Lipid production by robust Aspergillus oryzae BCC7051 and a mathematical model describing its growth and lipid phenotypic traits

AIMS

To identify the promising oleaginous Aspergillus oryzae strain and leverage its lipid and biomass production through a mathematical model.

METHODS AND RESULTS

Comparative profiling of the cell growth and total fatty acid (TFA) content among 13 strains of A. oryzae was performed to explore the discrimination in their lipid productions. The oleaginicity of A. oryzae was found to be strain dependent, where the fungal strain BCC7051 exhibited superior performance in producing lipid-rich biomass by submerged fermentation. The TFA contents of the strain BCC7051 were comparable when cultivated at a range of pH values (pH 3.5-6.5) and temperatures (24-42°C). The mathematical model was generated, well describing and predicting the fungal growth and lipid phenotypic traits at various temperatures and carbon substrates.

CONCLUSION

The A. oryzae strain BCC7051 was a robust cell factory, acquiring economically feasible options for producing valuable lipid-based products.

Bringing a scalable adaptive hybrid modeling framework closer to industrial use: Application on a multiscale fungal fermentation

Digitalization has paved the way for new paradigms such as digital shadows and digital twins for fermentation processes, opening the door for real-time process monitoring, control, and optimization. With a digital shadow, real-time model adaptation to accommodate complex metabolic phenomena such as metabolic shifts of a process can be monitored. Despite the many benefits of digitalization, the potential has not been fully reached in the industry. This study investigates the development of a digital shadow for a very complex fungal fermentation process in terms of microbial physiology and fermentation operation on pilot-scale at Novonesis and the challenges thereof. The process has historically been difficult to optimize and control due to a lack of offline measurements and an absence of biomass measurements. Pilot-scale and lab-scale fermentations were conducted for model development and validation. With all available pilot-scale data, a data-driven soft sensor was developed to estimate the main substrate concentration (glucose) with a normalized root mean squared error (N-RMSE) of 2%. This robust data-driven soft sensor was able to estimate accurately in lab-scale (volume < 20× pilot) with a N-RMSE of 7.8%. A hybrid soft sensor was developed by combining the data-driven soft sensor with a mass balance to estimate the glycerol and biomass concentrations on pilot-scale data with N-RMSEs of 11% and 21%, respectively. A digital shadow modeling framework was developed by coupling a mechanistic model (MM) with the hybrid soft sensor. The digital shadow modeling framework significantly improved the predictability compared with the MM. The contribution of this study brings the application of digital shadows closer to industrial implementation. It demonstrates the high potential of using this type of modeling framework for scale-up and leads the way to a new generation of in silico-based process development.

Dynamic modeling of the activated sludge microbial growth and activity under exposure to heavy metals

The presence of heavy metals in the environment can lead to ecological and health problems. The evolution of biological systems, such as activated sludge, exposed to heavy metals is still underexplored. Therefore, this study sought to develop a model of microorganism activity and growth in activated sludge and used it to investigate the toxicity of five metals: Cu, Cd, Ni, Zn, and Ag. Patterns in the evolution of the toxic effects caused by these metals were similar at the beginning of exposure. Differences in toxicity between metal ions were noted for longer exposure times. Changes in model parameters indicate the influence of metal ions on the mass and energy balance of living cells. Decreases in new enzyme units and biomass production yields in contaminated activated sludge indicate a shift from anabolic reactions to metal homeostasis and resistance.

Effects of Impeller Geometry on the 11α-Hydroxylation of Canrenone in Rushton Turbine-Stirred Tanks

