Updating genome annotation for the microbial cell factory Aspergillus niger using gene co-expression networks

What is new in FungiDB: a web-based bioinformatics platform for omics-scale data analysis for fungal and oomycete species

FungiDB (https://fungidb.org) serves as a valuable online resource that seamlessly integrates genomic and related large-scale data for a wide range of fungal and oomycete species. As an integral part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org), FungiDB continually integrates both published and unpublished data addressing various aspects of fungal biology. Established in early 2011, the database has evolved to support 674 datasets. The datasets include over 300 genomes spanning various taxa (e.g. Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, as well as Albuginales, Peronosporales, Pythiales, and Saprolegniales). In addition to genomic assemblies and annotation, over 300 extra datasets encompassing diverse information, such as expression and variation data, are also available. The resource also provides an intuitive web-based interface, facilitating comprehensive approaches to data mining and visualization. Users can test their hypotheses and navigate through omics-scale datasets using a built-in search strategy system. Moreover, FungiDB offers capabilities for private data analysis via the integrated VEuPathDB Galaxy platform. FungiDB also permits genome improvements by capturing expert knowledge through the User Comments system and the Apollo genome annotation editor for structural and functional gene curation. FungiDB facilitates data exploration and analysis and contributes to advancing research efforts by capturing expert knowledge for fungal and oomycete species.

Breaking down barriers: comprehensive functional analysis of the Aspergillus niger chitin synthase repertoire

BACKGROUND

Members of the fungal kingdom are heterotrophic eukaryotes encased in a chitin containing cell wall. This polymer is vital for cell wall stiffness and, ultimately, cell shape. Most fungal genomes contain numerous putative chitin synthase encoding genes. However, systematic functional analysis of the full chitin synthase catalogue in a given species is rare. This greatly limits fundamental understanding and potential applications of manipulating chitin synthesis across the fungal kingdom.

RESULTS

In this study, we conducted in silico profiling and subsequently deleted all predicted chitin synthase encoding genes in the multipurpose cell factory Aspergillus niger. Phylogenetic analysis suggested nine chitin synthases evolved as three distinct groups. Transcript profiling and co-expression network construction revealed remarkably independent expression, strongly supporting specific role(s) for the respective chitin synthases. Deletion mutants confirmed all genes were dispensable for germination, yet impacted colony spore titres, chitin content at hyphal septa, and internal architecture of submerged fungal pellets. We were also able to assign specific roles to individual chitin synthases, including those impacting colony radial growth rates (ChsE, ChsF), lateral cell wall chitin content (CsmA), chemical genetic interactions with a secreted antifungal protein (CsmA, CsmB, ChsE, ChsF), resistance to therapeutics (ChsE), and those that modulated pellet diameter in liquid culture (ChsA, ChsB). From an applied perspective, we show chsF deletion increases total protein in culture supernatant over threefold compared to the control strain, indicating engineering filamentous fungal chitin content is a high priority yet underexplored strategy for strain optimization.

CONCLUSION

This study has conducted extensive analysis for the full chitin synthase encoding gene repertoire of A. niger. For the first time we reveal both redundant and non-redundant functional roles of chitin synthases in this fungus. Our data shed light on the complex, multifaceted, and dynamic role of chitin in fungal growth, morphology, survival, and secretion, thus improving fundamental understanding and opening new avenues for biotechnological applications in fungi.

CryptoCEN: A Co-Expression Network for Cryptococcus neoformans reveals novel proteins involved in DNA damage repair

Elucidating gene function is a major goal in biology, especially among non-model organisms. However, doing so is complicated by the fact that molecular conservation does not always mirror functional conservation, and that complex relationships among genes are responsible for encoding pathways and higher-order biological processes. Co-expression, a promising approach for predicting gene function, relies on the general principal that genes with similar expression patterns across multiple conditions will likely be involved in the same biological process. For Cryptococcus neoformans, a prevalent human fungal pathogen greatly diverged from model yeasts, approximately 60% of the predicted genes in the genome lack functional annotations. Here, we leveraged a large amount of publicly available transcriptomic data to generate a C. neoformans Co-Expression Network (CryptoCEN), successfully recapitulating known protein networks, predicting gene function, and enabling insights into the principles influencing co-expression. With 100% predictive accuracy, we used CryptoCEN to identify 13 new DNA damage response genes, underscoring the utility of guilt-by-association for determining gene function. Overall, co-expression is a powerful tool for uncovering gene function, and decreases the experimental tests needed to identify functions for currently under-annotated genes.

Genome-wide prediction and transcriptome analysis of sugar transporters in four ascomycete fungi

The import of plant-derived small sugars by sugar transporters (STs) has received increasing interest due to its important biological role and great industrial potential. STs are important targets of genetic engineering to improve fungal plant biomass conversion. Comparatively analysis of the genome-wide prevalence and transcriptomics of STs was performed in four filamentous fungi: Aspergillus niger, Aspergillus nidulans, Penicillium subrubescens and Trichoderma reesei. Using phylogenetic analysis and literature mining, their predicted STs were divided into ten subfamilies with putative sugar specificities assigned. In addition, transcriptome analysis revealed complex expression profiles among different STs subfamilies and fungal species, indicating a sophisticated transcriptome regulation and functional diversity of fungal STs. Several STs showed strong co-expression with other genes involved in sugar utilization, encoding CAZymes and sugar catabolic enzymes. This study provides new insights into the diversity of STs at the genomic/transcriptomic level, facilitating their biochemical characterization and metabolic engineering.

