Quantitative modeling and analytic assessment of the transcription dynamics of the XlnR regulon in Aspergillus niger

Background: Transcription of genes coding for xylanolytic and cellulolytic enzymes in Aspergillus niger is controlled by the transactivator XlnR. In this work we analyse and model the transcription dynamics in the XlnR regulon from time-course data of the messenger RNA levels for some XlnR target genes, obtained by reverse transcription quantitative PCR (RT-qPCR). Induction of transcription was achieved using low (1 mM) and high (50 mM) concentrations of D-xylose (Xyl). We investigated the wild type strain (Wt) and a mutant strain with partial loss-of-function of the carbon catabolite repressor CreA (Mt). Results: An improved kinetic differential equation model based on two antagonistic Hill functions was proposed, and fitted to the time-course RT-qPCR data from the Wt and the Mt by numerical optimization of the parameters. We show that perturbing the XlnR regulon with Xyl in low and high concentrations results in different expression levels and transcription dynamics of the target genes. At least four distinct transcription profiles were observed, particularly for the usage of 50 mM Xyl. Higher transcript levels were observed for some genes after induction with 1 mM rather than 50 mM Xyl, especially in the Mt. Grouping the expression profiles of the investigated genes has improved our understanding of induction by Xyl and the according regulatory role of CreA. Conclusions: The model explains for the higher expression levels at 1 mM versus 50 mM in both Wt and Mt. It does not yet fully encapsulate the effect of partial loss-of-function of CreA in the Mt. The model describes the dynamics in most of the data and elucidates the time-dynamics of the two major regulatory mechanisms: i) the activation by XlnR, and ii) the carbon catabolite repression by CreA.</p

Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger

Background: In this paper the dynamics of the transcription-translation system for XlnR regulon in Aspergillus niger is modeled. The model is based on Hill regulation functions and uses ordinary differential equations. The network response to a trigger of D-xylose is considered and stability analysis is performed. The activating, repressive feedback, and the combined effect of the two feedbacks on the network behavior are analyzed. Results: Simulation and systems analysis showed significant influence of activating and repressing feedback on metabolite expression profiles. The dynamics of the D-xylose input function has an important effect on the profiles of the individual metabolite concentrations. Variation of the time delay in the feedback loop has no significant effect on the pattern of the response. The stability and existence of oscillatory behavior depends on which proteins are involved in the feedback loop. Conclusions: The dynamics in the regulation properties of the network are dictated mainly by the transcription and translation degradation rate parameters, and by the D-xylose consumption profile. This holds true with and without feedback in the network. Feedback was found to significantly influence the expression dynamics of genes and proteins. Feedback increases the metabolite abundance, changes the steady state values, alters the time trajectories and affects the response oscillatory behavior and stability conditions. The modeling approach provides insight into network behavioral dynamics particularly for small-sized networks. The analysis of the network dynamics has provided useful information for experimental design for future in vitro experimental wor

