Mapping the polysaccharide degradation potential of Aspergillus niger

Co-production of sugars and aroma compounds from tobacco waste using biomass-degrading enzymes produced by Aspergillus brunneoviolaceus Ab-10

Biomass-degrading enzymes produced by microorganisms have a great potential in the processing of agricultural wastes. In order to produce suitable biomass-degrading enzymes for releasing sugars and aroma compounds from tobacco scraps, the feasibility of directly using the scraps as a carbon source for enzyme production was investigated in this study. By comparative studies of ten fungal strains isolated from tobacco leaves, Aspergillus brunneoviolaceus Ab-10 was found to produce an efficient enzyme mixture for the saccharification of tobacco scraps. Proteomic analysis identified a set of plant biomass-degrading enzymes in the enzyme mixture, including amylases, hemicellulases, cellulases and pectinases. At a substrate concentration of 100 g/L and enzyme dosage of 4 mg/g, glucose of 17.6 g/L was produced from tobacco scraps using the crude enzyme produced by A. brunneoviolaceus Ab-10. In addition, the contents of 23 volatile molecules, including the aroma compounds 4-ketoisophorone and benzyl alcohol, were significantly increased after the enzymatic treatment. The results provide a strategy for valorization of tobacco waste by integrating the production of biomass-degrading enzymes into the tobacco scrap processing system.

Genome mining of Fusarium reveals structural and functional diversity of pectin lyases: a bioinformatics approach

Pectin lyase (PNL) is an important enzyme of the pectinases group which degrades pectin polymer to 4,5-unsaturated oligogalacturonides by a unique β-elimination mechanism and is used in several industries. The existence of multigene families of pectin lyases has been investigated by mining microbial genomes. In the present study, 52 pectin lyase genes were predicted from sequenced six species of Fusarium, namely F. fujikuroi, F. graminearum, F. proliferatum, F. oxysporum, F. verticillioides and F. virguliforme. These sequences were in silico characterized for several physico-chemical, structural and functional attributes. The translated PNL proteins showed variability with 344-1142 amino acid residues, 35.44-127.41 kDa molecular weight, and pI ranging from 4.63 to 9.28. The aliphatic index ranged from 75.33 to 84.75. Multiple sequence alignment analysis showed several conserved amino acid residues and five distinct groups marked as I, II, III, IV, and V were observed in the phylogenetic tree. The Three-dimensional Structure of five of these PNLs, each representing a distinct group of phylogenetic trees was predicted using I-TASSER Server and validated. The pectin lyase proteins of Fusarium species revealed close similarity with pectin lyase of Aspergillus niger PelA(1IDJ) and PelB(1QCX). Diversity in the structural motifs was observed among Fusarium species with 2 β-sheets, 1 β-hairpin, 7-12 β bulges, 18-25 strands, 6 -11 helices, 1 helix-helix interaction, 32-49 β turns, 2-6 γ turns and 2- 3 disulfide bonds. The unique Pec_lyase domain was uniformly observed among all PNL proteins confirming its identity. The genome-wide mining of Fusarium species was attempted to provide the diversity of PNL genes, which could be explored for diverse applications after performing cloning and expression studies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03333-w.

Comparative Characterization of Aspergillus Pectin Lyases by Discriminative Substrate Degradation Profiling