The 11α-hydroxylation of canrenone can be catalyzed by Aspergillus ochraceus in bioreactors, where the geometry of the impeller greatly influences the biotransformation. In this study, the effects of the blade number and impeller diameter of a Rushton turbine on the 11α-hydroxylation of canrenone were considered. The results of fermentation experiments using a 50 mm four-blade impeller showed that 3.40% and 11.43% increases in the conversion ratio were achieved by increasing the blade number and impeller diameter, respectively. However, with an impeller diameter of 60 mm, the conversion ratio with a six-blade impeller was 14.42% lower than that with a four-blade impeller. Data from cold model experiments with a large-diameter six-blade impeller indicated that the serious leakage of inclusions and a 22.08% enzyme activity retention led to a low conversion ratio. Numerical simulations suggested that there was good gas distribution and high fluid flow velocity when the fluid was stirred by large-diameter impellers, resulting in a high dissolved oxygen content and good bulk circulation, which positively affected hyphal growth and metabolism. However, a large-diameter six-blade impeller created overly high shear compared to a large-diameter four-blade impeller, thereby decreasing the conversion ratio. The average shear rates of the former and latter cases were 43.25 s^-1 and 35.31 s^-1, respectively. We therefore concluded that appropriate shear should be applied in the 11α-hydroxylation of canrenone. Overall, this study provides basic data for the scaled-up production of 11α-hydroxycanrenone.

Engineering interventions in enzyme production: Lab to industrial scale

Commercial enzyme production has gained popularity due to its extensive applications in traditional and modern industrial sectors. Rigorous research activities are being conducted worldwide to make the enzyme production system more efficient, cost-effective and hence, sustainable. To overcome the lacunae in earlier enzyme production methods, new engineering interventions are being introduced to meet the growing demand for industrial enzymes. This review focuses initially on the current global scenario of the enzyme market followed by a discussion on different bioreactor design approaches. The use of novel membrane based, airlift and reciprocating plate bioreactors along with the emergence of micro-reactors have also been discussed. Further, the review covers different modelling and optimization strategies for the enzyme production process including advanced techniques like neural networks, adaptive neuro-fuzzy inference systems and genetic algorithms. Finally, the required thrust areas in the enzyme production sector have been highlighted with directions for future research.

Understanding gradients in industrial bioreactors

Gradients in industrial bioreactors have attracted substantial research attention since exposure to fluctuating environmental conditions has been shown to lead to changes in the metabolome, transcriptome as well as population heterogeneity in industrially relevant microorganisms. Such changes have also been found to impact key process parameters like the yield on substrate and the productivity. Hence, understanding gradients is important from both the academic and industrial perspectives. In this review the causes of gradients are outlined, along with their impact on microbial physiology. Quantifying the impact of gradients requires a detailed understanding of both fluid flow inside industrial equipment and microbial physiology. This review critically examines approaches used to investigate gradients including large-scale experimental work, computational methods and scale-down approaches. Avenues for future work have been highlighted, particularly the need for further coordinated development of both in silico and experimental tools which can be used to further the current understanding of gradients in industrial equipment.

Effects of Agitation, Aeration and Temperature on Production of a Novel Glycoprotein GP-1 by Streptomyces kanasenisi ZX01 and Scale-Up Based on Volumetric Oxygen Transfer Coefficient

The effects of temperature, agitation and aeration on glycoprotein GP-1 production by Streptomyces kanasenisi ZX01 in bench-scale fermentors were systematically investigated. The maximum final GP-1 production was achieved at an agitation speed of 200 rpm, aeration rate of 2.0 vvm and temperature of 30 °C. By using a dynamic gassing out method, the effects of agitation and aeration on volumetric oxygen transfer coefficient (k_La) were also studied. The values of volumetric oxygen transfer coefficient in the logarithmic phase increased with increase of agitation speed (from 14.53 to 32.82 h⁻¹) and aeration rate (from 13.21 to 22.43 h⁻¹). In addition, a successful scale-up from bench-scale to pilot-scale was performed based on volumetric oxygen transfer coefficient, resulting in final GP-1 production of 3.92, 4.03, 3.82 and 4.20 mg/L in 5 L, 15 L, 70 L and 500 L fermentors, respectively. These results indicated that constant volumetric oxygen transfer coefficient was appropriate for the scale-up of batch fermentation of glycoprotein GP-1 by Streptomyces kanasenisi ZX01, and this scale-up strategy successfully achieved 100-fold scale-up from bench-scale to pilot-scale fermentor.