Transcriptional profiling of Aspergillus niger

The industrially important fungus Aspergillus niger feeds naturally on decomposing plant material, of which a significant proportion is lipid. Examination of the A. niger genome sequence suggested that all proteins required for metabolic conversion of lipids are present, including 63 predicted lipases. In contrast to polysaccharide-degrading enzyme networks, not much is known about the signaling and regulatory processes that control lipase expression and activity in fungi. This project was aimed to gain better understanding of lipid degradation mechanisms and how this process is regulated in A. niger, primarily via assessment of its gene transcription levels. Minimizing biological and technical variation is crucial for experiments in which transcription levels are determined, such as microarray and quantitative real-time PCR experiments. However, A. niger is difficult to cultivate in a reproducible way due to its filamentous growth. In addition, the complex processing steps of transcriptomics technologies add non-experimental variation to the biological variation. To reduce this data noise, robust protocols based on a batch-fermentation setup were developed. Variation in this setup was surveyed by examining the fungal transcriptional response towards a pulse of D-xylose. The sources of non-experimental variation were described by variance components analysis. Two-thirds of total variation stems from differences in routine handling of fermentations, but in absolute terms this variation is low. As D-xylose is an inducer of the xylanolytic system, the high reproducibility of cultures for the first time allowed a detailed description of the global fungal transcriptional response towards D-xylose using microarrays. The transcriptional response towards three plant derived oils was examined in another study. Both olive oil and a wheat-gluten extracted oil induce the transcription of genes involved in lipid metabolism and peroxisome assembly, albeit with different expression profiles. The third oil, a plant membrane lipid, did not trigger a transcriptional response. Microarray data are related to the physiology of the fungus. To better understand the general principles that underlie gene regulation and gene transcription, microarray data from cultures grown under mildly and strongly perturbed conditions were analyzed for co-expression of genes. Despite the diverse culturing conditions, co-expressed gene modules could be identified. Some of these modules can be related to biological functions. For some modules, conserved promoter elements were identified, which suggests that genes in these modules are regulated on a transcriptional level. The work described in this thesis shows that (i) high-quality -omics data for A. niger can be generated; that (ii) analysis and interpretation of these data enhances our understanding of the xylanolytic and lipid metabolic regulons; and (iii) that these data give insight into the regulatory mechanisms of this fungus. <br/