Metabolomic and transcriptomic analyses reveal comparisons against liquid-state fermentation of primary dark tea, green tea and white tea by Aspergillus cristatus

Liquid-state fermentation (LSF) of tea leaves is a promising way to obtain tea-based nutraceutical products rich in various bioactive compounds. In the study, the changes of bioactive compounds, tea pigments and complex metabolites from LSF of primary dark tea, green tea and white tea infusions with Aspergillus cristatus were determined. Chemical analyses revealed that soluble sugars, monosaccharide composition, total polyphenols, total flavonoids, free amino acids, soluble proteins and tea pigments were changed in different ways. An untargeted metabolomic analysis and ribonucleic acid sequencing (RNA-seq) based transcriptomic analysis were performed to investigate the metabolic differentiation and clarify the key differentially expressed genes (DEGs, fold change >2 and p < 0.05), showing that amino acid metabolism, carbohydrate metabolism and lipid metabolism were the most enriched pathways during A. cristatus fermentation of primary dark tea, green tea and white tea infusions. In addition, glycerophospholipid metabolism, linoleic acid metabolism and phenylalanine metabolism were greatly accumulated in the fermentation of primary dark tea and white tea infusions; Pyruvate metabolism, glycolysis/gluconeogenesis, fatty acid degradation, tyrosine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis and valine and leucine, isoleucine degradation were greatly accumulated in the fermentation of primary dark tea and green tea infusions; Starch and sucrose metabolism was greatly accumulated in the fermentation of green tea and white tea infusions; Galactose metabolism was significantly enhanced in the fermentation of primary dark tea infusion; Amino sugar and nucleotide sugar metabolism, sphingolipid metabolism and alanine, aspartate and glutamate metabolism were significantly enhanced in the fermentation of green tea infusion. Besides, some other pathways involving aminobenzoate degradation, biosynthesis of cofactors, pyrimidine metabolism, benzoxazinoid biosynthesis and phenazine biosynthesis, tropane, piperidine and pyridine alkaloid biosynthesis and flavone and flavonol biosynthesis also differed from each other. These findings support that A. cristatus plays a vital role in the biochemical and genetic regulation of metabolite profile, and could be considered a potential prospect for better use of A. cristatus on different kinds of tea materials.

CryptoCEN: A Co-Expression Network for Cryptococcus neoformans reveals novel proteins involved in DNA damage repair

Elucidating gene function is a major goal in biology, especially among non-model organisms. However, doing so is complicated by the fact that molecular conservation does not always mirror functional conservation, and that complex relationships among genes are responsible for encoding pathways and higher-order biological processes. Co-expression, a promising approach for predicting gene function, relies on the general principal that genes with similar expression patterns across multiple conditions will likely be involved in the same biological process. For Cryptococcus neoformans, a prevalent human fungal pathogen greatly diverged from model yeasts, approximately 60% of the predicted genes in the genome lack functional annotations. Here, we leveraged a large amount of publicly available transcriptomic data to generate a C. neoformans Co-Expression Network (CryptoCEN), successfully recapitulating known protein networks, predicting gene function, and enabling insights into the principles influencing co-expression. With 100% predictive accuracy, we used CryptoCEN to identify 13 new DNA damage response genes, underscoring the utility of guilt-by-association for determining gene function. Overall, co-expression is a powerful tool for uncovering gene function, and decreases the experimental tests needed to identify functions for currently under-annotated genes.

Regression modelling of conditional morphogene expression links and quantifies the impact of growth rate, fitness and macromorphology with protein secretion in Aspergillus niger

BACKGROUND

Filamentous fungi are used as industrial cell factories to produce a diverse portfolio of proteins, organic acids, and secondary metabolites in submerged fermentation. Generating optimized strains for maximum product titres relies on a complex interplay of molecular, cellular, morphological, and macromorphological factors that are not yet fully understood.

RESULTS

In this study, we generate six conditional expression mutants in the protein producing ascomycete Aspergillus niger and use them as tools to reverse engineer factors which impact total secreted protein during submerged growth. By harnessing gene coexpression network data, we bioinformatically predicted six morphology and productivity associated 'morphogenes', and placed them under control of a conditional Tet-on gene switch using CRISPR-Cas genome editing. Strains were phenotypically screened on solid and liquid media following titration of morphogene expression, generating quantitative measurements of growth rate, filamentous morphology, response to various abiotic perturbations, Euclidean parameters of submerged macromorphologies, and total secreted protein. These data were built into a multiple linear regression model, which identified radial growth rate and fitness under heat stress as positively correlated with protein titres. In contrast, diameter of submerged pellets and cell wall integrity were negatively associated with productivity. Remarkably, our model predicts over 60% of variation in A. niger secreted protein titres is dependent on these four variables, suggesting that they play crucial roles in productivity and are high priority processes to be targeted in future engineering programs. Additionally, this study suggests A. niger dlpA and crzA genes are promising new leads for enhancing protein titres during fermentation.

CONCLUSIONS

Taken together this study has identified several potential genetic leads for maximizing protein titres, delivered a suite of chassis strains with user controllable macromorphologies during pilot fermentation studies, and has quantified four crucial factors which impact secreted protein titres in A. niger.

Biochemical characterization of a glycoside hydrolase family 43 β-D-galactofuranosidase from the fungus Aspergillus niger

β-D-Galactofuranose (Galf) and its polysaccharides are found in bacteria, fungi and protozoa but do not occur in mammalian tissues, and thus represent a specific target for anti-pathogenic drugs. Understanding the enzymatic degradation of these polysaccharides is therefore of great interest, but the identity of fungal enzymes with exclusively galactofuranosidase activity has so far remained elusive. Here we describe the identification and characterization of a galactofuranosidase from the industrially important fungus Aspergillus niger. Analysis of glycoside hydrolase family 43 subfamily 34 (GH43_34) members via conserved unique peptide patterns and phylogeny, revealed the occurrence of distinct clusters and, by comparison with specificities of characterized bacterial members, suggested a basis for prediction of enzyme specificity. Using this rationale, in tandem with molecular docking, we identified a putative β-D-galactofuranosidase from A. niger which was recombinantly produced in Escherichia coli. The Galf-specific hydrolase, encoded by xynD demonstrates maximum activity at pH 5, 25 °C towards 4-nitrophenyl-β-galactofuranoside (pNP-β-Galf), with a K_m of 17.9 ± 1.9 mM and V_max of 70.6 ± 5.3 µM min^-1. The characterization of this first fungal GH43 galactofuranosidase offers further molecular insight into the degradation of Galf-containing structures.

The importance of complete and high-quality genome sequences in Aspergillus niger research

The possibility to sequence the entire genome of an organism revolutionized the fields of biology and biotechnology. The first genome sequence of the important filamentous fungus Aspergillus niger was obtained in 2007, 11 years after the release of the first eukaryotic genome sequence. From that moment, genomics of A. niger has seen major progresses, facilitated by the advances in the sequencing technologies and in the methodologies for gene function prediction. However, there are still challenges to face when trying to obtain complete genomes, equipped with all the repetitive sequences that they contain and without omitting the mitochondrial sequences. The aim of this perspective article is to discuss the current status of A. niger genomics and draw attention to the open challenges that the fungal community should address to move research of this important fungus forward.

