Mikael Rørdam Andersen

Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88

The filamentous fungus Aspergillus niger is widely exploited by the fermentation industry for the production of enzymes and organic acids, particularly citric acid. We sequenced the 33.9-megabase genome of A. niger CBS 513.88, the ancestor of currently used enzyme production strains. A high level of synteny was observed with other aspergilli sequenced. Strong function predictions were made for 6,506 of the 14,165 open reading frames identified. A detailed description of the components of the protein secretion pathway was made and striking differences in the hydrolytic enzyme spectra of aspergilli were observed. A reconstructed metabolic network comprising 1,069 unique reactions illustrates the versatile metabolism of A. niger. Noteworthy is the large number of major facilitator superfamily transporters and fungal zinc binuclear cluster transcription factors, and the presence of putative gene clusters for fumonisin and ochratoxin A synthesis.

The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line

Chinese hamster ovary (CHO)–derived cell lines are the preferred host cells for the production of therapeutic proteins. Here we present a draft genomic sequence of the CHO-K1 ancestral cell line. The assembly comprises 2.45 Gb of genomic sequence, with 24,383 predicted genes. We associate most of the assembled scaffolds with 21 chromosomes isolated by microfluidics to identify chromosomal locations of genes. Furthermore, we investigate genes involved in glycosylation, which affect therapeutic protein quality, and viral susceptibility genes, which are relevant to cell engineering and regulatory concerns. Homologs of most human glycosylation-associated genes are present in the CHO-K1 genome, although 141 of these homologs are not expressed under exponential growth conditions. Many important viral entry genes are also present in the genome but not expressed, which may explain the unusual viral resistance property of CHO cell lines. We discuss how the availability of this genome sequence may facilitate genome-scale science for the optimization of biopharmaceutical protein production.

Comparative genomics of citric-acid-producing Aspergillus niger ATCC 1015 versus enzyme-producing CBS 513.88

The filamentous fungus Aspergillus niger exhibits 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-producing A. niger strain (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 acidogenic A. niger wild-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.

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.

Accurate prediction of secondary metabolite gene clusters in filamentous fungi

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.

A trispecies Aspergillus microarray: Comparative transcriptomics of three Aspergillus species

The full-genome sequencing of the filamentous fungi Aspergillus nidulans, Aspergillus niger, and Aspergillus oryzae has opened possibilities for studying the cellular physiology of these fungi on a systemic level. As a tool to explore this, we are making available an Affymetrix GeneChip developed for transcriptome analysis of any of the three above-mentioned aspergilli. Transcriptome analysis of triplicate batch cultivations of all three aspergilli on glucose and xylose media was used to validate the performance of the microarray. Gene comparisons of all three species and cross-analysis with the expression data identified 23 genes to be a conserved response across Aspergillus sp., including the xylose transcriptional activator XlnR. A promoter analysis of the up-regulated genes in all three species indicates the conserved XlnR-binding site to be 5′-GGNTAAA-3′. The composition of the conserved gene-set suggests that xylose acts as a molecule, indicating the presence of complex carbohydrates such as hemicellulose, and triggers an array of degrading enzymes. With this case example, we present a validated tool for transcriptome analysis of three Aspergillus species and a methodology for conducting cross-species evolutionary studies within a genus using comparative transcriptomics.

Aggressive dereplication using UHPLC-DAD-QTOF: screening extracts for up to 3000 fungal secondary metabolites

