Linuron-mineralizing cultures were enriched from two linuron-treated agricultural soils in the presence and absence of a solid support. The cultures contained linuron-degrading bacteria, which coexisted with bacteria degrading either 3,4-dichloroaniline (3,4-DCA) or N,O-dimethylhydroxylamine (N,O-DMHA), two common metabolites in the linuron degradation pathway. For one soil, the presence of a solid support enriched for linuron-degrading strains phylogenetically related to but different from those enriched without support. Most linuron-degrading consortium members were identified as Variovorax, but a Hydrogenophaga and an Achromobacter strain capable of linuron degradation were also obtained. Several of the linuron-degrading isolates also degraded 3,4-DCA. Isolates that degraded 3,4-DCA but not linuron belonged to the genera Variovorax, Cupriavidus and Afipia. Hyphomicrobium spp. were involved in the metabolism of N,O-DMHA. Whereas several isolates degraded linuron independently, more efficient degradation was achieved by combining linuron and 3,4-DCA-degraders or by adding casamino acids. These data suggest that (1) linuron degradation is performed by a group of metabolically interacting bacteria rather than by individual strains, (2) there are other genera in addition to Variovorax that degrade linuron beyond 3,4-DCA, (3) linuron-degrading consortia of different origins have a similar composition, and (4) interactions between consortium members can be complex and can involve exchange of both metabolites and other nutrients.

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Abstract13C-based metabolic flux analysis is an excellent technique to resolve fluxes in the central carbon metabolism but costs can be significant when using specialized tracers. This work presents a framework for cost-effective design of 13 C-tracer experiments, illustrated on two different networks.Linear and non-linear optimal input mixtures are computed for networks high amounts of 1,2-13 C 2 glucose combined with uniformly labelled glucose.Experimental designs are evaluated based on a linear (D-criterion) and nonlinear approach (S-criterion). Both approaches generate almost the same input mixture, however, the linear approach is favoured due to its low computational effort. The high amount of 1,2-13 C 2 glucose in the optimal designs coincides with a high experimental cost, which is further enhanced when la-