Biosynthetic Potential of the Endophytic Fungus Helotiales sp. BL73 Revealed via Compound Identification and Genome Mining.

Endophytic fungi have been recognized as prolific producers of chemically diverse secondary metabolites. In this work, we describe a new representative of the order Helotiales isolated from the medicinal plant Bergenia pacumbis. Several bioactive secondary metabolites were produced by this Helotiales sp. BL 73 isolate grown on rice medium, including cochlioquinones and isofusidienols. Sequencing and analysis of the approximately 59-Mb genome revealed at least 77 secondary metabolite biosynthesis gene clusters, of which several could be associated with detected compounds or linked to previously reported molecules. Four terpene synthase genes identified in the BL73 genome were codon optimized and expressed, together with farnesyl-, geranyl-, and geranylgeranyl-pyrophosphate synthases, in Streptomyces spp. An analysis of recombinant strains revealed the production of linalool and its oxidized form, terpenoids typically associated with plants, as well as a yet unidentified terpenoid. This study demonstrates the importance of a complex approach to the investigation of the biosynthetic potential of endophytic fungi using both conventional methods and genome mining. IMPORTANCE Endophytic fungi represent an as yet underexplored source of secondary metabolites, of which some may have industrial and medical applications. We isolated a slow-growing fungus belonging to the order Helotiales from the traditional medicinal plant Bergenia pacumbis and characterized its potential to biosynthesize secondary metabolites. We used cultivation of the isolate with a subsequent analysis of compounds produced, bioinformatics-based mining of the genome, and heterologous expression of several terpene synthase genes. Our study revealed that this Helotiales isolate has enormous potential to produce structurally diverse natural products, including polyketides, nonribosomally synthesized peptides, terpenoids, and ribosomally synthesized and posttranslationally modified peptides (RiPPs). Identification of meroterpenoids and xanthones, along with establishing a link between these molecules and their putative biosynthetic genes, sets the stage for investigation of the respective biosynthetic pathways. The heterologous production of terpenoids suggests that this approach can be used for the discovery of new compounds belonging to this chemical class using Streptomyces bacteria as hosts.

FunOrder: A robust and semi-automated method for the identification of essential biosynthetic genes through computational molecular co-evolution.

Secondary metabolites (SMs) are a vast group of compounds with different structures and properties that have been utilized as drugs, food additives, dyes, and as monomers for novel plastics. In many cases, the biosynthesis of SMs is catalysed by enzymes whose corresponding genes are co-localized in the genome in biosynthetic gene clusters (BGCs). Notably, BGCs may contain so-called gap genes, that are not involved in the biosynthesis of the SM. Current genome mining tools can identify BGCs, but they have problems with distinguishing essential genes from gap genes. This can and must be done by expensive, laborious, and time-consuming comparative genomic approaches or transcriptome analyses. In this study, we developed a method that allows semi-automated identification of essential genes in a BGC based on co-evolution analysis. To this end, the protein sequences of a BGC are blasted against a suitable proteome database. For each protein, a phylogenetic tree is created. The trees are compared by treeKO to detect co-evolution. The results of this comparison are visualized in different output formats, which are compared visually. Our results suggest that co-evolution is commonly occurring within BGCs, albeit not all, and that especially those genes that encode for enzymes of the biosynthetic pathway are co-evolutionary linked and can be identified with FunOrder. In light of the growing number of genomic data available, this will contribute to the studies of BGCs in native hosts and facilitate heterologous expression in other organisms with the aim of the discovery of novel SMs.

Genome sequencing of the neotype strain CBS 554.65 reveals the MAT1-2 locus of Aspergillus niger.

