Biochemical engineering’s grand adventure

Integration Approaches to Model Bioreactor Hydrodynamics and Cellular Kinetics for Advancing Bioprocess Optimisation

Large-scale bioprocesses are increasing globally to cater to the larger market demands for biological products. As fermenter volumes increase, the efficiency of mixing decreases, and environmental gradients become more pronounced compared to smaller scales. Consequently, the cells experience gradients in process parameters, which in turn affects the efficiency and profitability of the process. Computational fluid dynamics (CFD) simulations are being widely embraced for their ability to simulate bioprocess performance, facilitate bioprocess upscaling, downsizing, and process optimisation. Recently, CFD approaches have been integrated with dynamic Cell reaction kinetic (CRK) modelling to generate valuable information about the cellular response to fluctuating hydrodynamic parameters inside large production processes. Such coupled approaches have the potential to facilitate informed decision-making in intelligent biomanufacturing, aligning with the principles of "Industry 4.0" concerning digitalisation and automation. In this review, we discuss the benefits of utilising integrated CFD-CRK models and the different approaches to integrating CFD-based bioreactor hydrodynamic models with cellular kinetic models. We also highlight the suitability of different coupling approaches for bioprocess modelling in the purview of associated computational loads.

Probing efficient microbial CO2 utilisation through metabolic and process modelling

Acetogenic gas fermentation is increasingly studied as a promising technology to upcycle carbon-rich waste gasses. Currently the product range is limited, and production yields, rates and titres for a number of interesting products do not allow for economically viable processes. By pairing process modelling and host-agnostic metabolic modelling, we compare fermentation conditions and various products to optimise the processes. The models were then used in a simulation of an industrial-scale bubble column reactor. We find that increased temperatures favour gas transfer rates, particularly for the valuable and limiting H2 , while furthermore predicting an optimal feed composition of 9:1 mol H2 to mol CO2 . Metabolically, the increased non-growth associated maintenance requirements of thermophiles favours the formation of catabolic products. To assess the expansion of the product portfolio beyond acetate, both a product volatility analysis and a metabolic pathway model were implemented. In-situ recovery of volatile products is shown to be within range for acetone but challenging due to the extensive evaporation of water, while the direct production of more valuable compounds by acetogens is metabolically unfavourable compared to acetate and ethanol. We discuss alternative approaches to overcome these challenges to utilise acetogenic CO2 fixation to produce a wider range of carbon negative chemicals.

Holistic Approach to Process Design and Scale-Up for Itaconic Acid Production from Crude Substrates

Bio-based bulk chemicals such as carboxylic acids continue to struggle to compete with their fossil counterparts on an economic basis. One possibility to improve the economic feasibility is the use of crude substrates in biorefineries. However, impurities in these substrates pose challenges in fermentation and purification, requiring interdisciplinary research. This work demonstrates a holistic approach to biorefinery process development, using itaconic acid production on thick juice based on sugar beets with Ustilago sp. as an example. A conceptual process design with data from artificially prepared solutions and literature data from fermentation on glucose guides the simultaneous development of the upstream and downstream processes up to a 100 L scale. Techno-economic analysis reveals substrate consumption as the main constituent of production costs and therefore, the product yield is the driver of process economics. Aligning pH-adjusting agents in the fermentation and the downstream process is a central lever for product recovery. Experiments show that fermentation can be transferred from glucose to thick juice by changing the feeding profile. In downstream processing, an additional decolorization step is necessary to remove impurities accompanying the crude substrate. Moreover, we observe an increased use of pH-adjusting agents compared to process simulations.

Adaptive laboratory evolution of Bacillus subtilis to overcome toxicity of lignocellulosic hydrolysate derived from Distiller's dried grains with solubles (DDGS)

Microbial tolerance to toxic compounds formed during biomass pretreatment is a significant challenge to produce bio-based products from lignocellulose cost effectively. Rational engineering can be problematic due to insufficient prerequisite knowledge of tolerance mechanisms. Therefore, adaptive laboratory evolution was applied to obtain 20 tolerant lineages of Bacillus subtilis strains able to utilize Distiller's Dried Grains with Solubles-derived (DDGS) hydrolysate. Evolved strains showed both improved growth performance and retained heterologous enzyme production using 100% hydrolysate-based medium, whereas growth of the starting strains was essentially absent. Whole-genome resequencing revealed that evolved isolates acquired mutations in the global regulator codY in 15 of the 19 sequenced isolates. Furthermore, mutations in genes related to oxidative stress (katA, perR) and flagella function appeared in both tolerance and control evolution experiments without toxic compounds. Overall, tolerance adaptive laboratory evolution yielded strains able to utilize DDGS-hydrolysate to produce enzymes and hence proved to be a valuable tool for the valorization of lignocellulose.