Fungal genomes often contain several copies of genes that encode carbohydrate active enzymes having similar activity. The copies usually have slight sequence variability, and it has been suggested that the multigenecity represents distinct reaction optima versions of the enzyme. Whether the copies represent differences in substrate attack proficiencies of the enzyme have rarely been considered. The genomes of Aspergillus species encode several pectin lyases (EC 4.2.2.10), which all belong to polysaccharide lyase subfamily PL1_4 in the CAZy database. The enzymes differ in terms of sequence identity and phylogeny, and exhibit structural differences near the active site in their homology models. These enzymes catalyze pectin degradation via eliminative cleavage of the α-(1,4) glycosidic linkages in homogalacturonan with a preference for linkages between methyl-esterified galacturonate residues. This study examines four different pectin lyases (PelB, PelC, PelD, and PelF) encoded by the same Aspergillus sp. (namely A. luchuensis), and further compares two PelA pectin lyases from two related Aspergillus spp. (A. aculeatus and A. tubingensis). We report the phylogeny, enzyme kinetics, and enzymatic degradation profiles of the enzymes' action on apple pectin, citrus pectin, and sugar beet pectin. All the pectin lyases exerted highest reaction rate on apple pectin [degree of methoxylation (DM) 69%, degree of acetylation (DAc) 2%] and lowest reaction rate on sugar beet pectin (DM 56%, DAc 19%). Activity comparison at pH 5-5.5 produced the following ranking: PelB > PelA > PelD > PelF > PelC. The evolution of homogalacturonan-oligomer product profiles during reaction was analyzed by liquid chromatography with mass spectrometry (LC-MS) detection. This analyses revealed subtle differences in the product profiles indicating distinct substrate degradation preferences amongst the enzymes, notably with regard to acetyl substitutions. The LC-MS product profiling analysis thus disclosed that the multigenecity appears to provide the fungus with additional substrate degradation versatility. This product profiling furthermore represents a novel approach to functionally compare pectin-degrading enzymes, which can help explain structure-function relations and reaction properties of disparate copies of carbohydrate active enzymes. A better understanding of the product profiles generated by pectin modifying enzymes has significant implications for targeted pectin modification in food and biorefinery processes.

Succession of physiological stages hallmarks the transcriptomic response of the fungus Aspergillus niger to lignocellulose

BACKGROUND

Understanding how fungi degrade lignocellulose is a cornerstone of improving renewables-based biotechnology, in particular for the production of hydrolytic enzymes. Considerable progress has been made in investigating fungal degradation during time-points where CAZyme expression peaks. However, a robust understanding of the fungal survival strategies over its life time on lignocellulose is thereby missed. Here we aimed to uncover the physiological responses of the biotechnological workhorse and enzyme producer Aspergillus niger over its life time to six substrates important for biofuel production.

RESULTS

We analysed the response of A. niger to the feedstock Miscanthus and compared it with our previous study on wheat straw, alone or in combination with hydrothermal or ionic liquid feedstock pretreatments. Conserved (substrate-independent) metabolic responses as well as those affected by pretreatment and feedstock were identified via multivariate analysis of genome-wide transcriptomics combined with targeted transcript and protein analyses and mapping to a metabolic model. Initial exposure to all substrates increased fatty acid beta-oxidation and lipid metabolism transcripts. In a strain carrying a deletion of the ortholog of the Aspergillus nidulans fatty acid beta-oxidation transcriptional regulator farA, there was a reduction in expression of selected lignocellulose degradative CAZyme-encoding genes suggesting that beta-oxidation contributes to adaptation to lignocellulose. Mannan degradation expression was wheat straw feedstock-dependent and pectin degradation was higher on the untreated substrates. In the later life stages, known and novel secondary metabolite gene clusters were activated, which are of high interest due to their potential to synthesize bioactive compounds.

CONCLUSION

In this study, which includes the first transcriptional response of Aspergilli to Miscanthus, we highlighted that life time as well as substrate composition and structure (via variations in pretreatment and feedstock) influence the fungal responses to lignocellulose. We also demonstrated that the fungal response contains physiological stages that are conserved across substrates and are typically found outside of the conditions with high CAZyme expression, as exemplified by the stages that are dominated by lipid and secondary metabolism.

Three glycoside hydrolase family 12 enzymes display diversity in substrate specificities and synergistic action between each other

