of putative disease-suppressive functions in the rhizosphere and endosphere microbiome of common bean under siege