Metabolic model integration of the bibliome, genome, metabolome and reactome of Aspergillus niger

The release of the genome sequences of two strains of Aspergillus niger has allowed systems-level investigations of this important microbial cell factory. To this end, tools for doing data integration of multi-ome data are necessary, and especially interesting in the context of metabolism. On the basis of an A. niger bibliome survey, we present the largest model reconstruction of a metabolic network reported for a fungal species. The reconstructed gapless metabolic network is based on the reportings of 371 articles and comprises 1190 biochemically unique reactions and 871 ORFs. Inclusion of isoenzymes increases the total number of reactions to 2240. A graphical map of the metabolic network is presented. All levels of the reconstruction process were based on manual curation. From the reconstructed metabolic network, a mathematical model was constructed and validated with data on yields, fluxes and transcription. The presented metabolic network and map are useful tools for examining systemwide data in a metabolic context. Results from the validated model show a great potential for expanding the use of A. niger as a high-yield production platform

Isolation and identification of Sclerotinia stem rot causal pathogen in Arabidopsis thaliana * §

A new stem rot disease is found to occur naturally on Arabidopsis plants in greenhouses of Fuzhou, China. In order to identify its pathogen, we conducted a series of fungal isolation and purification, plant reinoculation, and ascus and ascospore induction from the sclerotia. The isolate caused typical water-soaked lesions after reinoculation and produced sclerotia both on Arabidopsis plants and culture medium plates, and the sclerotia could be induced to produce discal apothecia and 8 binucleate ascospores per ascus. These disease symptom and fungal morphology data revealed that the fungus Sclerotinia sclerotiorum (Lib.) de Bary was the pathogen for Arabidopsis stem rot. To confirm this, we further amplified its large subunit ribosomal DNA (LSU rDNA) by polymerase chain reaction (PCR), and compared the sequence with the known LSU rDNA sequences in GenBank. The results show that the sequence shares the highest identities with the LSU rDNAs of different S. sclerotiorum strains. Taking all these data together, we concluded that the fungus that caused the Arabidopsis stem rot is S. sclerotiorum (Lib.) de Bary. This is the first report that Arabidopsis is naturally infected by S. sclerotiorum