PoCel12A, PoCel12B, and PoCel12C are genes that encode glycoside hydrolase family 12 (GH12) enzymes in Penicillium oxalicum. PoCel12A and PoCel12B are typical GH12 enzymes that belong to fungal subfamilies 12-1 and 12-2, respectively. PoCel12C contains a low-complexity region (LCR) domain, which is not found in PoCel12A or PoCel12B and independent of fungal subfamily 12-1 or 12-2. Recombinant enzymes (named rCel12A, rCel12B and rCel12C) demonstrate existing diversity in the substrate specificities. Although most members in GH family 12 are typical endoglucanases and preferentially hydrolyze β-1,4-glucan (e.g., carboxymethylcellulose), recombinant PoCel12A is a non-typical endo-(1-4)-β-glucanase; it preferentially hydrolyzes mix-linked β-glucan (barley β-glucan, β-1,3-1,4-glucan) and slightly hydrolyzes β-1,4-glucan (carboxymethylcellulose). Recombinant PoCel12B possesses a significantly high activity against xyloglucan. A specific activity of rCel12B toward xyloglucan (239 µmol/min/mg) is the second-highest value known. Recombinant PoCel12C shows low activity toward β-glucan, carboxymethylcellulose, or xyloglucan. All three enzymes can degrade phosphoric acid-swollen cellulose (PASC). However, the hydrolysis products toward PASC by enzymes are different: the main hydrolysis products are cellotriose, cellotetraose, and cellobiose for rCel12A, rCel12B, and rCel12C, correspondingly. A synergistic action toward PASC among rCel12A and rCel12B is observed, thereby suggesting a potential application for preparing enzyme cocktails used in lignocellulose hydrolysis.

Deletion of either the regulatory gene ara1 or metabolic gene xki1 in Trichoderma reesei leads to increased CAZyme gene expression on crude plant biomass

BACKGROUND

Trichoderma reesei is one of the major producers of enzymes for the conversion of plant biomass to sustainable fuels and chemicals. Crude plant biomass can induce the production of CAZymes in T. reesei, but there is limited understanding of how the transcriptional response to crude plant biomass is regulated. In addition, it is unknown whether induction on untreated recalcitrant crude plant biomass (with a large diversity of inducers) can be sustained for longer. We investigated the transcriptomic response of T. reesei to the two industrial feedstocks, corn stover (CS) and soybean hulls (SBH), over time (4 h, 24 h and 48 h), and its regulatory basis using transcription factor deletion mutants (Δxyr1 and Δara1). We also investigated whether deletion of a xylulokinase gene (Δxki1) from the pentose catabolic pathway that converts potential inducers could lead to increased CAZyme gene expression.

RESULTS

By analyzing the transcriptomic responses using clustering as well as differential and cumulative expression of plant biomass degrading CAZymes, we found that corn stover induced a broader range and higher expression of CAZymes in T. reesei, while SBH induced more pectinolytic and mannanolytic transcripts. XYR1 was the major TF regulating CS utilization, likely due to the significant amount of d-xylose in this substrate. In contrast, ARA1 had a stronger effect on SBH utilization, which correlates with a higher abundance of l-arabinose in SBH that activates ARA1. Blocking pentose catabolism by deletion of xki1 led to higher expression of CAZyme encoding genes on both substrates at later time points. Surprisingly, this was also observed for Δara1 at later time points. Many of these genes were XYR1 regulated, suggesting that inducers for this regulator accumulated over time on both substrates.

CONCLUSION

Our data demonstrates the complexity of the regulatory system related to plant biomass degradation in T. reesei and the effect the feedstock composition has on this. Furthermore, this dataset provides leads to improve the efficiency of a T. reesei enzyme cocktail, such as by the choice of substrate or by deleting xki1 to obtain higher production of plant biomass degrading CAZymes.

A community-driven reconstruction of the Aspergillus niger metabolic network

Background

Aspergillus niger is an important fungus used in industrial applications for enzyme and acid production. To enable rational metabolic engineering of the species, available information can be collected and integrated in a genome-scale model to devise strategies for improving its performance as a host organism.

Results

In this paper, we update an existing model of A. niger metabolism to include the information collected from 876 publications, thereby expanding the coverage of the model by 940 reactions, 777 metabolites and 454 genes. In the presented consensus genome-scale model of A. niger iJB1325 , we integrated experimental data from publications and patents, as well as our own experiments, into a consistent network. This information has been included in a standardized way, allowing for automated testing and continuous improvements in the future. This repository of experimental data allowed the definition of 471 individual test cases, of which the model complies with 373 of them. We further re-analyzed existing transcriptomics and quantitative physiology data to gain new insights on metabolism. Additionally, the model contains 3482 checks on the model structure, thereby representing the best validated genome-scale model on A. niger developed until now. Strain-specific model versions for strains ATCC 1015 and CBS 513.88 have been created containing all data used for model building, thereby allowing users to adopt the models and check the updated version against the experimental data. The resulting model is compliant with the SBML standard and therefore enables users to easily simulate it using their preferred software solution.