Downscaling Industrial-Scale Syngas Fermentation to Simulate Frequent and Irregular Dissolved Gas Concentration Shocks

In large-scale syngas fermentation, strong gradients in dissolved gas (CO, H₂) concentrations are very likely to occur due to locally varying mass transfer and convection rates. Using Euler-Lagrangian CFD simulations, we analyzed these gradients in an industrial-scale external-loop gas-lift reactor (EL-GLR) for a wide range of biomass concentrations, considering CO inhibition for both CO and H₂ uptake. Lifeline analyses showed that micro-organisms are likely to experience frequent (5 to 30 s) oscillations in dissolved gas concentrations with one order of magnitude. From the lifeline analyses, we developed a conceptual scale-down simulator (stirred-tank reactor with varying stirrer speed) to replicate industrial-scale environmental fluctuations at bench scale. The configuration of the scale-down simulator can be adjusted to match a broad range of environmental fluctuations. Our results suggest a preference for industrial operation at high biomass concentrations, as this would strongly reduce inhibitory effects, provide operational flexibility and enhance the product yield. The peaks in dissolved gas concentration were hypothesized to increase the syngas-to-ethanol yield due to the fast uptake mechanisms in C. autoethanogenum. The proposed scale-down simulator can be used to validate such results and to obtain data for parametrizing lumped kinetic metabolic models that describe such short-term responses.

Dynamic Interplay between O2 Availability, Growth Rates, and the Transcriptome of Yarrowia lipolytica

Industrial-sized fermenters differ from the laboratory environment in which bioprocess development initially took place. One of the issues that can lead to reduced productivity on a large scale or even early termination of the process is the presence of bioreactor heterogeneities. This work proposes and adopts a design–build–test–learn-type workflow that estimates the substrate, oxygen, and resulting growth heterogeneities through a compartmental modelling approach and maps Yarrowia lipolytica-specific behavior in this relevant range of conditions. The results indicate that at a growth rate of 0.1 h−1, the largest simulated volume (90 m3) reached partial oxygen limitation. Throughout the fed-batch, the cells experienced dissolved oxygen values from 0 to 75% and grew at rates of 0 to 0.2 h−1. These simulated large-scale conditions were tested in small-scale cultivations, which elucidated a transcriptome with a strong downregulation of various transporter and central carbon metabolism genes during oxygen limitation. The relation between oxygen availability and differential gene expression was dynamic and did not show a simple on–off behavior. This indicates that Y. lipolytica can differentiate between different available oxygen concentrations and adjust its transcription accordingly. The workflow presented can be used for Y. lipolytica-based strain engineering, thereby accelerating bioprocess development.

Microbial lifelines in bioprocesses: From concept to application

Bioprocesses are scaled up for the production of large product quantities. With larger fermenter volumes, mixing becomes increasingly inefficient and environmental gradients get more prominent than in smaller scales. Environmental gradients have an impact on the microorganism's metabolism, which makes the prediction of large-scale performance difficult and can lead to scale-up failure. A promising approach for improved understanding and estimation of dynamics of microbial populations in large-scale bioprocesses is the analysis of microbial lifelines. The lifeline of a microbe in a bioprocess is the experience of environmental gradients from a cell's perspective, which can be described as a time series of position, environment and intracellular condition. Currently, lifelines are predominantly determined using models with computational fluid dynamics, but new technical developments in flow-following sensor particles and microfluidic single-cell cultivation open the door to a more interdisciplinary concept. We critically review the current concepts and challenges in lifeline determination and application of lifeline analysis, as well as strategies for the integration of these techniques into bioprocess development. Lifelines can contribute to a successful scale-up by guiding scale-down experiments and identifying strain engineering targets or bioreactor optimisations.

A scalable model for EPA and fatty acid production by Phaeodactylum tricornutum

Large-scale photoautotrophic production of microalgae has the potential to provide a sustainable supply of omega-3 fatty acids (eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)) for human and animal nutrition. This study presents a kinetic model for the EPA-producing microalga Phaeodactylum tricornutum in photoautotrophic conditions, with light and nitrogen being the growth limiting factors. The model was developed using a dataset obtained from bench-scale (5 L) cultures and was successfully validated against pilot-scale (50 L) cultures. This model is the first to predict the biomass and total fatty acid accumulation along with the EPA concentrations in the biomass and total fatty acid fraction for microalgae. The model was used to develop an optimized repeated-batch strategy; implementation of this led to increases in the biomass and EPA productivities of 50 and 20% respectively. This clearly indicates the potential of the model to be used as a tool in the design, optimization and scale-up of microalgal systems for EPA production.

