While plant pathogens are traditionally controlled using synthetic agrochemicals the availability of commercial bactericides is still limited. One potential control strategy could be the use of plant-growth-promoting bacteria (PGPBs) to suppress pathogens via resource competition or the production of antimicrobial compounds. This study aimed to conduct in vitro and in vivo screening of eight Pseudomonas strains against Ralstonia solanacearum (the causative agent of bacterial wilt) and to investigate underlying mechanisms of potential pathogen suppression. We found that inhibitory effects were Pseudomonas strain-specific, with strain CHA0 showing the highest pathogen suppression. Genomic screening identified 2, 4-diacetylphloroglucinol (DAPG), pyoluteorin, and orfamides A and B secondary metabolite clusters in the genomes of the most inhibitory strains, which were investigated further. While all these compounds suppressed R. solanacearum growth, only Orfamide A was produced in the growth media based on mass spectrometry. Moreover, orfamide variants extracted from Pseudomonas cultures showed high pathogen suppression. Using the Micro Tom tomato cultivar, it was found that CHA0 could reduce bacterial wilt disease incidence with one of the two tested pathogen strains. Together, these findings suggest that a better understanding of Pseudomonas-Ralstonia interactions in the rhizosphere is required to successfully translate in vitro findings into agricultural applications.

Background: Sequencing and PCR errors are a major challenge when characterising genetic diversity using high-throughput amplicon sequencing (HTAS). Results: We have developed a multiplexed HTAS method, MAUI-seq, which uses unique molecular identifiers (UMIs) to improve error correction by exploiting variation among sequences associated with a single UMI. We show that two main advantages of this approach are efficient elimination of chimeric and other erroneous reads, outperforming DADA2 and UNOISE3, and the ability to confidently recognise genuine alleles that are present at low abundance or resemble chimeras. Conclusions: The method provides sensitive and flexible profiling of diversity and is readily adaptable to most HTAS applications, including microbial 16S rRNA profiling and metabarcoding of environmental DNA.