Conclusion

Experimental data on most organisms are scattered across hundreds of publications and several repositories.To allow for a systems level understanding of metabolism, the data must be integrated in a consistent knowledge network. The A. niger iJB1325 model presented here integrates the available data into a highly curated genome-scale model to facilitate the simulation of flux distributions, as well as the interpretation of other genome-scale data by providing the metabolic context.

Electronic supplementary material

The online version of this article (10.1186/s40694-018-0060-7) contains supplementary material, which is available to authorized users.

Application of carbohydrate arrays coupled with mass spectrometry to detect activity of plant-polysaccharide degradative enzymes from the fungus Aspergillus niger

Renewables-based biotechnology depends on enzymes to degrade plant lignocellulose to simple sugars that are converted to fuels or high-value products. Identification and characterization of such lignocellulose degradative enzymes could be fast-tracked by availability of an enzyme activity measurement method that is fast, label-free, uses minimal resources and allows direct identification of generated products. We developed such a method by applying carbohydrate arrays coupled with MALDI-ToF mass spectrometry to identify reaction products of carbohydrate active enzymes (CAZymes) of the filamentous fungus Aspergillus niger. We describe the production and characterization of plant polysaccharide-derived oligosaccharides and their attachment to hydrophobic self-assembling monolayers on a gold target. We verify effectiveness of this array for detecting exo- and endo-acting glycoside hydrolase activity using commercial enzymes, and demonstrate how this platform is suitable for detection of enzyme activity in relevant biological samples, the culture filtrate of A. niger grown on wheat straw. In conclusion, this versatile method is broadly applicable in screening and characterisation of activity of CAZymes, such as fungal enzymes for plant lignocellulose degradation with relevance to biotechnological applications as biofuel production, the food and animal feed industry.

Expression of Aspergillus niger CAZymes is determined by compositional changes in wheat straw generated by hydrothermal or ionic liquid pretreatments

BACKGROUND

The capacity of fungi, such as Aspergillus niger, to degrade lignocellulose is harnessed in biotechnology to generate biofuels and high-value compounds from renewable feedstocks. Most feedstocks are currently pretreated to increase enzymatic digestibility: improving our understanding of the transcriptomic responses of fungi to pretreated lignocellulosic substrates could help to improve the mix of activities and reduce the production costs of commercial lignocellulose saccharifying cocktails.

RESULTS

We investigated the responses of A. niger to untreated, ionic liquid and hydrothermally pretreated wheat straw over a 5-day time course using RNA-seq and targeted proteomics. The ionic liquid pretreatment altered the cellulose crystallinity while retaining more of the hemicellulosic sugars than the hydrothermal pretreatment. Ionic liquid pretreatment of straw led to a dynamic induction and repression of genes, which was correlated with the higher levels of pentose sugars saccharified from the ionic liquid-pretreated straw. Hydrothermal pretreatment of straw led to reduced levels of transcripts of genes encoding carbohydrate-active enzymes as well as the derived proteins and enzyme activities. Both pretreatments abolished the expression of a large set of genes encoding pectinolytic enzymes. These reduced levels could be explained by the removal of parts of the lignocellulose by the hydrothermal pretreatment. The time course also facilitated identification of temporally limited gene induction patterns.

CONCLUSIONS

The presented transcriptomic and biochemical datasets demonstrate that pretreatments caused modifications of the lignocellulose, to both specific structural features as well as the organisation of the overall lignocellulosic structure, that determined A. niger transcript levels. The experimental setup allowed reliable detection of substrate-specific gene expression patterns as well as hitherto non-expressed genes. Our data suggest beneficial effects of using untreated and IL-pretreated straw, but not HT-pretreated straw, as feedstock for CAZyme production.