Evaluation of Aspergillus niger Six Constitutive Strong Promoters by Fluorescent-Auxotrophic Selection Coupled with Flow Cytometry: A Case for Citric Acid Production

Aspergillus niger is an important industrial workhorse for the biomanufacturing of organic acids, proteins, etc. Well-controlled genetic regulatory elements, including promoters, are vital for strain engineering, but available strong promoters for A. niger are limited. Herein, to efficiently assess promoters, we developed an accurate and intuitive fluorescent-auxotrophic selection workflow based on mCherry, pyrG, CRISPR/Cas9 system, and flow cytometry. With this workflow, we characterized six endogenous constitutive promoters in A. niger. The endogenous glyceraldehyde-3-phosphate dehydrogenase promoter PgpdAg showed a 2.28-fold increase in promoter activity compared with the most frequently used strong promoter PgpdAd from A. nidulans. Six predicted conserved motifs, including the gpdA-box, were verified to be essential for the PgpdAg activity. To demonstrate its application, the promoter PgpdAg was used for enhancing the expression of citrate exporter cexA in a citric acid-producing isolate D353.8. Compared with the cexA controlled by PgpdAd, the transcription level of the cexA gene driven by PgpdAg increased by 2.19-fold, which is consistent with the promoter activity assessment. Moreover, following cexA overexpression, several genes involved in carbohydrate transport and metabolism were synergically upregulated, resulting in up to a 2.48-fold increase in citric acid titer compared with that of the parent strain. This study provides an intuitive workflow to speed up the quantitative evaluation of A. niger promoters and strong constitutive promoters for fungal cell factory construction and strain engineering.

Comprehensively dissecting the hub regulation of PkaC on high-productivity and pellet macromorphology in citric acid producing Aspergillus niger

Aspergillus niger, an important industrial workhorse for citric acid production, is characterized by polar hyphal growth with complex pelleted, clumped or dispersed macromorphologies in submerged culture. Although organic acid titres are dramatically impacted by these growth types, studies that assess productivity and macromorphological changes are limited. Herein, we functionally analysed the role of the protein kinase A (PKA)/cyclic adenosine monophosphate (cAMP) signalling cascade during fermentation by disrupting and conditionally expressing the pkaC gene. pkaC played multiple roles during hyphal, colony and conidiophore growth. By overexpressing pkaC, we could concomitantly modify hyphal growth at the pellet surface and improve citric acid titres up to 1.87‐fold. By quantitatively analysing hundreds of pellets during pilot fermentation experiments, we provide the first comprehensive correlation between A. niger pellet surface morphology and citric acid production. Finally, by intracellular metabolomics analysis and weighted gene coexpression network analysis (WGCNA) following titration of pkaC expression, we unveil the metabolomic and transcriptomic basis underpin hyperproductivity and pellet growth. Taken together, this study confirms pkaC as hub regulator linking submerged macromorphology and citric acid production and provides high‐priority genetic leads for future strain engineering programmes.

Natural Variation and the Role of Zn2Cys6 Transcription Factors SdrA, WarA and WarB in Sorbic Acid Resistance of Aspergillus niger

Weak acids, such as sorbic acid, are used as chemical food preservatives by the industry. Fungi overcome this weak-acid stress by inducing cellular responses mediated by transcription factors. In our research, a large-scale sorbic acid resistance screening was performed on 100 A. niger sensu stricto strains isolated from various sources to study strain variability in sorbic acid resistance. The minimal inhibitory concentration of undissociated (MIC_u) sorbic acid at pH = 4 in the MEB of the A. niger strains varies between 4.0 mM and 7.0 mM, with the average out of 100 strains being 4.8 ± 0.8 mM, when scored after 28 days. MIC_u values were roughly 1 mM lower when tested in commercial ice tea. Genome sequencing of the most sorbic-acid-sensitive strain among the isolates revealed a premature stop codon inside the sorbic acid response regulator encoding gene sdrA. Repairing this missense mutation increased the sorbic acid resistance, showing that the sorbic-acid-sensitive phenotype of this strain is caused by the loss of SdrA function. To identify additional transcription factors involved in weak-acid resistance, a transcription factor knock-out library consisting of 240 A. niger deletion strains was screened. The screen identified a novel transcription factor, WarB, which contributes to the resistance against a broad range of weak acids, including sorbic acid. The roles of SdrA, WarA and WarB in weak-acid resistance, including sorbic acid, were compared by creating single, double and the triple knock-out strains. All three transcription factors were found to have an additive effect on the sorbic acid stress response.

A Library of Aspergillus niger Chassis Strains for Morphology Engineering Connects Strain Fitness and Filamentous Growth With Submerged Macromorphology

Submerged fermentation using filamentous fungal cell factories is used to produce a diverse portfolio of useful molecules, including food, medicines, enzymes, and platform chemicals. Depending on strain background and abiotic culture conditions, different macromorphologies are formed during fermentation, ranging from dispersed hyphal fragments to approximately spherical pellets several millimetres in diameter. These macromorphologies are known to have a critical impact on product titres and rheological performance of the bioreactor. Pilot productivity screens in different macromorphological contexts is technically challenging, time consuming, and thus a significant limitation to achieving maximum product titres. To address this bottleneck, we developed a library of conditional expression mutants in the organic, protein, and secondary metabolite cell factory Aspergillus niger. Thirteen morphology-associated genes transcribed during fermentation were placed via CRISPR-Cas9 under control of a synthetic Tet-on gene switch. Quantitative analysis of submerged growth reveals that these strains have distinct and titratable macromorphologies for use as chassis during strain engineering programs. We also used this library as a tool to quantify how pellet formation is connected with strain fitness and filamentous growth. Using multiple linear regression modelling, we predict that pellet formation is dependent largely on strain fitness, whereas pellet Euclidian parameters depend on fitness and hyphal branching. Finally, we have shown that conditional expression of the putative kinase encoding gene pkh2 can decouple fitness, dry weight, pellet macromorphology, and culture heterogeneity. We hypothesize that further analysis of this gene product and the cell wall integrity pathway in which it is embedded will enable more precise engineering of A. niger macromorphology in future.