In natural-product drug discovery, finding new compounds is the main task, and thus fast dereplication of known compounds is essential. This is usually performed by manual liquid chromatography-ultraviolet (LC-UV) or visible light-mass spectroscopy (Vis-MS) interpretation of detected peaks, often assisted by automated identification of previously identified compounds. We used a 15 min high-performance liquid chromatography–diode array detection (UHPLC–DAD)–high-resolution MS method (electrospray ionization (ESI)+ or ESI−), followed by 10–60 s of automated data analysis for up to 3000 relevant elemental compositions. By overlaying automatically generated extracted-ion chromatograms from detected compounds on the base peak chromatogram, all major potentially novel peaks could be visualized. Peaks corresponding to compounds available as reference standards, previously identified compounds, and major contaminants from solvents, media, filters etc. were labeled to differentiate these from compounds only identified by elemental composition. This enabled fast manual evaluation of both known peaks and potential novel-compound peaks, by manual verification of: the adduct pattern, UV–Vis, retention time compared with log D, co-identified biosynthetic related compounds, and elution order. System performance, including adduct patterns, in-source fragmentation, and ion-cooler bias, was investigated on reference standards, and the overall method was used on extracts of Aspergillus carbonarius and Penicillium melanoconidium, revealing new nitrogen-containing biomarkers for both species.

The 2008 update of the Aspergillus nidulans genome annotation: A community effort

The identification and annotation of protein-coding genes is one of the primary goals of whole-genome sequencing projects, and the accuracy of predicting the primary protein products of gene expression is vital to the interpretation of the available data and the design of downstream functional applications. Nevertheless, the comprehensive annotation of eukaryotic genomes remains a considerable challenge. Many genomes submitted to public databases, including those of major model organisms, contain significant numbers of wrong and incomplete gene predictions. We present a community-based reannotation of the Aspergillus nidulans genome with the primary goal of increasing the number and quality of protein functional assignments through the careful review of experts in the field of fungal biology.

Systemic analysis of the response of Aspergillus niger to ambient pH

BackgroundThe filamentous fungus Aspergillus niger is an exceptionally efficient producer of organic acids, which is one of the reasons for its relevance to industrial processes and commercial importance. While it is known that the mechanisms regulating this production are tied to the levels of ambient pH, the reasons and mechanisms for this are poorly understood.MethodsTo cast light on the connection between extracellular pH and acid production, we integrate results from two genome-based strategies: A novel method of genome-scale modeling of the response, and transcriptome analysis across three levels of pH.ResultsWith genome scale modeling with an optimization for extracellular proton-production, it was possible to reproduce the preferred pH levels for citrate and oxalate. Transcriptome analysis and clustering expanded upon these results and allowed the identification of 162 clusters with distinct transcription patterns across the different pH-levels examined. New and previously described pH-dependent cis-acting promoter elements were identified. Combining transcriptome data with genomic coordinates identified four pH-regulated secondary metabolite gene clusters. Integration of regulatory profiles with functional genomics led to the identification of candidate genes for all steps of the pal/pacC pH signalling pathway.ConclusionsThe combination of genome-scale modeling with comparative genomics and transcriptome analysis has provided systems-wide insights into the evolution of highly efficient acidification as well as production process applicable knowledge on the transcriptional regulation of pH response in the industrially important A. niger. It has also made clear that filamentous fungi have evolved to employ several offensive strategies for out-competing rival organisms.

Systems Analysis Unfolds the Relationship between the Phosphoketolase Pathway and Growth in Aspergillus nidulans

Background Aspergillus nidulans is an important model organism for studies on fundamental eukaryotic cell biology and on industrial processes due to its close relation to A. niger and A. oryzae. Here we identified the gene coding for a novel metabolic pathway in A. nidulans, namely the phosphoketolase pathway, and investigated the role of an increased phosphoketolase activity. Methodology/Principal Findings Over-expression of the phosphoketolase gene (phk) improved the specific growth rate on xylose, glycerol and ethanol. Transcriptome analysis showed that a total of 1,222 genes were significantly affected by over-expression of the phk, while more than half of the affected genes were carbon source specific. During growth on glucose medium, the transcriptome analysis showed that the response to phk over-expression is targeted to neutralize the effect of the over-expression by regulating the acetate metabolism and initiate a growth dampening response. Conclusions/Significance Metabolic flux analysis using 13C-labelled glucose, showed that over-expression of phosphoketolase added flexibility to the central metabolism. Our findings further suggests that A. nidulans is not optimized for growth on xylose, glycerol or ethanol as the sole carbon sources.