Leads and hurdles to sustainable microbial bioplastic production

Indiscriminate usage, disposal and recalcitrance of petroleum-based plastics have led to its accumulation leaving a negative impact on the environment. Bioplastics, particularly microbial bioplastics serve as an ecologically sustainable solution to nullify the negative impacts of plastics. Microbial production of biopolymers like Polyhydroxyalkanoates, Polyhydroxybutyrates and Polylactic acid using renewable feedstocks as well as industrial wastes have gained momentum in the recent years. The current study outlays types of bioplastics, their microbial sources and applications in various fields. Scientific evidence on bioplastics has suggested a unique range of applications such as industrial, agricultural and medical applications. Though diverse microorganisms such as Alcaligenes latus, Burkholderia sacchari, Micrococcus species, Lactobacillus pentosus, Bacillus sp., Pseudomonas sp., Klebsiella sp., Rhizobium sp., Enterobacter sp., Escherichia sp., Azototobacter sp., Protomonas sp., Cupriavidus sp., Halomonas sp., Saccharomyces sp., Kluyveromyces sp., and Ralstonia sp. are known to produce bioplastics, the industrial production of bioplastics is still challenging. Thus this paper also provides deep insights on the advancements made to maximise production of bioplastics using different approaches such as metabolic engineering, rDNA technologies and multitude of cultivation strategies. Finally, the constraints to microbial bioplastic production and the future directions of research are briefed. Hence the present review emphasizes on the importance of using bioplastics as a sustainable alternative to petroleum based plastic products to diminish environmental pollution.

Scalability of microbial electrochemical technologies: Applications and challenges

During wastewater treatment, microbial electrochemical technologies (METs) are a promising means for in situ energy harvesting and resource recovery. The primary constraint for such systems is scaling them up from the laboratory to practical applications. Currently, most research (∼90%) has been limited to benchtop models because of bioelectrochemical, economic, and engineering design limitations. Field trials, i.e., 1.5 m³ bioelectric toilet, 1000 L microbial electrolysis cell and industrial applications of METs have been conducted, and their results serve as positive indicators of their readiness for practical applications. Multiple startup companies have invested in the pilot-scale demonstrations of METs for industrial effluent treatment. Recently, advances in membrane/electrode modification, understanding of microbe-electrode interaction, and feasibility of electrochemical redox reactions have provided new directions for realizing the practical application. This study reviews the scaling-up challenges, success stories for onsite use, and readiness level of METs for commercialization that is inexpensive and sustainable.

Multi-Objective Sustainability Optimization of Biomass Residues to Ethanol via Gasification and Syngas Fermentation: Trade-Offs between Profitability, Energy Efficiency, and Carbon Emissions

This work presents a strategy for optimizing the production process of ethanol via integrated gasification and syngas fermentation, a conversion platform of growing interest for its contribution to carbon recycling. The objective functions (minimum ethanol selling price (MESP), energy efficiency, and carbon footprint) were evaluated for the combinations of different input variables in models of biomass gasification, energy production from syngas, fermentation, and ethanol distillation, and a multi-objective genetic algorithm was employed for the optimization of the integrated process. Two types of waste feedstocks were considered, wood residues and sugarcane bagasse, with the former leading to lower MESP and a carbon footprint of 0.93 USD/L and 3 g CO2eq/MJ compared to 1.00 USD/L and 10 g CO2eq/MJ for sugarcane bagasse. The energy efficiency was found to be 32% in both cases. An uncertainty analysis was conducted to determine critical decision variables, which were found to be the gasification zone temperature, the split fraction of the unreformed syngas sent to the combustion chamber, the dilution rate, and the gas residence time in the bioreactor. Apart from the abovementioned objectives, other aspects such as water footprint, ethanol yield, and energy self-sufficiency were also discussed.

Exploiting unconventional prokaryotic hosts for industrial biotechnology

Developing cost-efficient biotechnological processes is a major challenge in replacing fossil-based industrial production processes. The remarkable progress in genetic engineering ensures efficient and fast tailoring of microbial metabolism for a wide range of bioconversions. However, improving intrinsic properties such as tolerance, handling, growth, and substrate consumption rates is still challenging. At the same time, synthetic biology tools are becoming easier applicable and transferable to nonmodel organisms. These trends have resulted in the exploitation of new and unconventional microbial systems with sophisticated properties, which render them promising hosts for the bio-based industry. Here, we highlight the metabolic and cellular capabilities of representative prokaryotic newcomers and discuss the potential and drawbacks of these hosts for industrial application.

