Guido Melzer

Characterization and control of fungal morphology for improved production performance in biotechnology.

Filamentous fungi have been widely applied in industrial biotechnology for many decades. In submerged culture processes, they typically exhibit a complex morphological life cycle that is related to production performance--a link that is of high interest for process optimization. The fungal forms can vary from dense spherical pellets to viscous mycelia. The resulting morphology has been shown to be influenced strongly by process parameters, including power input through stirring and aeration, mass transfer characteristics, pH value, osmolality and the presence of solid micro-particles. The surface properties of fungal spores and hyphae also play a role. Due to their high industrial relevance, the past years have seen a substantial development of tools and techniques to characterize the growth of fungi and obtain quantitative estimates on their morphological properties. Based on the novel insights available from such studies, more recent studies have been aimed at the precise control of morphology, i.e., morphology engineering, to produce superior bio-processes with filamentous fungi.

Flux Design: In silico design of cell factories based on correlation of pathway fluxes to desired properties

BackgroundThe identification of genetic target genes is a key step for rational engineering of production strains towards bio-based chemicals, fuels or therapeutics. This is often a difficult task, because superior production performance typically requires a combination of multiple targets, whereby the complex metabolic networks complicate straightforward identification. Recent attempts towards target prediction mainly focus on the prediction of gene deletion targets and therefore can cover only a part of genetic modifications proven valuable in metabolic engineering. Efficient in silico methods for simultaneous genome-scale identification of targets to be amplified or deleted are still lacking.ResultsHere we propose the identification of targets via flux correlation to a chosen objective flux as approach towards improved biotechnological production strains with optimally designed fluxes. The approach, we name Flux Design, computes elementary modes and, by search through the modes, identifies targets to be amplified (positive correlation) or down-regulated (negative correlation). Supported by statistical evaluation, a target potential is attributed to the identified reactions in a quantitative manner. Based on systems-wide models of the industrial microorganisms Corynebacterium glutamicum and Aspergillus niger, up to more than 20,000 modes were obtained for each case, differing strongly in production performance and intracellular fluxes. For lysine production in C. glutamicum the identified targets nicely matched with reported successful metabolic engineering strategies. In addition, simulations revealed insights, e.g. into the flexibility of energy metabolism. For enzyme production in A.niger flux correlation analysis suggested a number of targets, including non-obvious ones. Hereby, the relevance of most targets depended on the metabolic state of the cell and also on the carbon source.ConclusionsObjective flux correlation analysis provided a detailed insight into the metabolic networks of industrially relevant prokaryotic and eukaryotic microorganisms. It was shown that capacity, pathway usage, and relevant genetic targets for optimal production partly depend on the network structure and the metabolic state of the cell which should be considered in future metabolic engineering strategies. The presented strategy can be generally used to identify priority sorted amplification and deletion targets for metabolic engineering purposes under various conditions and thus displays a useful strategy to be incorporated into efficient strain and bioprocess optimization.

Integration of in vivo and in silico metabolic fluxes for improvement of recombinant protein production.

The filamentous fungus Aspergillus niger is an efficient host for the recombinant production of the glycosylated enzyme fructofuranosidase, a biocatalyst of commercial interest for the synthesis of pre-biotic sugars. In batch culture on a minimal glucose medium, the recombinant strain A. niger SKAn1015, expressing the fructofuranosidase encoding suc1 gene secreted 45U/mL of the target enzyme, whereas the parent wild type SKANip8 did not exhibit production. The production of the recombinant enzyme induced a significant change of in vivo fluxes in central carbon metabolism, as assessed by (13)C metabolic flux ratio analysis. Most notably, the flux redistribution enabled an elevated supply of NADPH via activation of the cytosolic pentose phosphate pathway (PPP) and mitochondrial malic enzyme, whereas the flux through energy generating TCA cycle was reduced. In addition, the overall possible flux space of fructofuranosidase producing A. niger was investigated in silico by elementary flux mode analysis. This provided theoretical flux distributions for multiple scenarios with differing production capacities. Subsequently, the measured flux changes linked to improved production performance were projected into the in silico flux space. This provided a quantitative evaluation of the achieved optimization and a priority ranked target list for further strain engineering. Interestingly, the metabolism was shifted largely towards the optimum flux pattern by sole expression of the recombinant enzyme, which seems an inherent attractive property of A. niger. Selected fluxes, however, changed contrary to the predicted optimum and thus revealed novel targets-including reactions linked to NADPH metabolism and gluconate formation.