Machine learning prediction of novel pectinolytic enzymes in Aspergillus niger through integrating heterogeneous (post-) genomics data

Pectinolytic enzymes are a variety of enzymes involved in breaking down pectin, a complex and abundant plant cell-wall polysaccharide. In nature, pectinolytic enzymes play an essential role in allowing bacteria and fungi to depolymerize and utilize pectin. In addition, pectinases have been widely applied in various industries, such as the food, wine, textile, paper and pulp industries. Due to their important biological function and increasing industrial potential, discovery of novel pectinolytic enzymes has received global interest. However, traditional enzyme characterization relies heavily on biochemical experiments, which are time consuming, laborious and expensive. To accelerate identification of novel pectinolytic enzymes, an automatic approach is needed. We developed a machine learning (ML) approach for predicting pectinases in the industrial workhorse fungus, Aspergillus niger. The prediction integrated a diverse range of features, including evolutionary profile, gene expression, transcriptional regulation and biochemical characteristics. Results on both the training and the independent testing dataset showed that our method achieved over 90 % accuracy, and recalled over 60 % of pectinolytic genes. Application of the ML model on the A. niger genome led to the identification of 83 pectinases, covering both previously described pectinases and novel pectinases that do not belong to any known pectinolytic enzyme family. Our study demonstrated the tremendous potential of ML in discovery of new industrial enzymes through integrating heterogeneous (post-) genomimcs data.

Leveraging machine learning essentiality predictions and chemogenomic interactions to identify antifungal targets

Fungal pathogens pose a global threat to human health, with Candida albicans among the leading killers. Systematic analysis of essential genes provides a powerful strategy to discover potential antifungal targets. Here, we build a machine learning model to generate genome-wide gene essentiality predictions for C. albicans and expand the largest functional genomics resource in this pathogen (the GRACE collection) by 866 genes. Using this model and chemogenomic analyses, we define the function of three uncharacterized essential genes with roles in kinetochore function, mitochondrial integrity, and translation, and identify the glutaminyl-tRNA synthetase Gln4 as the target of N-pyrimidinyl-β-thiophenylacrylamide (NP-BTA), an antifungal compound.

Beyond the Biosynthetic Gene Cluster Paradigm: Genome-Wide Coexpression Networks Connect Clustered and Unclustered Transcription Factors to Secondary Metabolic Pathways

Fungal secondary metabolites are widely used as therapeutics and are vital components of drug discovery programs. A major challenge hindering discovery of novel secondary metabolites is that the underlying pathways involved in their biosynthesis are transcriptionally silent under typical laboratory growth conditions, making it difficult to identify the transcriptional networks that they are embedded in. Furthermore, while the genes participating in secondary metabolic pathways are typically found in contiguous clusters on the genome, known as biosynthetic gene clusters (BGCs), this is not always the case, especially for global and pathway-specific regulators of pathways’ activities. To address these challenges, we used 283 genome-wide gene expression data sets of the ascomycete cell factory Aspergillus niger generated during growth under 155 different conditions to construct two gene coexpression networks based on Spearman’s correlation coefficients (SCCs) and on mutual rank-transformed Pearson’s correlation coefficients (MR-PCCs). By mining these networks, we predicted six transcription factors, named MjkA to MjkF, to regulate secondary metabolism in A. niger. Overexpression of each transcription factor using the Tet-On cassette modulated the production of multiple secondary metabolites. We found that the SCC and MR-PCC approaches complemented each other, enabling the delineation of putative global (SCC) and pathway-specific (MR-PCC) transcription factors. These results highlight the potential of coexpression network approaches to identify and activate fungal secondary metabolic pathways and their products. More broadly, we argue that drug discovery programs in fungi should move beyond the BGC paradigm and focus on understanding the global regulatory networks in which secondary metabolic pathways are embedded.

IMPORTANCE There is an urgent need for novel bioactive molecules in both agriculture and medicine. The genomes of fungi are thought to contain vast numbers of metabolic pathways involved in the biosynthesis of secondary metabolites with diverse bioactivities. Because these metabolites are biosynthesized only under specific conditions, the vast majority of the fungal pharmacopeia awaits discovery. To discover the genetic networks that regulate the activity of secondary metabolites, we examined the genome-wide profiles of gene activity of the cell factory Aspergillus niger across hundreds of conditions. By constructing global networks that link genes with similar activities across conditions, we identified six putative global and pathway-specific regulators of secondary metabolite biosynthesis. Our study shows that elucidating the behavior of the genetic networks of fungi under diverse conditions harbors enormous promise for understanding fungal secondary metabolism, which ultimately may lead to novel drug candidates.

Profiling of chromatin accessibility identifies transcription factor binding sites across the genome of Aspergillus species

Background

The identification of open chromatin regions and transcription factor binding sites (TFBs) is an important step in understanding the regulation of gene expression in diverse species. ATAC-seq is a technique used for such purpose by providing high-resolution measurements of chromatin accessibility revealed through integration of Tn5 transposase. However, the existence of cell walls in filamentous fungi and associated difficulty in purifying nuclei have precluded the routine application of this technique, leading to a lack of experimentally determined and computationally inferred data on the identity of genome-wide cis-regulatory elements (CREs) and TFBs. In this study, we constructed an ATAC-seq platform suitable for filamentous fungi and generated ATAC-seq libraries of Aspergillus niger and Aspergillus oryzae grown under a variety of conditions.

Results

We applied the ATAC-seq assay for filamentous fungi to delineate the syntenic orthologue and differentially changed chromatin accessibility regions among different Aspergillus species, during different culture conditions, and among specific TF-deleted strains. The syntenic orthologues of accessible regions were responsible for the conservative functions across Aspergillus species, while regions differentially changed between culture conditions and TFs mutants drove differential gene expression programs. Importantly, we suggest criteria to determine TFBs through the analysis of unbalanced cleavage of distinct TF-bound DNA strands by Tn5 transposase. Based on this criterion, we constructed data libraries of the in vivo genomic footprint of A. niger under distinct conditions, and generated a database of novel transcription factor binding motifs through comparison of footprints in TF-deleted strains. Furthermore, we validated the novel TFBs in vivo through an artificial synthetic minimal promoter system.