BACKGROUND: Aspergillus niger is a ubiquitous filamentous fungus widely employed as a cell factory thanks to its abilities to produce a wide range of organic acids and enzymes. Its genome was one of the first Aspergillus genomes to be sequenced in 2007, due to its economic importance and its role as model organism to study fungal fermentation. Nowadays, the genome sequences of more than 20 A. niger strains are available. These, however, do not include the neotype strain CBS 554.65. RESULTS: The genome of CBS 554.65 was sequenced with PacBio. A high-quality nuclear genome sequence consisting of 17 contigs with a N50 value of 4.07 Mbp was obtained. The assembly covered all the 8 centromeric regions of the chromosomes. In addition, a complete circular mitochondrial DNA assembly was obtained. Bioinformatic analyses revealed the presence of a MAT1-2-1 gene in this genome, contrary to the most commonly used A. niger strains, such as ATCC 1015 and CBS 513.88, which contain a MAT1-1-1 gene. A nucleotide alignment showed a different orientation of the MAT1-1 locus of ATCC 1015 compared to the MAT1-2 locus of CBS 554.65, relative to conserved genes flanking the MAT locus. Within 24 newly sequenced isolates of A. niger half of them had a MAT1-1 locus and the other half a MAT1-2 locus. The genomic organization of the MAT1-2 locus in CBS 554.65 is similar to other Aspergillus species. In contrast, the region comprising the MAT1-1 locus is flipped in all sequenced strains of A. niger. CONCLUSIONS: This study, besides providing a high-quality genome sequence of an important A. niger strain, suggests the occurrence of genetic flipping or switching events at the MAT1-1 locus of A. niger. These results provide new insights in the mating system of A. niger and could contribute to the investigation and potential discovery of sexuality in this species long thought to be asexual.

A quantitative metabolic analysis reveals Acetobacterium woodii as a flexible and robust host for formate-based bioproduction.

Cheap and renewable feedstocks such as the one-carbon substrate formate are emerging for sustainable production in a growing chemical industry. We investigated the acetogen Acetobacterium woodii as a potential host for bioproduction from formate alone and together with autotrophic and heterotrophic co-substrates by quantitatively analyzing physiology, transcriptome, and proteome in chemostat cultivations in combination with computational analyses. Continuous cultivations with a specific growth rate of 0.05 h-1 on formate showed high specific substrate uptake rates (47 mmol g-1 h-1). Co-utilization of formate with H2, CO, CO2 or fructose was achieved without catabolite repression and with acetate as the sole metabolic product. A transcriptomic comparison of all growth conditions revealed a distinct adaptation of A. woodii to growth on formate as 570 genes were changed in their transcript level. Transcriptome and proteome showed higher expression of the Wood-Ljungdahl pathway during growth on formate and gaseous substrates, underlining its function during utilization of one-carbon substrates. Flux balance analysis showed varying flux levels for the WLP (0.7-16.4 mmol g-1 h-1) and major differences in redox and energy metabolism. Growth on formate, H2/CO2, and formate + H2/CO2 resulted in low energy availability (0.20-0.22 ATP/acetate) which was increased during co-utilization with CO or fructose (0.31 ATP/acetate for formate + H2/CO/CO2, 0.75 ATP/acetate for formate + fructose). Unitrophic and mixotrophic conversion of all substrates was further characterized by high energetic efficiencies. In silico analysis of bioproduction of ethanol and lactate from formate and autotrophic and heterotrophic co-substrates showed promising energetic efficiencies (70-92%). Collectively, our findings reveal A. woodii as a promising host for flexible and simultaneous bioconversion of multiple substrates, underline the potential of substrate co-utilization to improve the energy availability of acetogens and encourage metabolic engineering of acetogenic bacteria for the efficient synthesis of bulk chemicals and fuels from sustainable one carbon substrates.

Novel approach in whole genome mining and transcriptome analysis reveal conserved RiPPs in Trichoderma spp.