FunGeneClusterS: Predicting fungal gene clusters from genome and transcriptome data

Introduction

Secondary metabolites of fungi are receiving an increasing amount of interest due to their prolific bioactivities and the fact that fungal biosynthesis of secondary metabolites often occurs from co-regulated and co-located gene clusters. This makes the gene clusters attractive for synthetic biology and industrial biotechnology applications. We have previously published a method for accurate prediction of clusters from genome and transcriptome data, which could also suggest cross-chemistry, however, this method was limited both in the number of parameters which could be adjusted as well as in user-friendliness. Furthermore, sensitivity to the transcriptome data required manual curation of the predictions. In the present work, we have aimed at improving these features.

Results

FunGeneClusterS is an improved implementation of our previous method with a graphical user interface for off- and on-line use. The new method adds options to adjust the size of the gene cluster(s) being sought as well as an option for the algorithm to be flexible with genes in the cluster which may not seem to be co-regulated with the remainder of the cluster. We have benchmarked the method using data from the well-studied Aspergillus nidulans and found that the method is an improvement over the previous one. In particular, it makes it possible to predict clusters with more than 10 genes more accurately, and allows identification of co-regulated gene clusters irrespective of the function of the genes. It also greatly reduces the need for manual curation of the prediction results. We furthermore applied the method to transcriptome data from A. niger. Using the identified best set of parameters, we were able to identify clusters for 31 out of 76 previously predicted secondary metabolite synthases/synthetases. Furthermore, we identified additional putative secondary metabolite gene clusters. In total, we predicted 432 co-transcribed gene clusters in A. niger (spanning 1.323 genes, 12% of the genome). Some of these had functions related to primary metabolism, e.g. we have identified a cluster for biosynthesis of biotin, as well as several for degradation of aromatic compounds. The data identifies that suggests that larger parts of the fungal genome than previously anticipated operates as gene clusters. This includes both primary and secondary metabolism as well as other cellular maintenance functions.

Conclusion

We have developed FunGeneClusterS in a graphical implementation and made the method capable of adjustments to different datasets and target clusters. The method is versatile in that it can predict co-regulated clusters not limited to secondary metabolism. Our analysis of data has shown not only the validity of the method, but also strongly suggests that large parts of fungal primary metabolism and cellular functions are both co-regulated and co-located.

Deciphering the signaling mechanisms of the plant cell wall degradation machinery in Aspergillus oryzae

Background

The gene expression and secretion of fungal lignocellulolytic enzymes are tightly controlled at the transcription level using independent mechanisms to respond to distinct inducers from plant biomass. An advanced systems-level understanding of transcriptional regulatory networks is required to rationally engineer filamentous fungi for more efficient bioconversion of different types of biomass.

Results

In this study we focused on ten chemically defined inducers to drive expression of cellulases, hemicellulases and accessory enzymes in the model filamentous fungus Aspergillus oryzae and shed light on the complex network of transcriptional activators required. The chemical diversity analysis of the inducers, based on 186 chemical descriptors calculated from the structure, resulted into three clusters, however, the global, metabolic and extracellular protein transcription of the A. oryzae genome were only partially explained by the chemical similarity of the enzyme inducers. Genes encoding enzymes that have attracted considerable interest such as cellobiose dehydrogenases and copper-dependent polysaccharide mono-oxygenases presented a substrate-specific induction. Several homology-model structures were derived using ab-initio multiple threading alignment in our effort to elucidate the interplay of transcription factors involved in regulating plant-deconstructing enzymes and metabolites. Systematic investigation of metabolite-protein interactions, using the 814 unique reactants involved in 2360 reactions in the genome scale metabolic network of A. oryzae, was performed through a two-step molecular docking against the binding pockets of the transcription factors AoXlnR and AoAmyR. A total of six metabolites viz., sulfite (H₂SO₃), sulfate (SLF), uroporphyrinogen III (UPGIII), ethanolamine phosphate (PETHM), D-glyceraldehyde 3-phosphate (T3P1) and taurine (TAUR) were found as strong binders, whereas the genes involved in the metabolic reactions that these metabolites appear were found to be significantly differentially expressed when comparing the inducers with glucose.