Conclusions

We characterized the chromatin accessibility regions of filamentous fungi species, and identified a complete TFBs map by ATAC-seq, which provides valuable data for future analyses of transcriptional regulation in filamentous fungi.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01114-0.

Understanding and controlling filamentous growth of fungal cell factories: novel tools and opportunities for targeted morphology engineering

Filamentous fungal cell factories are efficient producers of platform chemicals, proteins, enzymes and natural products. Stirred-tank bioreactors up to a scale of several hundred m³ are commonly used for their cultivation. Fungal hyphae self-assemble into various cellular macromorphologies ranging from dispersed mycelia, loose clumps, to compact pellets. Development of these macromorphologies is so far unpredictable but strongly impacts productivities of fungal bioprocesses. Depending on the strain and the desired product, the morphological forms vary, but no strain- or product-related correlations currently exist to improve process understanding of fungal production systems. However, novel genomic, genetic, metabolic, imaging and modelling tools have recently been established that will provide fundamental new insights into filamentous fungal growth and how it is balanced with product formation. In this primer, these tools will be highlighted and their revolutionary impact on rational morphology engineering and bioprocess control will be discussed.

Something old, something new: challenges and developments in Aspergillus niger biotechnology

The filamentous ascomycete fungus Aspergillus niger is a prolific secretor of organic acids, proteins, enzymes and secondary metabolites. Throughout the last century, biotechnologists have developed A. niger into a multipurpose cell factory with a product portfolio worth billions of dollars each year. Recent technological advances, from genome editing to other molecular and omics tools, promise to revolutionize our understanding of A. niger biology, ultimately to increase efficiency of existing industrial applications or even to make entirely new products. However, various challenges to this biotechnological vision, many several decades old, still limit applications of this fungus. These include an inability to tightly control A. niger growth for optimal productivity, and a lack of high-throughput cultivation conditions for mutant screening. In this mini-review, we summarize the current state-of-the-art for A. niger biotechnology with special focus on organic acids (citric acid, malic acid, gluconic acid and itaconic acid), secreted proteins and secondary metabolites, and discuss how new technological developments can be applied to comprehensively address a variety of old and persistent challenges.

Turning Inside Out: Filamentous Fungal Secretion and Its Applications in Biotechnology, Agriculture, and the Clinic

Filamentous fungi are found in virtually every marine and terrestrial habitat. Vital to this success is their ability to secrete a diverse range of molecules, including hydrolytic enzymes, organic acids, and small molecular weight natural products. Industrial biotechnologists have successfully harnessed and re-engineered the secretory capacity of dozens of filamentous fungal species to make a diverse portfolio of useful molecules. The study of fungal secretion outside fermenters, e.g., during host infection or in mixed microbial communities, has also led to the development of novel and emerging technological breakthroughs, ranging from ultra-sensitive biosensors of fungal disease to the efficient bioremediation of polluted environments. In this review, we consider filamentous fungal secretion across multiple disciplinary boundaries (e.g., white, green, and red biotechnology) and product classes (protein, organic acid, and secondary metabolite). We summarize the mechanistic understanding for how various molecules are secreted and present numerous applications for extracellular products. Additionally, we discuss how the control of secretory pathways and the polar growth of filamentous hyphae can be utilized in diverse settings, including industrial biotechnology, agriculture, and the clinic.

Comparative Genomic and Transcriptomic Analysis Reveals Specific Features of Gene Regulation in Kluyveromyces marxianus

Kluyveromyces marxianus is a promising host for producing bioethanol and heterologous proteins. It displays many superior traits to a conventional industrial yeast species, Saccharomyces cerevisiae, including fast growth, thermotolerance and the capacity to assimilate a wider variety of sugars. However, little is known about the mechanisms underlying the fast-growing feature of K. marxianus. In this study, we performed a comparative genomic analysis between K. marxianus and other Saccharomycetaceae species. Genes involved in flocculation, iron transport, and biotin biosynthesis have particularly high copies in K. marxianus. In addition, 60 K. marxianus specific genes were identified, 45% of which were upregulated during cultivation in rich medium and these genes may participate in glucose transport and mitochondrion related functions. Furthermore, the transcriptomic analysis revealed that under aerobic condition, normalized levels of genes participating in TCA cycles, respiration chain and ATP biosynthesis in the lag phase were higher in K. marxianus than those in S. cerevisiae. Levels of highly copied genes, genes involved in the respiratory chain and mitochondrion assembly, were upregulated in K. marxianus, but not in S. cerevisiae, in later time points during cultivation compared with those in the lag phase. Notably, during the fast-growing phase, genes involved in the respiratory chain, ATP synthesis and glucose transport were co-upregulated in K. marxianus. A few shared motifs in upstream sequences of relevant genes might result in the co-upregulation. Specific features in the co-regulations of gene expressions might contribute to the fast-growing phenotype of K. marxianus. Our study underscores the importance of genome-wide rewiring of the transcriptional network during evolution.

DeORFanizing Candida albicans Genes using Coexpression

Candida albicans is a common and deadly fungal pathogen of humans, yet the genome of this organism contains many genes of unknown function. By determining gene function, we can help identify essential genes, new virulence factors, or new regulators of drug resistance, and thereby give new targets for antifungal development.

Functional characterization of open reading frames in nonmodel organisms, such as the common opportunistic fungal pathogen Candida albicans, can be labor-intensive. To meet this challenge, we built a comprehensive and unbiased coexpression network for C. albicans, which we call CalCEN, from data collected from 853 RNA sequencing runs from 18 large-scale studies deposited in the NCBI Sequence Read Archive. Retrospectively, CalCEN is highly predictive of known gene function annotations and can be synergistically combined with sequence similarity and interaction networks in Saccharomyces cerevisiae through orthology for additional accuracy in gene function prediction. To prospectively demonstrate the utility of the coexpression network in C. albicans, we predicted the function of underannotated open reading frames (ORFs) and identified CCJ1 as a novel cell cycle regulator in C. albicans. This study provides a tool for future systems biology analyses of gene function in C. albicans. We provide a computational pipeline for building and analyzing the coexpression network and CalCEN itself at http://github.com/momeara/CalCEN.