Influence of pH on the expression of a recombinant epoxide hydrolase in Aspergillus niger

The filamentous fungus Aspergillus niger was investigated in relation to its ability to produce a soluble epoxide hydrolase (EH) (E.C. 3.3.2.3) belonging to the microsomal EH family. This EH is a highly useful biocatalyst for kinetic resolution of racemic epoxides to give enantiopure building blocks. The production of EH on an industrial scale is still a major challenge and is linked to various optimization processes. In this work, production of protein and organic acids as a function of pH and cultivation time was investigated. The production of EH was highest (1000 U/L for p-nitrostyrene oxide) under acidic fermentation conditions (pH value of about 3). The metabolic flux toward production of organic acids and thereby acidification of the environment increased with an increasing pH value. At pH 7, nearly 50% of total carbon of the substrate was incorporated into organic acids, mainly gluconic and oxalic acid. Finally, the addition of protease inhibitors, antioxidants and cryoprotectants was investigated in relation to the stability of the EH during the downstream process. The determination of the pH dependence during fermentation and understanding of the parameters influencing the stability of the enzyme has allowed us to optimize intracellular expression. The EH has been easily isolated from the biomass with high activity (1.67 U/mg lyophilisate) in a robust process.

Novel Approach for High-Throughput Metabolic Screening of Whole Plants by Stable Isotopes

Stable isotopic labeling combined with combustion isotope ratio mass spectrometry elucidates metabolic properties of whole plants under strictly controlled physiological conditions. Here, we demonstrate whole-plant metabolic profiling by stable isotope labeling and combustion isotope-ratio mass spectrometry for precise quantification of assimilation, translocation, and molecular reallocation of 13CO2 and 15NH4NO3. The technology was applied to rice (Oryza sativa) plants at different growth stages. For adult plants, 13CO2 labeling revealed enhanced carbon assimilation of the flag leaf from flowering to late grain-filling stage, linked to efficient translocation into the panicle. Simultaneous 13CO2 and 15NH4NO3 labeling with hydroponically grown seedlings was used to quantify the relative distribution of carbon and nitrogen. Two hours after labeling, assimilated carbon was mainly retained in the shoot (69%), whereas 7% entered the root and 24% was respired. Nitrogen, taken up via the root, was largely translocated into the shoot (85%). Salt-stressed seedlings showed decreased uptake and translocation of nitrogen (69%), whereas carbon metabolism was unaffected. Coupled to a gas chromatograph, labeling analysis provided enrichment of proteinogenic amino acids. This revealed significant protein synthesis in the panicle of adult plants, whereas protein biosynthesis in adult leaves was 8-fold lower than that in seedling shoots. Generally, amino acid enrichment was similar among biosynthetic families and allowed us to infer labeling dynamics of their precursors. On this basis, early and strong 13C enrichment of Embden-Meyerhof-Parnas pathway and pentose phosphate pathway intermediates indicated high activity of these routes. Applied to mode-of-action analysis of herbicides, the approach showed severe disturbance in the synthesis of branched-chain amino acids upon treatment with imazapyr. The established technology displays a breakthrough for quantitative high-throughput plant metabolic phenotyping.

In silico metabolic network analysis of Arabidopsis leaves

BackgroundDuring the last decades, we face an increasing interest in superior plants to supply growing demands for human and animal nutrition and for the developing bio-based economy. Presently, our limited understanding of their metabolism and its regulation hampers the targeted development of desired plant phenotypes. In this regard, systems biology, in particular the integration of metabolic and regulatory networks, is promising to broaden our knowledge and to further explore the biotechnological potential of plants.ResultsThe thale cress Arabidopsis thaliana provides an ideal model to understand plant primary metabolism. To obtain insight into its functional properties, we constructed a large-scale metabolic network of the leaf of A. thaliana. It represented 511 reactions with spatial separation into compartments. Systematic analysis of this network, utilizing elementary flux modes, investigates metabolic capabilities of the plant and predicts relevant properties on the systems level: optimum pathway use for maximum growth and flux re-arrangement in response to environmental perturbation. Our computational model indicates that the A. thaliana leaf operates near its theoretical optimum flux state in the light, however, only in a narrow range of photon usage. The simulations further demonstrate that the natural day-night shift requires substantial re-arrangement of pathway flux between compartments: 89 reactions, involving redox and energy metabolism, substantially change the extent of flux, whereas 19 reactions even invert flux direction. The optimum set of anabolic pathways differs between day and night and is partly shifted between compartments. The integration with experimental transcriptome data pinpoints selected transcriptional changes that mediate the diurnal adaptation of the plant and superimpose the flux response.ConclusionsThe successful application of predictive modelling in Arabidopsis thaliana can bring systems-biological interpretation of plant systems forward. Using the gained knowledge, metabolic engineering strategies to engage plants as biotechnological factories can be developed.

METABOLIC FLUX ANALYSIS APPLICATIONS TO ASPERGILLUS NIGER AB1.13 CULTIVATIONS

Abstract A stoichiometric model was developed for Aspergillus niger AB1.13. Metabolic flux analysis (MFA) revealed that the pH of the medium does not affect the flux distribution of the central carbon metabolism. However, one exception could be observed regarding the oxaloacetate hydrolase ( OAAH ) reaction. During D-glucose and D-xylose feeding, a 6-fold and 2-fold increase in flux distribution was observed with increasing pH (ΔpH 2.5), respectively. Differences in flux with D-glucose and D-xylose as substrate were reflected in a higher demand of NADPH during D-xylose consumption. Additionally, a comparison between metabolic models revealed that the ribulose-5-phosphate epimerase ( RPE ) might not be expressed during D-xylose consumption.