Conclusions

Based on our observations, we believe that specific binding of sulfite to the regulator of the cellulase gene expression, AoXlnR, may be the molecular basis for the connection of sulfur metabolism and cellulase gene expression in filamentous fungi. Further characterization and manipulation of the regulatory network components identified in this study, will enable rational engineering of industrial strains for improved production of the sophisticated set of enzymes necessary to break-down chemically divergent plant biomass.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0224-5) contains supplementary material, which is available to authorized users.

Genomics review of holocellulose deconstruction by aspergilli

SUMMARY

Biomass is constructed of dense recalcitrant polymeric materials: proteins, lignin, and holocellulose, a fraction constituting fibrous cellulose wrapped in hemicellulose-pectin. Bacteria and fungi are abundant in soil and forest floors, actively recycling biomass mainly by extracting sugars from holocellulose degradation. Here we review the genome-wide contents of seven Aspergillus species and unravel hundreds of gene models encoding holocellulose-degrading enzymes. Numerous apparent gene duplications followed functional evolution, grouping similar genes into smaller coherent functional families according to specialized structural features, domain organization, biochemical activity, and genus genome distribution. Aspergilli contain about 37 cellulase gene models, clustered in two mechanistic categories: 27 hydrolyze and 10 oxidize glycosidic bonds. Within the oxidative enzymes, we found two cellobiose dehydrogenases that produce oxygen radicals utilized by eight lytic polysaccharide monooxygenases that oxidize glycosidic linkages, breaking crystalline cellulose chains and making them accessible to hydrolytic enzymes. Among the hydrolases, six cellobiohydrolases with a tunnel-like structural fold embrace single crystalline cellulose chains and cooperate at nonreducing or reducing end termini, splitting off cellobiose. Five endoglucanases group into four structural families and interact randomly and internally with cellulose through an open cleft catalytic domain, and finally, seven extracellular β-glucosidases cleave cellobiose and related oligomers into glucose. Aspergilli contain, on average, 30 hemicellulase and 7 accessory gene models, distributed among 9 distinct functional categories: the backbone-attacking enzymes xylanase, mannosidase, arabinase, and xyloglucanase, the short-side-chain-removing enzymes xylan α-1,2-glucuronidase, arabinofuranosidase, and xylosidase, and the accessory enzymes acetyl xylan and feruloyl esterases.

The Cell Factory Aspergillus Enters the Big Data Era: Opportunities and Challenges for Optimising Product Formation

Living with limits. Getting more from less. Producing commodities and high-value products from renewable resources including waste. What is the driving force and quintessence of bioeconomy outlines the lifestyle and product portfolio of Aspergillus, a saprophytic genus, to which some of the top-performing microbial cell factories belong: Aspergillus niger, Aspergillus oryzae and Aspergillus terreus. What makes them so interesting for exploitation in biotechnology and how can they help us to address key challenges of the twenty-first century? How can these strains become trimmed for better growth on second-generation feedstocks and how can we enlarge their product portfolio by genetic and metabolic engineering to get more from less? On the other hand, what makes it so challenging to deduce biological meaning from the wealth of Aspergillus -omics data? And which hurdles hinder us to model and engineer industrial strains for higher productivity and better rheological performance under industrial cultivation conditions? In this review, we will address these issues by highlighting most recent findings from the Aspergillus research with a focus on fungal growth, physiology, morphology and product formation. Indeed, the last years brought us many surprising insights into model and industrial strains. They clearly told us that similar is not the same: there are different ways to make a hypha, there are more protein secretion routes than anticipated and there are different molecular and physical mechanisms which control polar growth and the development of hyphal networks. We will discuss new conceptual frameworks derived from these insights and the future scientific advances necessary to create value from Aspergillus Big Data.

RNA-sequencing reveals the complexities of the transcriptional response to lignocellulosic biofuel substrates in Aspergillus niger

BACKGROUND

Saprobic fungi are the predominant industrial sources of Carbohydrate Active enZymes (CAZymes) used for the saccharification of lignocellulose during the production of second generation biofuels. The production of more effective enzyme cocktails is a key objective for efficient biofuel production. To achieve this objective, it is crucial to understand the response of fungi to lignocellulose substrates. Our previous study used RNA-seq to identify the genes induced in Aspergillus niger in response to wheat straw, a biofuel feedstock, and showed that the range of genes induced was greater than previously seen with simple inducers.