IMPORTANCECandida albicans is a common and deadly fungal pathogen of humans, yet the genome of this organism contains many genes of unknown function. By determining gene function, we can help identify essential genes, new virulence factors, or new regulators of drug resistance, and thereby give new targets for antifungal development. Here, we use information from large-scale RNA sequencing (RNAseq) studies and generate a C. albicans coexpression network (CalCEN) that is robust and able to predict gene function. We demonstrate the utility of this network in both retrospective and prospective testing and use CalCEN to predict a role for C4_06590W/CCJ1 in cell cycle. This tool will allow for a better characterization of underannotated genes in pathogenic yeasts.

Co-expression Networks in Predicting Transcriptional Gene Regulation

Recent progress in transcriptomics and co-expression networks have enabled us to predict the inference of the biological functions of genes with the associated environmental stress. Microarrays and RNA sequencing (RNA-seq) are the most commonly used high-throughput gene expression platforms for detecting differentially expressed genes between two (or more) phenotypes. Gene co-expression networks (GCNs) are a systems biology method for capturing transcriptional patterns and predicting gene interactions into functional and regulatory relationships. Here, we describe the procedures and tools used to construct and analyze GCN and investigate the integration of transcriptional data with GCN to provide reliable information about the underlying biological mechanism.

A seven-membered cell wall related transglycosylase gene family in Aspergillus niger is relevant for cell wall integrity in cell wall mutants with reduced α-glucan or galactomannan

Chitin is an important fungal cell wall component that is cross-linked to β-glucan for structural integrity. Acquisition of chitin to glucan cross-links has previously been shown to be performed by transglycosylation enzymes in Saccharomyces cerevisiae, called Congo Red hypersensitive (Crh) enzymes. Here, we characterized the impact of deleting all seven members of the crh gene family (crhA-G) in Aspergillus niger on cell wall integrity, cell wall composition and genome-wide gene expression. In this study, we show that the seven-fold crh knockout strain shows slightly compact growth on plates, but no increased sensitivity to cell wall perturbing compounds. Additionally, we found that the cell wall composition of this knockout strain was virtually identical to that of the wild type. In congruence with these data, genome-wide expression analysis revealed very limited changes in gene expression and no signs of activation of the cell wall integrity response pathway. However, deleting the entire crh gene family in cell wall mutants that are deficient in either galactofuranose or α-glucan, mainly α-1,3-glucan, resulted in a synthetic growth defect and an increased sensitivity towards Congo Red compared to the parental strains, respectively. Altogether, these results indicate that loss of the crh gene family in A. niger does not trigger the cell wall integrity response, but does play an important role in ensuring cell wall integrity in mutant strains with reduced galactofuranose or α-glucan.

Engineering cofactor metabolism for improved protein and glucoamylase production in Aspergillus niger

Background

Nicotinamide adenine dinucleotide phosphate (NADPH) is an important cofactor ensuring intracellular redox balance, anabolism and cell growth in all living systems. Our recent multi-omics analyses of glucoamylase (GlaA) biosynthesis in the filamentous fungal cell factory Aspergillus niger indicated that low availability of NADPH might be a limiting factor for GlaA overproduction.

Results

We thus employed the Design-Build-Test-Learn cycle for metabolic engineering to identify and prioritize effective cofactor engineering strategies for GlaA overproduction. Based on available metabolomics and ¹³C metabolic flux analysis data, we individually overexpressed seven predicted genes encoding NADPH generation enzymes under the control of the Tet-on gene switch in two A. niger recipient strains, one carrying a single and one carrying seven glaA gene copies, respectively, to test their individual effects on GlaA and total protein overproduction. Both strains were selected to understand if a strong pull towards glaA biosynthesis (seven gene copies) mandates a higher NADPH supply compared to the native condition (one gene copy). Detailed analysis of all 14 strains cultivated in shake flask cultures uncovered that overexpression of the gsdA gene (glucose 6-phosphate dehydrogenase), gndA gene (6-phosphogluconate dehydrogenase) and maeA gene (NADP-dependent malic enzyme) supported GlaA production on a subtle (10%) but significant level in the background strain carrying seven glaA gene copies. We thus performed maltose-limited chemostat cultures combining metabolome analysis for these three isolates to characterize metabolic-level fluctuations caused by cofactor engineering. In these cultures, overexpression of either the gndA or maeA gene increased the intracellular NADPH pool by 45% and 66%, and the yield of GlaA by 65% and 30%, respectively. In contrast, overexpression of the gsdA gene had a negative effect on both total protein and glucoamylase production.

Conclusions

This data suggests for the first time that increased NADPH availability can indeed underpin protein and especially GlaA production in strains where a strong pull towards GlaA biosynthesis exists. This data also indicates that the highest impact on GlaA production can be engineered on a genetic level by increasing the flux through the pentose phosphate pathway (gndA gene) followed by engineering the flux through the reverse TCA cycle (maeA gene). We thus propose that NADPH cofactor engineering is indeed a valid strategy for metabolic engineering of A. niger to improve GlaA production, a strategy which is certainly also applicable to the rational design of other microbial cell factories.

Comparative evaluation of Aspergillus niger strains for endogenous pectin-depolymerization capacity and suitability for D-galacturonic acid production

Pectinaceous agricultural residues rich in D-galacturonic acid (D-GalA), such as sugar beet pulp, are considered as promising feedstocks for waste-to-value conversions. Aspergillus niger is known for its strong pectinolytic activity. However, while specialized strains for production of citric acid or proteins are well characterized, this is not the case for the production of pectinases. We, therefore, systematically compared the pectinolytic capabilities of six A. niger strains (ATCC 1015, ATCC 11414, NRRL 3122, CBS 513.88, NRRL 3, and N402) using controlled batch cultivations in stirred-tank bioreactors. A. niger ATCC 11414 showed the highest polygalacturonase activity, specific protein secretion, and a suitable morphology. Furthermore, D-GalA release from sugar beet pulp was 75% higher compared to the standard lab strain A. niger N402. Our study, therefore, presents a robust initial strain selection to guide future process improvement of D-GalA production from agricultural residues and identifies a high-performance base strain for further genetic optimizations.

