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Ruiter, R.

Publications and source records attributed to Ruiter, R..

2 recordsLinked to original sources

Pseudomonas virulence factor SaxA detoxifies plant glucosinolate hydrolysis products, rescuing a commensal that suppresses virulence gene expression

Plants produce a plethora of specialised metabolites that often play important roles in their defence against pathogenic microbes or herbivorous insects. Exposure of leaf colonising microbes to these metabolites influences their growth and we hypothesize that it also has consequences for microbe-microbe interactions and bacterial recruitment to leaves. In Brassicaceae plants like the model plant Arabidopsis thaliana, glucosinolates and their biologically active derivatives, the isothiocyanates, are major defence metabolites. Adapted plant pathogens like Pseudomonas spp. use the hydrolase SaxA to convert the antimicrobial isothiocyanate sulforaphane to a non-toxic amine, whereas non-adapted commensal microbes are inhibited by this plant toxin. We used Plantibacter sp. 2H11-2 as a model commensal in co-culture with either Pseudomonas viridiflava 3D9 wildtype or a saxA-knock-out mutant. Both strains were isolated from the same wild A. thaliana population. Without isothiocyanate, Plantibacter grew better alone than with Pseudomonas, a potential competitor. At high isothiocyanate concentrations, however, the commensal was dependent on SaxA-mediated isothiocyanate degradation in both solid and liquid medium. At intermediate isothiocyanate concentrations, Plantibacters transcriptome changed in response to sulforaphane in mono-culture but not in co-culture with Pseudomonas, suggesting it was fully protected from this toxin. In return, Plantibacter caused transcriptional changes in Pseudomonas, suppressing biofilm formation and increasing amino acids metabolism gene expression which might suppress virulence and so contribute to plant health. Together, we find that an antimicrobial plant metabolite can force a commensal to depend on a pathogen-produced virulence factor, but that the interaction overall might benefit the plant by limiting pathogenicity.

microbiology↗

Search for early pancreatic cancer blood biomarkers in five European prospective population biobanks using metabolomics

Background and aimMost patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. MethodsThe low incidence rate complicates prospective biomarker studies. Here, we took advantage of the availability of biobanked samples from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian biobank, Rotterdam Study) and identified prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between one month and seventeen years after blood sampling, and compared these with age- and gender-matched controls from the same cohorts. We applied 1H-NMR-based metabolomics on the Nightingale platform on these samples and applied logistic regression to assess the predictive value of individual metabolite concentrations, with gender, age, body mass index, smoking status, type 2 diabetes mellitus status, fasting status, and cohort as covariates. ResultsAfter quality assessment, we retained 356 cases and 887 controls. We identified two interesting hits, glutamine (p=0.011) and histidine (p=0.012), and obtained Westfall-Young family-wise error rate adjusted p-values of 0.43 for both. Stratification in quintiles showed a 1.5x elevated risk for the lowest 20% of glutamine and a 2.2x increased risk for the lowest 20% of histidine. Stratification by time to diagnosis (<2 years, 2-5 years, >5 years) suggested glutamine to be involved in an earlier process, tapering out closer to onset, and histidine in a process closer to the actual onset. Lasso-penalized logistic regression showed a slight improvement of the area under the Receiver Operator Curves when including glutamine and histidine in the model. Finally, our data did not support the earlier identified branched-chain amino acids as potential biomarkers for pancreatic cancer in several American cohorts. ConclusionWhile identifying glutamine and histidine as early biomarkers of potential biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers.

epidemiology↗