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

Going fishing: how to get what you want from a fungal genetic screen

Five years ago, as I was starting my lab, I wrote about two functional genomic screens in fungi that had inspired me (mSphere 4:e00299-19, https://doi.org/10.1128/mSphere.00299-19). Now, I want to discuss some of the principles and questions that I ask myself and my students as we embark on our own screens. A good screen, whether it is a genetic or chemical screen, can be the starting point for new discovery and an excellent basis for the beginning of a scientific research project. However, screens are often criticized for being "fishing expeditions." To stretch this metaphor to the extreme, this is because people are worried that we do not know how to fish, that we will come home without any fish, bring home the wrong fish, or not know what to do with a fish if we caught it. How you set up the screen and analyze the results determines whether the screen will be useful. In this mini-review, and in the spirit of teaching a scientist to fish, I will discuss recent excellent fungal genetic and chemical screens that illustrate some of the key aspects of a successful screen.

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.

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.

Protocol for gene characterization in Aspergillus niger using 5S rRNA-CRISPR-Cas9-mediated Tet-on inducible promoter exchange

This protocol presents an efficient genetic strategy to investigate gene function in the fungus Aspergillus niger. We combined 5S rRNA-CRISPR-Cas9 technology with Tet-on gene switch to generate conditional-expression mutants via precisely replacing native promoter with inducible promoter. We describe the design and DNA preparation for sgRNAs and donor DNA. We then detail the steps for DNA co-transformation into A. niger protoplasts by PEG-mediated transformation, followed by homozygote isolation. Finally, we describe the genome verification and strain validation of the isolates. For complete details on the use and execution of this protocol, please refer to Zheng et al. (2019).¹.

CRISPR/Cas9-Based Genome Editing and Its Application in Aspergillus Species

Aspergillus, a genus of filamentous fungi, is extensively distributed in nature and plays crucial roles in the decomposition of organic materials as an important environmental microorganism as well as in the traditional fermentation and food processing industries. Furthermore, due to their strong potential to secrete a large variety of hydrolytic enzymes and other natural products by manipulating gene expression and/or introducing new biosynthetic pathways, several Aspergillus species have been widely exploited as microbial cell factories. In recent years, with the development of next-generation genome sequencing technology and genetic engineering methods, the production and utilization of various homo-/heterologous-proteins and natural products in Aspergillus species have been well studied. As a newly developed genome editing technology, the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) system has been used to edit and modify genes in Aspergilli. So far, the CRISPR/Cas9-based approach has been widely employed to improve the efficiency of gene modification in the strain type Aspergillus nidulans and other industrially important and pathogenic Aspergillus species, including Aspergillus oryzae, Aspergillus niger, and Aspergillus fumigatus. This review highlights the current development of CRISPR/Cas9-based genome editing technology and its application in basic research and the production of recombination proteins and natural products in the Aspergillus species.

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.

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.

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.

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.

Integration of enzyme constraints in a genome-scale metabolic model of Aspergillus niger improves phenotype predictions

Background

Genome-scale metabolic model (GSMM) is a powerful tool for the study of cellular metabolic characteristics. With the development of multi-omics measurement techniques in recent years, new methods that integrating multi-omics data into the GSMM show promising effects on the predicted results. It does not only improve the accuracy of phenotype prediction but also enhances the reliability of the model for simulating complex biochemical phenomena, which can promote theoretical breakthroughs for specific gene target identification or better understanding the cell metabolism on the system level.

Results

Based on the basic GSMM model iHL1210 of Aspergillus niger, we integrated large-scale enzyme kinetics and proteomics data to establish a GSMM based on enzyme constraints, termed a GEM with Enzymatic Constraints using Kinetic and Omics data (GECKO). The results show that enzyme constraints effectively improve the model’s phenotype prediction ability, and extended the model’s potential to guide target gene identification through predicting metabolic phenotype changes of A. niger by simulating gene knockout. In addition, enzyme constraints significantly reduced the solution space of the model, i.e., flux variability over 40.10% metabolic reactions were significantly reduced. The new model showed also versatility in other aspects, like estimating large-scale \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$k_{{cat}}$$\end{document}kcat values, predicting the differential expression of enzymes under different growth conditions.

Conclusions

This study shows that incorporating enzymes’ abundance information into GSMM is very effective for improving model performance with A. niger. Enzyme-constrained model can be used as a powerful tool for predicting the metabolic phenotype of A. niger by incorporating proteome data. In the foreseeable future, with the fast development of measurement techniques, and more precise and rich proteomics quantitative data being obtained for A. niger, the enzyme-constrained GSMM model will show greater application space on the system level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01614-2.

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.

Fungi.guru: Comparative genomic and transcriptomic resource for the fungi kingdom

The fungi kingdom is composed of eukaryotic heterotrophs, which are responsible for balancing the ecosystem and play a major role as decomposers. They also produce a vast diversity of secondary metabolites, which have antibiotic or pharmacological properties. However, our lack of knowledge of gene function in fungi precludes us from tailoring them to our needs and tapping into their metabolic diversity. To help remedy this, we gathered genomic and gene expression data of 19 most widely-researched fungi to build an online tool, fungi.guru, which contains tools for cross-species identification of conserved pathways, functional gene modules, and gene families. We exemplify how our tool can elucidate the molecular function, biological process and cellular component of genes involved in various biological processes, by identifying a secondary metabolite pathway producing gliotoxin in Aspergillus fumigatus, the catabolic pathway of cellulose in Coprinopsis cinerea and the conserved DNA replication pathway in Fusarium graminearum and Pyricularia oryzae. The tool is available at www.fungi.guru.

Aspergillus: A Powerful Protein Production Platform

Aspergilli have been widely used in the production of organic acids, enzymes, and secondary metabolites for almost a century. Today, several GRAS (generally recognized as safe) Aspergillus species hold a central role in the field of industrial biotechnology with multiple profitable applications. Since the 1990s, research has focused on the use of Aspergillus species in the development of cell factories for the production of recombinant proteins mainly due to their natively high secretion capacity. Advances in the Aspergillus-specific molecular toolkit and combination of several engineering strategies (e.g., protease-deficient strains and fusions to carrier proteins) resulted in strains able to generate high titers of recombinant fungal proteins. However, the production of non-fungal proteins appears to still be inefficient due to bottlenecks in fungal expression and secretion machinery. After a brief overview of the different heterologous expression systems currently available, this review focuses on the filamentous fungi belonging to the genus Aspergillus and their use in recombinant protein production. We describe key steps in protein synthesis and secretion that may limit production efficiency in Aspergillus systems and present genetic engineering approaches and bioprocessing strategies that have been adopted in order to improve recombinant protein titers and expand the potential of Aspergilli as competitive production platforms.

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.