Growing a circular economy with fungal biotechnology: a white paper

Fungi have the ability to transform organic materials into a rich and diverse set of useful products and provide distinct opportunities for tackling the urgent challenges before all humans. Fungal biotechnology can advance the transition from our petroleum-based economy into a bio-based circular economy and has the ability to sustainably produce resilient sources of food, feed, chemicals, fuels, textiles, and materials for construction, automotive and transportation industries, for furniture and beyond. Fungal biotechnology offers solutions for securing, stabilizing and enhancing the food supply for a growing human population, while simultaneously lowering greenhouse gas emissions. Fungal biotechnology has, thus, the potential to make a significant contribution to climate change mitigation and meeting the United Nation’s sustainable development goals through the rational improvement of new and established fungal cell factories. The White Paper presented here is the result of the 2nd Think Tank meeting held by the EUROFUNG consortium in Berlin in October 2019. This paper highlights discussions on current opportunities and research challenges in fungal biotechnology and aims to inform scientists, educators, the general public, industrial stakeholders and policymakers about the current fungal biotech revolution.

Disruption or reduced expression of the orotidine-5'-decarboxylase gene pyrG increases citric acid production: a new discovery during recyclable genome editing in Aspergillus niger

Background

Aspergillus niger is a filamentous fungus used for the majority of global citric acid production. Recent developments in genome editing now enable biotechnologists to engineer and optimize A. niger. Currently, however, genetic-leads for maximizing citric acid titers in industrial A. niger isolates is limited.

Results

In this study, we try to engineer two citric acid A. niger production isolates, WT-D and D353, to serve as platform strains for future high-throughput genome engineering. Consequently, we used genome editing to simultaneously disrupt genes encoding the orotidine-5′-decarboxylase (pyrG) and non-homologous end-joining component (kusA) to enable use of the pyrG selection/counter selection system, and to elevate homologous recombination rates, respectively. During routine screening of these pyrG mutant strains, we unexpectedly observed a 2.17-fold increase in citric acid production when compared to the progenitor controls, indicating that inhibition of uridine/pyrimidine synthesis may increase citric acid titers. In order to further test this hypothesis, the pyrG gene was placed under the control of a tetracycline titratable cassette, which confirmed that reduced expression of this gene elevated citric acid titers in both shake flask and bioreactor fermentation. Subsequently, we conducted intracellular metabolomics analysis, which demonstrated that pyrG disruption enhanced the glycolysis flux and significantly improved abundance of citrate and its precursors.

Conclusions

In this study, we deliver two citric acid producing isolates which are amenable to high throughput genetic manipulation due to pyrG/kusA deletion. Strikingly, we demonstrate for the first time that A. niger pyrG is a promising genetic lead for generating citric acid hyper-producing strains. Our data support the hypothesis that uridine/pyrimidine biosynthetic pathway offer future avenues for strain engineering efforts.

The regulatory and transcriptional landscape associated with carbon utilization in a filamentous fungus

Filamentous fungi, such as Neurospora crassa, are very efficient in deconstructing plant biomass by the secretion of an arsenal of plant cell wall-degrading enzymes, by remodeling metabolism to accommodate production of secreted enzymes, and by enabling transport and intracellular utilization of plant biomass components. Although a number of enzymes and transcriptional regulators involved in plant biomass utilization have been identified, how filamentous fungi sense and integrate nutritional information encoded in the plant cell wall into a regulatory hierarchy for optimal utilization of complex carbon sources is not understood. Here, we performed transcriptional profiling of N. crassa on 40 different carbon sources, including plant biomass, to provide data on how fungi sense simple to complex carbohydrates. From these data, we identified regulatory factors in N. crassa and characterized one (PDR-2) associated with pectin utilization and one with pectin/hemicellulose utilization (ARA-1). Using in vitro DNA affinity purification sequencing (DAP-seq), we identified direct targets of transcription factors involved in regulating genes encoding plant cell wall-degrading enzymes. In particular, our data clarified the role of the transcription factor VIB-1 in the regulation of genes encoding plant cell wall-degrading enzymes and nutrient scavenging and revealed a major role of the carbon catabolite repressor CRE-1 in regulating the expression of major facilitator transporter genes. These data contribute to a more complete understanding of cross talk between transcription factors and their target genes, which are involved in regulating nutrient sensing and plant biomass utilization on a global level.

Bidirectional histone-gene promoters in Aspergillus: characterization and application for multi-gene expression

Background

Filamentous fungi are important producers of enzymes and bioactive secondary metabolites and are exploited for industrial purposes. Expression and characterization of biosynthetic pathways requires stable expression of multiple genes in the production host. Fungal promoters are indispensable for the accomplishment of this task, and libraries of promoters that show functionality across diverse fungal species facilitate synthetic biology approaches, pathway expression, and cell-factory construction.

Results

In this study, we characterized the intergenic region between the genes encoding histones H4.1 and H3, from five phylogenetically diverse species of Aspergillus, as bidirectional promoters (Ph4h3). By expression of the genes encoding fluorescent proteins mRFP1 and mCitrine, we show at the translational and transcriptional level that this region from diverse species is applicable as strong and constitutive bidirectional promoters in Aspergillus nidulans. Bioinformatic analysis showed that the divergent gene orientation of h4.1 and h3 appears maintained among fungi, and that the Ph4h3 display conserved DNA motifs among the investigated 85 Aspergilli. Two of the heterologous Ph4h3s were utilized for single-locus expression of four genes from the putative malformin producing pathway from Aspergillus brasiliensis in A. nidulans. Strikingly, heterologous expression of mlfA encoding the non-ribosomal peptide synthetase is sufficient for biosynthesis of malformins in A. nidulans, which indicates an iterative use of one adenylation domain in the enzyme. However, this resulted in highly stressed colonies, which was reverted to a healthy phenotype by co-expressing the residual four genes from the putative biosynthetic gene cluster.

Conclusions

Our study has documented that Ph4h3 is a strong constitutive bidirectional promoter and a valuable new addition to the genetic toolbox of at least the genus Aspergillus.

Functional exploration of co-expression networks identifies a nexus for modulating protein and citric acid titres in Aspergillus niger submerged culture

Background

Filamentous fungal cell factories are used to produce numerous proteins, enzymes, and organic acids. Protein secretion and filamentous growth are tightly coupled at the hyphal tip. Additionally, both these processes require ATP and amino acid precursors derived from the citric acid cycle. Despite this interconnection of organic acid production and protein secretion/filamentous growth, few studies in fungi have identified genes which may concomitantly impact all three processes.