A novel model-based control strategy for aerobic filamentous fungal fed-batch fermentation processes

A novel model-based control strategy has been developed for filamentous fungal fed-batch fermentation processes. The system of interest is a pilot scale (550 L) filamentous fungus process operating at Novozymes A/S. In such processes, it is desirable to maximize the total product achieved in a batch in a defined process time. In order to achieve this goal, it is important to maximize both the product concentration, and also the total final mass in the fed-batch system. To this end, we describe the development of a control strategy which aims to achieve maximum tank fill, while avoiding oxygen limited conditions. This requires a two stage approach: (i) calculation of the tank start fill; and (ii) on-line control in order to maximize fill subject to oxygen transfer limitations. First, a mechanistic model was applied off-line in order to determine the appropriate start fill for processes with four different sets of process operating conditions for the stirrer speed, headspace pressure, and aeration rate. The start fills were tested with eight pilot scale experiments using a reference process operation. An on-line control strategy was then developed, utilizing the mechanistic model which is recursively updated using on-line measurements. The model was applied in order to predict the current system states, including the biomass concentration, and to simulate the expected future trajectory of the system until a specified end time. In this way, the desired feed rate is updated along the progress of the batch taking into account the oxygen mass transfer conditions and the expected future trajectory of the mass. The final results show that the target fill was achieved to within 5% under the maximum fill when tested using eight pilot scale batches, and over filling was avoided. The results were reproducible, unlike the reference experiments which show over 10% variation in the final tank fill, and this also includes over filling. The variance of the final tank fill is reduced by over 74%, meaning that it is possible to target the final maximum fill reproducibly. The product concentration achieved at a given set of process conditions was unaffected by the control strategy. Biotechnol. Bioeng. 2017;114: 1459-1468. © 2017 Wiley Periodicals, Inc.

Using a flexible shaft agitator to enhance the rheology of a complex fungal fermentation culture

The rheology behavior of biological fluids particularly when the viscosity is high and rheology is complex, is an important issue to understand, particularly for studies in mass-transfer and for solving technical problems with mixing in stirred bioreactors. In this paper, the use of a Swingstir(®) impeller during the fermentation of Aspergillus oryzae resulted in decreases from the parameters of a power-law model, in viscosity and in the thixotropic behavior of a cultivation broth. The results showed that both the K L a and the alpha amylase activity were improved when using the Swingstir(®) in comparison with Fullzone(®) impeller (FZ) at the same level of energy consumption. Increasing the pellet porosity during mixing via the Swingstir(®) resulted in increases in oxygen mass transfer and the average shear stress.

Fungal Morphology in Industrial Enzyme Production--Modelling and Monitoring

Filamentous fungi are widely used in the biotechnology industry for the production of industrial enzymes. Thus, considerable work has been done with the purpose of characterizing these processes. The ultimate goal of these efforts is to be able to control and predict fermentation performance on the basis of "standardized" measurements in terms of morphology, rheology, viscosity, mass transfer and productivity. However, because the variables are connected or dependent on each other, this task is not trivial. The aim of this review article is to gather available information in order to explain the interconnectivity between the different variables in submerged fermentations. An additional factor which makes the characterization of a fermentation broth even more challenging is that the data obtained are also dependent on the way they have been collected-meaning which technologies or probes have been used, and on the way the data is interpreted-i.e. which models were applied. The main filamentous fungi used in industrial fermentation are introduced, ranging from Trichoderma reesei to Aspergillus species. Due to the fact that secondary metabolites, like antibiotics, are not to be considered bulk products, organisms like e.g. Penicillium chrysogenum are just briefly touched upon for the description of some characterization techniques. The potential for development of different morphological phenotypes is discussed as well, also in view of what this could mean to productivity and-equally important-the collection of the data. An overview of the state of the art techniques for morphology characterization is provided, discussing methods that finally can be employed as the computational power has grown sufficiently in the recent years. Image analysis (IA) clearly benefits most but it also means that methods like near infrared measurement (NIR), capacitance and on-line viscosity now provide potential alternatives as powerful tools for characterizing morphology. These measuring techniques, and to some extent their combination, allow obtaining the data necessary for supporting the creation of mathematical models describing the fermentation process. An important part of this article will indeed focus on describing the different models, and on discussing their importance to fermentations of filamentous fungi in general. The main conclusion is that it has not yet been attempted to develop an overarching model that spans across strains and scales, as most studies indeed conclude that their respective results might be strain specific and not necessarily valid across scales.