RESULTS

In this work we used RNA-seq to identify the genes induced in A. niger in response to short rotation coppice willow and compared this with the response to wheat straw from our previous study, at the same time-point. The response to willow showed a large increase in expression of genes encoding CAZymes. Genes encoding the major activities required to saccharify lignocellulose were induced on willow such as endoglucanases, cellobiohydrolases and xylanases. The transcriptome response to willow had many similarities with the response to straw with some significant differences in the expression levels of individual genes which are discussed in relation to differences in substrate composition or other factors. Differences in transcript levels include higher levels on wheat straw from genes encoding enzymes classified as members of GH62 (an arabinofuranosidase) and CE1 (a feruloyl esterase) CAZy families whereas two genes encoding endoglucanases classified as members of the GH5 family had higher transcript levels when exposed to willow. There were changes in the cocktail of enzymes secreted by A. niger when cultured with willow or straw. Assays for particular enzymes as well as saccharification assays were used to compare the enzyme activities of the cocktails. Wheat straw induced an enzyme cocktail that saccharified wheat straw to a greater extent than willow. Genes not encoding CAZymes were also induced on willow such as hydrophobins as well as genes of unknown function. Several genes were identified as promising targets for future study.

CONCLUSIONS

By comparing this first study of the global transcriptional response of a fungus to willow with the response to straw, we have shown that the inducing lignocellulosic substrate has a marked effect upon the range of transcripts and enzymes expressed by A. niger. The use by industry of complex substrates such as wheat straw or willow could benefit efficient biofuel production.

The role of carbon starvation in the induction of enzymes that degrade plant-derived carbohydrates in Aspergillus niger

Fungi are an important source of enzymes for saccharification of plant polysaccharides and production of biofuels. Understanding of the regulation and induction of expression of genes encoding these enzymes is still incomplete. To explore the induction mechanism, we analysed the response of the industrially important fungus Aspergillus niger to wheat straw, with a focus on events occurring shortly after exposure to the substrate. RNA sequencing showed that the transcriptional response after 6h of exposure to wheat straw was very different from the response at 24h of exposure to the same substrate. For example, less than half of the genes encoding carbohydrate active enzymes that were induced after 24h of exposure to wheat straw, were also induced after 6h exposure. Importantly, over a third of the genes induced after 6h of exposure to wheat straw were also induced during 6h of carbon starvation, indicating that carbon starvation is probably an important factor in the early response to wheat straw. The up-regulation of the expression of a high number of genes encoding CAZymes that are active on plant-derived carbohydrates during early carbon starvation suggests that these enzymes could be involved in a scouting role during starvation, releasing inducing sugars from complex plant polysaccharides. We show, using proteomics, that carbon-starved cultures indeed release CAZymes with predicted activity on plant polysaccharides. Analysis of the enzymatic activity and the reaction products, indicates that these proteins are enzymes that can degrade various plant polysaccharides to generate both known, as well as potentially new, inducers of CAZymes.

Pectinase activity determination: an early deceleration in the release of reducing sugars throws a spanner in the works!

Recently, it has been suggested that pectinases could be used to hydrolyze pectin in biorefineries based on pectin-rich agro-industrial wastes. However, for this to be viable, the cost of their production would need to be lowered significantly. In fact, over the last few decades, there have been many attempts to improve pectinase production by existing strains or to screen for new strains from environmental isolates. In these studies, it is necessary to measure pectinase activities. Many researchers use single-time-point assays that involve incubation of pectinolytic extracts with pectic substrates for a fixed time, followed by determination of the liberated reducing sugars. However, different researchers use quite different conditions for this assay. Furthermore, no attention has been given to the reaction profile during the assay. In the current work, we show, for the first time, that a significant deceleration of the rate of liberation of reducing sugars occurs over the first ten minutes of the reaction. As a consequence, the incubation time used in a single-time-point assay has a large effect on the value obtained for the activity. In fact, we demonstrate that, depending on the particular combination of incubation time, pectin concentration and reaction temperature, the same extract could be reported to have activities that differ by an order of magnitude. In addition, we show that the relative activities obtained with polygalacturonic acid do not correlate with those obtained with pectin. We conclude that it is currently impossible to make meaningful comparisons between pectinase activities reported in the literature by workers who have used different assay conditions. Therefore there is an urgent need for the development of a standardized assay for evaluating the saccharification potential of pectinase complexes.