Results

We applied a novel screen of a global co-expression network in the cell factory Aspergillus niger to identify candidate genes which may concomitantly impact macromorphology, and protein/organic acid fermentation. This identified genes predicted to encode the Golgi localized ArfA GTPase activating protein (GAP, AgeB), and ArfA guanine nucleotide exchange factors (GEFs SecG and GeaB) to be co-expressed with citric acid cycle genes. Consequently, we used CRISPR-based genome editing to place the titratable Tet-on expression system upstream of ageB, secG, and geaB in A. niger. Functional analysis revealed that ageB and geaB are essential whereas secG was dispensable for early filamentous growth. Next, gene expression was titrated during submerged cultivations under conditions for either protein or organic acid production. ArfA regulators played varied and culture-dependent roles on pellet formation. Notably, ageB or geaB expression levels had major impacts on protein secretion, whereas secG was dispensable. In contrast, reduced expression of each predicted ArfA regulator resulted in an absence of citric acid in growth media. Finally, titrated expression of either GEFs resulted in an increase in oxaloacetic acid concentrations in supernatants.

Conclusion

Our data suggest that the Golgi may play an underappreciated role in modulating organic acid titres during industrial applications, and that this is SecG, GeaB and AgeB dependent in A. niger. These data may lead to novel avenues for strain optimization in filamentous fungi for improved protein and organic acid titres.

Unearthing fungal chemodiversity and prospects for drug discovery

Natural products have drastically improved our lives by providing an excellent source of molecules to fight cancer, pathogens, and cardiovascular diseases that have revolutionized medicine. Fungi are prolific producers of diverse natural products and several recent advances in synthetic biology, genetics, bioinformatics, and natural product chemistry have greatly enhanced our ability to efficiently mine their genomes for the discovery of novel drugs. In this article, we provide an overview of improved heterologous expression platforms for targeted production of fungal secondary metabolites, of advances in chemical and bioinformatics dereplication, and of novel bioinformatic platforms to discover biosynthetic genes involved in the production of metabolites with specific bioactivities. These advances, coupled with the presence of vast numbers of biosynthetic gene clusters in fungal genomes whose natural products remain unknown, have revitalized efforts to mine the fungal treasure chest and renewed the promise of discovering new drugs.

Moulding the mould: understanding and reprogramming filamentous fungal growth and morphogenesis for next generation cell factories

Filamentous fungi are harnessed as cell factories for the production of a diverse range of organic acids, proteins, and secondary metabolites. Growth and morphology have critical implications for product titres in both submerged and solid-state fermentations. Recent advances in systems-level understanding of the filamentous lifestyle and development of sophisticated synthetic biological tools for controlled manipulation of fungal genomes now allow rational strain development programs based on data-driven decision making. In this review, we focus on Aspergillus spp. and other industrially utilised fungi to summarise recent insights into the multifaceted and dynamic relationship between filamentous growth and product titres from genetic, metabolic, modelling, subcellular, macromorphological and process engineering perspectives. Current progress and knowledge gaps with regard to mechanistic understanding of product secretion and export from the fungal cell are discussed. We highlight possible strategies for unlocking lead genes for rational strain optimizations based on omics data, and discuss how targeted genetic manipulation of these candidates can be used to optimise fungal morphology for improved performance. Additionally, fungal signalling cascades are introduced as critical processes that can be genetically targeted to control growth and morphology during biotechnological applications. Finally, we review progress in the field of synthetic biology towards chassis cells and minimal genomes, which will eventually enable highly programmable filamentous growth and diversified production capabilities. Ultimately, these advances will not only expand the fungal biotechnology portfolio but will also significantly contribute to a sustainable bio-economy.

A quantitative image analysis pipeline for the characterization of filamentous fungal morphologies as a tool to uncover targets for morphology engineering: a case study using aplD in Aspergillus niger

BACKGROUND

Fungal fermentation is used to produce a diverse repertoire of enzymes, chemicals, and drugs for various industries. During submerged cultivation, filamentous fungi form a range of macromorphologies, including dispersed mycelia, clumped aggregates, or pellets, which have critical implications for rheological aspects during fermentation, gas/nutrient transfer, and, thus, product titres. An important component of strain engineering efforts is the ability to quantitatively assess fungal growth phenotypes, which will drive novel leads for morphologically optimized production strains.

RESULTS

In this study, we developed an automated image analysis pipeline to quantify the morphology of pelleted and dispersed growth (MPD) which rapidly and reproducibly measures dispersed and pelleted macromorphologies from any submerged fungal culture. It (i) enables capture and analysis of several hundred images per user/day, (ii) is designed to quantitatively assess heterogeneous cultures consisting of dispersed and pelleted forms, (iii) gives a quantitative measurement of culture heterogeneity, (iv) automatically generates key Euclidian parameters for individual fungal structures including particle diameter, aspect ratio, area, and solidity, which are also assembled into a previously described dimensionless morphology number MN, (v) has an in-built quality control check which enables end-users to easily confirm the accuracy of the automated calls, and (vi) is easily adaptable to user-specified magnifications and macromorphological definitions. To concomitantly provide proof of principle for the utility of this image analysis pipeline, and provide new leads for morphologically optimized fungal strains, we generated a morphological mutant in the cell factory Aspergillus niger based on CRISPR-Cas technology. First, we interrogated a previously published co-expression networks for A. niger to identify a putative gamma-adaptin encoding gene (aplD) that was predicted to play a role in endosome cargo trafficking. Gene editing was used to generate a conditional aplD expression mutant under control of the titratable Tet-on system. Reduced aplD expression caused a hyperbranched growth phenotype and diverse defects in pellet formation with a putative increase in protein secretion. This possible protein hypersecretion phenotype could be correlated with increased dispersed mycelia, and both decreased pellet diameter and MN.

CONCLUSION

The MPD image analysis pipeline is a simple, rapid, and flexible approach to quantify diverse fungal morphologies. As an exemplar, we have demonstrated that the putative endosomal transport gene aplD plays a crucial role in A. niger filamentous growth and pellet formation during submerged culture. This suggests that endocytic components are underexplored targets for engineering fungal cell factories.