A brief review on recent development of multidisciplinary engineering in fermentation of Saccharomyces cerevisiae

Fermentation technology has unprecedented potential to upgrade state-of-art biotechnology and refine the processes used in existing ones, taking into account of complex technical, economic and environmental factors. Given the economic importance and ongoing challenges of biotech sector, multidisciplinary engineering technologies is poised to become an increasingly important tool along with the emergence of modern technology and innovation. This article reviews recent technology advancement in the field of fermentation using Saccharomyces cerevisiae. Interesting research progress has been made by leveraging multiple engineering fields such as electrical engineering, information engineering, electrochemical engineering and new material development, leading to recent development of novel real-time probes (electronic nose technology, analysis of yeast morphology and metabolites, timely control of glucose feed), improved understanding of electro-fermentation (enhanced electronic transfer provision), as well as application of cost-effective and sustainable materials (bioreactor vessel manufactured from textile, and yeast immobilisation support matrix made from abundant natural biomass). To the best of our knowledge, the subject is reviewed for the first time in recent years. Furthermore, this review also constitutes a futuristic S. cerevisiae fermentation process based on the recent advancement discussed.

Waste to bioplastics: How close are we to sustainable polyhydroxyalkanoates production?

Increased awareness of environmental sustainability with associated strict environmental regulations has incentivized the pursuit of novel materials to replace conventional petroleum-derived plastics. Polyhydroxyalkanoates (PHAs) are appealing intracellular biopolymers and have drawn significant attention as a viable alternative to petrochemical based plastics not only due to their comparable physiochemical properties but also, their outstanding characteristics such as biodegradability and biocompatibility. This review provides a comprehensive overview of the recent developments on the involved PHA producer microorganisms, production process from different waste streams by both pure and mixed microbial cultures (MMCs). Bio-based PHA production, particularly using cheap carbon sources with MMCs, is getting more attention. The main bottlenecks are the low production yield and the inconsistency of the biopolymers. Bioaugmentation and metabolic engineering together with cost effective downstream processing are promising approaches to overcome the hurdles of commercial PHA production from waste streams.

Towards the Development of Digital Twins for the Bio-manufacturing Industry

The bio-manufacturing industry, along with other process industries, now has the opportunity to be engaged in the latest industrial revolution, also known as Industry 4.0. To successfully accomplish this, a physical-to-digital-to-physical information loop should be carefully developed. One way to achieve this is, for example, through the implementation of digital twins (DTs), which are virtual copies of the processes. Therefore, in this paper, the focus is on understanding the needs and challenges faced by the bio-manufacturing industry when dealing with this digitalized paradigm. To do so, two major building blocks of a DT, data and models, are highlighted and discussed. Hence, firstly, data and their characteristics and collection strategies are examined as well as new methods and tools for data processing. Secondly, modelling approaches and their potential of being used in DTs are reviewed. Finally, we share our vision with regard to the use of DTs in the bio-manufacturing industry aiming at bringing the DT a step closer to its full potential and realization.

Predicting By-Product Gradients of Baker’s Yeast Production at Industrial Scale: A Practical Simulation Approach

Scaling up bioprocesses is one of the most crucial steps in the commercialization of bioproducts. While it is known that concentration and shear rate gradients occur at larger scales, it is often too risky, if feasible at all, to conduct validation experiments at such scales. Using computational fluid dynamics equipped with mechanistic biochemical engineering knowledge of the process, it is possible to simulate such gradients. In this work, concentration profiles for the by-products of baker’s yeast production are investigated. By applying a mechanistic black-box model, concentration heterogeneities for oxygen, glucose, ethanol, and carbon dioxide are evaluated. The results suggest that, although at low concentrations, ethanol is consumed in more than 90% of the tank volume, which prevents cell starvation, even when glucose is virtually depleted. Moreover, long exposure to high dissolved carbon dioxide levels is predicted. Two biomass concentrations, i.e., 10 and 25 g/L, are considered where, in the former, ethanol production is solely because of overflow metabolism while, in the latter, 10% of the ethanol formation is due to dissolved oxygen limitation. This method facilitates the prediction of the living conditions of the microorganism and its utilization to address the limitations via change of strain or bioreactor design or operation conditions. The outcome can also be of value to design a representative scale-down reactor to facilitate strain studies.

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.

Bioprocess intensification: Cases that (don't) work

Development of affordable and low carbon biobased manufacturing depends critically on strategies that reduce cost and emission profiles. This paper indicates that efforts around the reduction of capital costs by intensification of process equipment need to be carefully weighed against the inherently fast increasing financial and climate costs of driving forces used for the intensification. The fundamental relation between capital expenditures (CAPEX) and operational expenditures (OPEX) of intensified and non-intensified biobased processes and their financial and climatic impacts are emphasized and provisionally explored for a few industrial processes. General learnings flag the importance in particular of OPEX minimisation for sustainable bio-economic development.