Abstracts from the 11th European Conference on Fungal Genetics

Programs and Abstracts from the 11th European Conference on Fungal Genetic

Organic acid production in Aspergillus niger and other filamentous fungi

The aim of the thesis was to increase the understanding of organic acid production in Aspergillus niger and other filamentous fungi, with the ultimate purpose to improve A. niger as biotechnological production host. In Chapter 1, the use of microbial cell-factories for the production of various compounds of interest, with a focus on organic acid production in A. niger, is introduced. To convert A. niger into a cell-factory for the production of fumarate, an organic acid that this fungus does not naturally accumulate extracellularly, we need to know the key components that lead to high extracellular fumarate accumulation. This can be achieved by studying a natural fumarate producer, in our case the filamentous fungus Rhizopus delemar. To increase both the understanding of R. delemar fumarate production, and identify a possible candidate fumarate exporter protein for heterologuous expression in A. niger, we studied differences in the transcriptional and proteomic responses of R. delemar under high and low fumarate producing conditions, described in Chapter 2. Based on our analyses, we propose that a substantial part of the fumarate accumulated in R. delemar during nitrogen starvation results from the urea cycle due to amino acid catabolism. Thus, although we failed to identify the correct fumarte exporter (discussed in Chapter 8), the results of these analyses lead to a broader understanding of the mechanism underlying fumarate accumulation in R. delemar. In order to make A. niger a suitable production host for other organic acids, we also delved deeper into the understanding of why A. niger has an innate ability to secrete various organic acids, especially citrate, described in Chapter 3. We show that an increase in citrate secretion under iron limited conditions is a physiological response consistent with a role of citrate as A. niger iron siderophore. We found that A. niger citrate secretion increases with decreasing amounts of iron added to the culture medium and, in contrast to previous findings, this response is independent of the nitrogen source. Differential transcriptomics analyses of the two A. niger mutants NW305 (gluconate non-producer) and NW186 (gluconate and oxalate non-producer) revealed up-regulation of the citrate biosynthesis gene citA under iron limited conditions compared to iron replete conditions. In addition, we show that A. niger can utilise Fe(III) citrate as iron source. Finally, we discuss our findings in the general context of the pH-dependency of A. niger organic acid production, offering an explanation, besides competition, for why A. niger organic acid production is a sequential process influenced by the external pH of the culture medium. In Chapter 4, we further unravel the various different mechanisms underlying extracellular A. niger citrate accumulation. We show that the phenotype of increased extracellular citrate accumulation can have fundamentally different underlying mechanisms, depending on how this response was triggered. We found that varying the amount and supplement of an arginine auxotrophic A. niger strain induces increased citrate productivity. Transcriptomics analysis shows down-regulation of citrate metabolising enzymes in the conditions in which more citrate is accumulated extracellularly. This contrasts with the transcriptional adaptations triggered by iron limited conditions, described in Chapter 3. By combining data obtained from both experimental setups described in Chapters 3 and 4, we compiled a list of likely citrate transporter candidates. Two promising citrate exporter candidates were tested in the yeast Saccharomyces cerevisiae, of which one was successfully identified as citrate exporter. Our findings provide the first steps in untangling the complex interplay of different mechanisms underlying A. niger citrate accumulation, and we pinpoint, for the first time, a promising A. niger citrate exporter candidate, offering a valuable tool for improvement of A. niger as biotechnological cell-factory for citrate production. For the identification of different A. niger substrate importers, we combined in silico and in vivo approaches, and established a reliable pipeline to identify and test candidate transport proteins. The in silico approach, in which likely glucose transporter candidates are inferred from good matches with a glucose transporter specific Hidden Markov model (HMMgluT), and the in vivo approach, in which a sub-cellular proteomics approach is applied to isolate plasmalemmal glucose transporters, is described in Chapter 5. In the presented research work, a hidden Markov model (HMM), that shows a good performance in the identification and segmentation of functionally validated glucose transporters, was constructed. The model (HMMgluT) was used to analyse the A. niger membrane-associated proteome response to high and low glucose concentrations at a low pH. By combining the abundance patterns of the proteins found in the A. niger plasmalemma proteome with their HMMgluT scores, two new putative high affinity glucose transporters, denoted MstG and MstH, were identified. MstG and MstH were functionally validated and biochemically characterised by heterologous expression in a S. cerevisiae glucose transport null mutant. They were shown to be a high affinity glucose transporter (Km = 0.6 ± 0.1 mM) and a very high affinity glucose transporter (Km = 0.06 ± 0.005 mM) respectively. The concepts developed in Chapter 5 were applied in Chapter 6 to identify further substrate importer proteins in both A. niger and another filamentous fungus, Trichoderma reesei. Again a hidden Markov model, this time for the identification of xylose transporters, was constructed and used to analyse the A. niger and T. reesei in silico proteomes, yielding a list of candidate xylose transporters. From this list, three A. niger (XltA, XltB and XltC) and three T. reesei (Str1, Str2 and Str3) transporters were selected, functionally validated and biochemically characterised through their expression in a S. cerevisiae hexose transport null mutant, engineered to be able to metabolise xylose, but unable to transport this sugar. All six transporters were able to support growth of the engineered yeast on xylose, but varied in affinities and efficiencies in the uptake of the pentose. Amino acid sequence analysis of the selected transporters showed the presence of specific residues and motifs associated to xylose transporters. Transcriptional analysis of A. niger and T. reesei showed that XltA and Str1 were specifically induced by xylose and dependent on the XlnR/Xyr1 regulators, implying a biological role for these transporters in xylose utilisation. Thus, our findings show that our approach using HMMs is a robust pipeline to identify different substrate importer candidates. In Chapter 7, comparative plasmalemma proteomic analysis was used to identify candidate L-rhamnose transporters in A. niger. Further analysis was focused on protein ID 1119135 (RhtA) (JGI A. niger ATCC 1015 genome database). RhtA was classified as a Family 7 Fucose:H+ Symporter (FHS) within the Major Facilitator Superfamily. Family 7 currently includes exclusively bacterial transporters able to use different sugars. Strong indications for its role in L-rhamnose transport were obtained by functional complementation of the Saccharomyces cerevisiae EBY.VW.4000 strain in growth studies with a range of potential substrates. Biochemical analysis using L-[3H(G)]-rhamnose confirmed that RhtA is a L-rhamnose transporter. The RhtA gene is located in tandem with a hypothetical alpha-L-rhamnosidase gene (rhaB). Transcriptional analysis of rhtA and rhaB confirmed that both genes have a coordinated expression, being strongly and specifically induced by L-rhamnose, and controlled by RhaR, a transcriptional regulator involved in the release and catabolism of the methyl-pentose. RhtA is the first eukaryotic L-rhamnose transporter identified and functionally validated to date. In Chapter 8, the findings presented in this thesis with regards to our attempts at improving A. niger as biotechnological production host are summarised, and further implications for metabolic engineering approaches based on the conclusions drawn are discussed.</p