Elucidation of primary metabolic pathways in Aspergillus species: orphaned research in characterizing orphan genes

Primary metabolism affects all phenotypical traits of filamentous fungi. Particular examples include reacting to extracellular stimuli, producing precursor molecules required for cell division and morphological changes as well as providing monomer building blocks for production of secondary metabolites and extracellular enzymes. In this review, all annotated genes from four Aspergillus species have been examined. In this process, it becomes evident that 80–96% of the genes (depending on the species) are still without verified function. A significant proportion of the genes with verified metabolic functions are assigned to secondary or extracellular metabolism, leaving only 2–4% of the annotated genes within primary metabolism. It is clear that primary metabolism has not received the same attention in the post-genomic area as many other research areas—despite its role at the very centre of cellular function. However, several methods can be employed to use the metabolic networks in tandem with comparative genomics to accelerate functional assignment of genes in primary metabolism. In particular, gaps in metabolic pathways can be used to assign functions to orphan genes. In this review, applications of this from the Aspergillus genes will be examined, and it is proposed that, where feasible, this should be a standard part of functional annotation of fungal genomes.

(Post-)genomics approaches in fungal research

To date, hundreds of fungal genomes have been sequenced and many more are in progress. This wealth of genomic information has provided new directions to study fungal biodiversity. However, to further dissect and understand the complicated biological mechanisms involved in fungal life styles, functional studies beyond genomes are required. Thanks to the developments of current -omics techniques, it is possible to produce large amounts of fungal functional data in a high-throughput fashion (e.g. transcriptome, proteome, etc.). The increasing ease of creating -omics data has also created a major challenge for downstream data handling and analysis. Numerous databases, tools and software have been created to meet this challenge. Facing such a richness of techniques and information, hereby we provide a brief roadmap on current wet-lab and bioinformatics approaches to study functional genomics in fungi.

Promise and reality in the expanding field of network interaction analysis: metabolic networks

In the last few decades, metabolic networks revealed their capabilities as powerful tools to analyze the cellular metabolism. Many research fields (eg, metabolic engineering, diagnostic medicine, pharmacology, biochemistry, biology and physiology) improved the understanding of the cell combining experimental assays and metabolic network-based computations. This process led to the rise of the “systems biology” approach, where the theory meets experiments and where two complementary perspectives cooperate in the study of biological phenomena. Here, the reconstruction of metabolic networks is presented, along with established and new algorithms to improve the description of cellular metabolism. Then, advantages and limitations of modeling algorithms and network reconstruction are discussed.

Development of highly efficient, low-cost lignocellulolytic enzyme systems in the post-genomic era

The current high cost of lignocellulolytic enzymes is a major bottleneck in the economic bioconversion of lignocellulosic biomass to fuels and chemicals. Fungal lignocellulolytic enzyme systems are secreted at high levels, making them the most promising starting points for further development of highly efficient lignocellulolytic enzyme systems. In this paper, recent advances in improvement of fungal lignocellulolytic enzyme systems are reviewed, with an emphasis on the achievements made using genomic approaches. A general strategy for lignocellulolytic enzyme system development is proposed, including the improvement of the hydrolysis efficiencies and productivities of current enzyme systems. The applications of genomic, transcriptomic and proteomic analysis methods in examining the composition of native enzyme systems, discovery of novel enzymes and synergistic proteins from natural sources, and understanding of regulatory mechanisms for lignocellulolytic enzyme biosynthesis are summarized. By combining systems biology and synthetic biology tools, engineered fungal strains are expected to produce high levels of optimized lignocellulolytic enzyme systems.