High bacterial diversity and siderophore-producing bacteria collectively suppress Fusarium oxysporum in maize/faba bean intercropping

Abstract

Beyond interacting with neighboring plants, crop performance is affected by the microbiome that includes pathogens and mutualists. While the importance of plant–plant interactions in explaining overyielding in intercropping is well known, the role of the microbiome, in particular how the presence of microbes from heterospecific crop species inhibit pathogens of the focal plants in affecting yield remains hardly explored. Here we performed both field samplings and pot experiments to investigate the microbial interactions in the maize/faba bean intercropping system, with the focus on the inhibition of Fusarium oxysporum in faba bean plants. Long-term field measurements show that maize/faba bean intercropping increased crop yield, reduced the gene copies of F. oxysporum by 30–84% and increased bacterial richness and Shannon index compared to monocropping. Bacterial networks in intercropping were more stable with more hub nodes than the respective monocultures. Furthermore, the observed changes of whole microbial communities were aligned with differences in the number of siderophore-producing rhizobacteria in maize and pathogen abundances in faba bean. Maize possessed 71% more siderophore-producing rhizobacteria and 33% more synthetases genes abundance of nonribosomal peptides, especially pyochelin, relative to faba bean. This was further evidenced by the increased numbers of siderophore-producing bacteria and decreased gene copies of F. oxysporum in the rhizosphere of intercropped faba bean. Four bacteria (Pseudomonas spp. B004 and B021, Bacillus spp. B005 and B208) from 95 isolates antagonized F. oxysporum f. sp. fabae. In particular, B005, which represented a hub node in the networks, showed particularly high siderophore-producing capabilities. Intercropping increased overall bacterial diversity and network complexity and the abundance of siderophore-producing bacteria, leading to facilitated pathogen suppression and increased resistance of faba bean to F. oxysporum. This study has great agronomic implications as microorganisms might be specifically targeted to optimize intercropping practices in the future.

The Effect of Two Siderophore-Producing Bacillus Strains on the Growth Promotion of Perennial Ryegrass under Cadmium Stress

“…Some bacteria can adsorb heavy metal ions through functionally active groups and protein groups on the surface of their cell wall, or they can precipitate and chelate heavy metals through protein binding [ 58 ]. Siderophores can chelate cadmium ions in the soil, increasing their bioavailability and thus promoting their absorption by and translocation into plants.…”

The Cultured Microbiome of Pollinated Maize Silks Shifts after Infection with Fusarium graminearum and Varies by Distance from the Site of Pathogen Inoculation

“…Out of 389 unique cultured OTUs (from healthy and F. graminearum-treated silks), there were 11 OTUs which were prevalent in both healthy and F. graminearum-treated silks, defined here as cultured from at least three host genotypes of each treatment. These conserved taxa were OTUs 117,119,130,158,271,276,290,292,372,374 and 375 (Figure 8). Apart from cultured OTUs that were prevalent in both treatments, we were also interested in identifying OTUs that were prevalent specifically to the F. graminearum-treated silks, which could be used to develop microbial molecular markers to help breeders select potentially defensive silk microbes-increasing their abundance and stability and/or stacking them together in a single hybrid.…”

Watering Shapes a Robust and Stable Microbial Community under Fusarium Crown Rot Infection

“…The correlation matrixes of the co-occurrence network were constructed by the rcorr function of the "Hmisc" package based on the Spearman method, and the OTUs with relative abundance < 0.1% were removed to reduce the bias of calculation and to ensure accuracy [35]. The robust correlations (|Spearman correlation coefficient| > 0.60 and p < 0.05) were used for co-occurrence network construction, and the Benjamini-Hochberg method was used to verify and adjust the p values [36].…”