Hydrodynamics, Fungal Physiology, and Morphology

Filamentous cultures, such as fungi and actinomycetes, contribute substantially to the pharmaceutical industry and to enzyme production, with an annual market of about 6 billion dollars. In mechanically stirred reactors, most frequently used in fermentation industry, microbial growth and metabolite productivity depend on complex interactions between hydrodynamics, oxygen transfer, and mycelial morphology. The dissipation of energy through mechanically stirring devices, either flasks or tanks, impacts both microbial growth through shearing forces on the cells and the transfer of mass and energy, improving the contact between phases (i.e., air bubbles and microorganisms) but also causing damage to the cells at high energy dissipation rates. Mechanical-induced signaling in the cells triggers the molecular responses to shear stress; however, the complete mechanism is not known. Volumetric power input and, more importantly, the energy dissipation/circulation function are the main parameters determining mycelial size, a phenomenon that can be explained by the interaction of mycelial aggregates and Kolmogorov eddies. The use of microparticles in fungal cultures is also a strategy to increase process productivity and reproducibility by controlling fungal morphology. In order to rigorously study the effects of hydrodynamics on the physiology of fungal microorganisms, it is necessary to rule out the possible associated effects of dissolved oxygen, something which has been reported scarcely. At the other hand, the processes of phase dispersion (including the suspended solid that is the filamentous biomass) are crucial in order to get an integral knowledge about biological and physicochemical interactions within the bioreactor. Digital image analysis is a powerful tool for getting relevant information in order to establish the mechanisms of mass transfer as well as to evaluate the viability of the mycelia. This review focuses on (a) the main characteristics of the two most common morphologies exhibited by filamentous microorganisms; (b) how hydrodynamic conditions affect morphology and physiology in filamentous cultures; and (c) techniques using digital image analysis to characterize the viability of filamentous microorganisms and mass transfer in multiphase dispersions. Representative case studies of fungi (Trichoderma harzianum and Pleurotus ostreatus) exhibiting different typical morphologies (disperse mycelia and pellets) are discussed.

Challenges in industrial fermentation technology research

Industrial fermentation processes are increasingly popular, and are considered an important technological asset for reducing our dependence on chemicals and products produced from fossil fuels. However, despite their increasing popularity, fermentation processes have not yet reached the same maturity as traditional chemical processes, particularly when it comes to using engineering tools such as mathematical models and optimization techniques. This perspective starts with a brief overview of these engineering tools. However, the main focus is on a description of some of the most important engineering challenges: scaling up and scaling down fermentation processes, the influence of morphology on broth rheology and mass transfer, and establishing novel sensors to measure and control insightful process parameters. The greatest emphasis is on the challenges posed by filamentous fungi, because of their wide applications as cell factories and therefore their relevance in a White Biotechnology context. Computational fluid dynamics (CFD) is introduced as a promising tool that can be used to support the scaling up and scaling down of bioreactors, and for studying mixing and the potential occurrence of gradients in a tank.

Nutrition and bioprocess development for efficient biosynthesis of an antitumor compound from marine-derived fungus

An integrated nutrition and bioprocess strategy was developed for improving the biosynthesis of an antitumor compound, 1403C, by a marine-derived fungus, Halorosellinia sp. (no. 1403). First, statistical design strategies were synthetically applied to optimize the nutritional composition. The resulting 1403C production reached 2.07 g/l, which was 143.5 % higher than the original production. However, it only produced 0.44 g/l of 1403C in 5-l bioreactor fermentation. Thus, the operating parameters including culture pH, dissolved oxygen, agitation speed, impeller type and inoculum level were considered to improve the fermentation process, and an effective control strategy for 1403C production by Halorosellinia sp. submerged in a 5-l bioreactor was established. When inoculating 0.22 g/l dry biomass, controlling dissolved oxygen not lower than 30 % during the growth phase but ranging between 30 and 40 % during the stationary phase, using a double-layer six-flat-blade Rushton disc turbine agitated at 400 rpm, keeping short-term low pH and rapid-rising pH with glucose starvation, the highest 1403C production was finally obtained at 1.32 g/l, which was promoted by 200 % compared to before optimization. Fermentation scale-up was finally performed in a 500-l bioreactor, and 1403C production of 1.09 g/l was obtained.