BACKGROUND: Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a highly diverse group of secondary metabolites (SM) of bacterial and fungal origin. While RiPPs have been intensively studied in bacteria, little is known about fungal RiPPs. In Fungi only six classes of RiPPs are described. Current strategies for genome mining are based on these six known classes. However, the genes involved in the biosynthesis of theses RiPPs are normally organized in biosynthetic gene clusters (BGC) in fungi. RESULTS: Here we describe a comprehensive strategy to mine fungal genomes for RiPPs by combining and adapting existing tools (e.g. antiSMASH and RiPPMiner) followed by extensive manual curation based on conserved domain identification, (comparative) phylogenetic analysis, and RNASeq data. Deploying this strategy, we could successfully rediscover already known fungal RiPPs. Further, we analysed four fungal genomes from the Trichoderma genus. We were able to find novel potential RiPP BGCs in Trichoderma using our unconventional mining approach. CONCLUSION: We demonstrate that the unusual mining approach using tools developed for bacteria can be used in fungi, when carefully curated. Our study is the first report of the potential of Trichoderma to produce RiPPs, the detected clusters encode novel uncharacterized RiPPs. The method described in our study will lead to further mining efforts in all subdivisions of the fungal kingdom.

Evaluation of reference genes for transcript analyses in Komagataella phaffii (Pichia pastoris).

BACKGROUND: The yeast Komagataella phaffii (Pichia pastoris) is routinely used for heterologous protein expression and is suggested as a model organism for yeast. Despite its importance and application potential, no reference gene for transcript analysis via RT-qPCR assays has been evaluated to date. In this study, we searched publicly available RNASeq data for stably expressed genes to find potential reference genes for relative transcript analysis by RT-qPCR in K. phaffii. To evaluate the applicability of these genes, we used a diverse set of samples from three different strains and a broad range of cultivation conditions. The transcript levels of 9 genes were measured and compared using commonly applied bioinformatic tools. RESULTS: We could demonstrate that the often-used reference gene ACT1 is not very stably expressed and could identify two genes with outstandingly low transcript level fluctuations. Consequently, we suggest the two genes, RSC1, and TAF10 to be simultaneously used as reference genes in transcript analyses by RT-qPCR in K. phaffii in future RT-qPCR assays. CONCLUSION: The usage of ACT1 as a reference gene in RT-qPCR analysis might lead to distorted results due to the instability of its transcript levels. In this study, we evaluated the transcript levels of several genes and found RSC1 and TAF10 to be extremely stable. Using these genes holds the promise for reliable RT-qPCR results.

FunOrder 2.0 - a method for the fully automated curation of co-evolved genes in fungal biosynthetic gene clusters.

Coevolution is an important biological process that shapes interacting proteins - may it be physically interacting proteins or consecutive enzymes in a metabolic pathway, such as the biosynthetic pathways for secondary metabolites. Previously, we developed FunOrder, a semi-automated method for the detection of co-evolved genes, and demonstrated that FunOrder can be used to identify essential genes in biosynthetic gene clusters from different ascomycetes. A major drawback of this original method was the need for a manual assessment, which may create a user bias and prevents a high-throughput application. Here we present a fully automated version of this method termed FunOrder 2.0. In the improved version, we use several mathematical indices to determine the optimal number of clusters in the FunOrder output, and a subsequent k-means clustering based on the first three principal components of a principal component analysis of the FunOrder output to automatically detect co-evolved genes. Further, we replaced the BLAST tool with the DIAMOND tool as a prerequisite for using larger proteome databases. Potentially, FunOrder 2.0 may be used for the assessment of complete genomes, which has not been attempted yet. However, the introduced changes slightly decreased the sensitivity of this method, which is outweighed by enhanced overall speed and specificity.

Genome Sequence of the Black Yeast-Like Strain Aureobasidium pullulans var. aubasidani CBS 100524.

In this work, we present the whole-genome sequence and the complete mitochondrial sequence of the black yeast-like strain Aureobasidium pullulans var. aubasidani CBS 100524, which produces the exopolysaccharide aubasidan and was previously isolated from Betula sp. slime flux from the Leningrad Region of Russia.