XXIII Fungal Genetics Conference

Program and abstracts from the 23rd Fungal Genetics Conference and Poster Abstracts at Asilomar, March 15-20, 200

27th Fungal Genetics Conference

Program and abstracts from the 27th Fungal Genetics Conference Asilomar, March 12-17, 2013

Engineering Regulation in Anaerobic Gut Fungi during Lignocellulose Breakdown

The development of a renewable, bio-based economy requires efficient methods to extract fermentable sugars from complex plant material. Currently, bioprocessing from crude biomass requires multiple steps including pretreatment to separate lignin from sugar-rich cellulose and hemicellulose, enzymatic hydrolysis to release simple sugars, and microbial fermentation to produce value-added chemicals. Consolidated bioprocessing seeks to improve bioprocessing efficiency by reducing the number of steps required to get from plant biomass to chemical product. To address this challenge, we derived inspiration from natural microbial communities known for degrading biomass. Within the rumen microbiome of large herbivores, anaerobic gut fungi are the primary colonizers of plant material and present an untapped opportunity for consolidated bioprocessing. These unique microorganisms efficiently hydrolyze lignocellulosic biomass into simple sugars, but remain relatively uncharacterized in comparison to industrial production organisms. We implemented Next Generation Sequencing (NGS) technologies alongside biochemical studies to develop a deeper understanding of gut fungi, their metabolism, and the mechanisms by which they break down complex biomass to identify a path forward for their industrial application. We also developed simple, rapid methodologies for cryopreservation and DNA extraction that are critical for the development of industrial microbes.Sequencing and functional annotation of transcriptomes and genomes of novel isolated species of gut fungi has elucidated their large repertoire of biomass degrading enzymes including cellulases, hemicellulases, and accessory enzymes. These enzymes allow them to efficiently degrade crude biomass, yielding similar growth rates on complex plant material and simple sugars. Remarkably, in isolated batch culture, the biomass degrading power of gut fungi is sufficient to generate surplus fermentable sugars for the growth of additional microorganisms. This ability has been exploited to develop a novel two-stage consolidated bioprocessing scheme that uses anaerobic gut fungi to consolidate the pretreatment and hydrolysis steps in traditional bioprocessing to hydrolyze sugars directly from crude biomass. These sugars can then be fed to the easily metabolically engineered model yeast, Saccharomyces cerevisiae, to support growth and bioproduction in a two-stage fermentation scheme. Further, RNA sequencing studies have provided critical insight into the regulation of biomass degrading activity. Gene expression during growth on varying substrates and in response to a carbon catabolite repressor has revealed conditions required to optimize expression of biomass degrading enzymes. Unannotated sequences that co-regulate with predicted biomass degrading enzymes have also been identified as candidate genes that may host novel biomass degrading function. Together these results reveal important process considerations for the use of gut fungi in industrial bioprocessing to maximize the production of enzymes and the degradation of biomass. While challenges remain for the implementation of gut fungi in industrial bioprocessing, we have demonstrated their potential to consolidate pretreatment and hydrolysis either through engineered culturing schemes or development of improved enzyme cocktails for biomass hydrolysis

27th Fungal Genetics Conference

Program and abstracts from the 27th Fungal Genetics Conference Asilomar, March 12-17, 2013