The filamentous fungusAspergillus nigerexhibits great diversity in its phenotype. It is found globally, both as marine and terrestrial strains, produces both organic acids and hydrolytic enzymes in high amounts, and some isolates exhibit pathogenicity. Although the genome of an industrial enzyme-producingA. nigerstrain (CBS 513.88) has already been sequenced, the versatility and diversity of this species compel additional exploration. We therefore undertook whole-genome sequencing of the acidogenicA. nigerwild-type strain (ATCC 1015) and produced a genome sequence of very high quality. Only 15 gaps are present in the sequence, and half the telomeric regions have been elucidated. Moreover, sequence information from ATCC 1015 was used to improve the genome sequence of CBS 513.88. Chromosome-level comparisons uncovered several genome rearrangements, deletions, a clear case of strain-specific horizontal gene transfer, and identification of 0.8 Mb of novel sequence. Single nucleotide polymorphisms per kilobase (SNPs/kb) between the two strains were found to be exceptionally high (average: 7.8, maximum: 160 SNPs/kb). High variation within the species was confirmed with exo-metabolite profiling and phylogenetics. Detailed lists of alleles were generated, and genotypic differences were observed to accumulate in metabolic pathways essential to acid production and protein synthesis. A transcriptome analysis supported up-regulation of genes associated with biosynthesis of amino acids that are abundant in glucoamylase A, tRNA-synthases, and protein transporters in the protein producing CBS 513.88 strain. Our results and data sets from this integrative systems biology analysis resulted in a snapshot of fungal evolution and will support further optimization of cell factories based on filamentous fungi.
Aspergillus section Nigri comprises filamentous fungi relevant to biomedicine, bioenergy, health, and biotechnology. To learn more about what genetically sets these species apart, as well as about potential applications in biotechnology and biomedicine, we sequenced 23 genomes de novo, forming a full genome compendium for the section (26 species), as well as 6 Aspergillus niger isolates. This allowed us to quantify both inter- and intraspecies genomic variation. We further predicted 17,903 carbohydrate-active enzymes and 2,717 secondary metabolite gene clusters, which we condensed into 455 distinct families corresponding to compound classes, 49% of which are only found in single species. We performed metabolomics and genetic engineering to correlate genotypes to phenotypes, as demonstrated for the metabolite aurasperone, and by heterologous transfer of citrate production to Aspergillus nidulans. Experimental and computational analyses showed that both secondary metabolism and regulation are key factors that are significant in the delineation of Aspergillus species.
17 December 2012 in Proceedings of the National Academy of Sciences
Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association–based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.