Data-driven in silico prediction of regulation heterogeneity and ATP demands of Escherichia coli in large-scale bioreactors

Escherichia coli exposed to industrial-scale heterogeneous mixing conditions respond to external stress by initiating short-term metabolic and long-term strategic transcriptional programs. In native habitats, long-term strategies allow survival in severe stress but are of limited use in large bioreactors, where microenvironmental conditions may change right after said programs are started. Related on/off switching of genes causes additional ATP burden that may reduce the cellular capacity for producing the desired product. Here, we present an agent-based data-driven model linked to computational fluid dynamics, finally allowing to predict additional ATP needs of Escherichia coli K12 W3110 exposed to realistic large-scale bioreactor conditions. The complex model describes transcriptional up- and downregulation dynamics of about 600 genes starting from subminute range covering 28 h. The data-based approach was extracted from comprehensive scale-down experiments. Simulating mixing and mass transfer conditions in a 54 m³ stirred bioreactor, 120,000 E. coli cells were tracked while fluctuating between different zones of glucose availability. It was found that cellular ATP demands rise between 30% and 45% of growth decoupled maintenance needs, which may limit the production of ATP-intensive product formation accordingly. Furthermore, spatial analysis of individual cell transcriptional patterns reveal very heterogeneous gene amplifications with hot spots of 50%-80% messenger RNA upregulation in the upper region of the bioreactor. The phenomenon reflects the time-delayed regulatory response of the cells that propagate through the stirred tank. After 4.2 h, cells adapt to environmental changes but still have to bear an additional 6% ATP demand.

Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor

BACKGROUND

Ethanol production through fermentation of gas mixtures containing CO, CO₂ and H₂ has just started operating at commercial scale. However, quantitative schemes for understanding and predicting productivities, yields, mass transfer rates, gas flow profiles and detailed energy requirements have been lacking in literature; such are invaluable tools for process improvements and better systems design. The present study describes the construction of a hybrid model for simulating ethanol production inside a 700 m³ bubble column bioreactor fed with gas of two possible compositions, i.e., pure CO and a 3:1 mixture of H₂ and CO₂.

RESULTS

Estimations made using the thermodynamics-based black-box model of microbial reactions on substrate threshold concentrations, biomass yields, as well as CO and H₂ maximum specific uptake rates agreed reasonably well with data and observations reported in literature. According to the bioreactor simulation, there is a strong dependency of process performance on mass transfer rates. When mass transfer coefficients were estimated using a model developed from oxygen transfer to water, ethanol productivity reached 5.1 g L^-1 h^-1; when the H₂/CO₂ mixture is fed to the bioreactor, productivity of CO fermentation was 19% lower. Gas utilization reached 23 and 17% for H₂/CO₂ and CO fermentations, respectively. If mass transfer coefficients were 100% higher than those estimated, ethanol productivity and gas utilization may reach 9.4 g L^-1 h^-1 and 38% when feeding the H₂/CO₂ mixture at the same process conditions. The largest energetic requirements for a complete manufacturing plant were identified for gas compression and ethanol distillation, being higher for CO fermentation due to the production of CO₂.

CONCLUSIONS

The thermodynamics-based black-box model of microbial reactions may be used to quantitatively assess and consolidate the diversity of reported data on CO, CO₂ and H₂ threshold concentrations, biomass yields, maximum substrate uptake rates, and half-saturation constants for CO and H₂ for syngas fermentations by acetogenic bacteria. The maximization of ethanol productivity in the bioreactor may come with a cost: low gas utilization. Exploiting the model flexibility, multi-objective optimizations of bioreactor performance might reveal how process conditions and configurations could be adjusted to guide further process development.

Advances in biological conversion technologies: new opportunities for reaction engineering

Reaction engineering needs to embrace biological conversion technologies, on the road to identify more sustainable routes for chemical manufacture.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

Scale-up of industrial microbial processes

Scaling up industrial microbial processes for commercial production is a high-stakes endeavor, requiring time and investment often exceeding that for laboratory microbe and process development. Omissions, oversights and errors can be costly, even fatal to the program. Approached properly, scale-up can be executed successfully. Three guiding principles are provided as a basis: begin with the end in mind; be diligent in the details; prepare for the unexpected. A detailed roadmap builds on these principles. There is a special emphasis on the fermentation step, which is usually the costliest and also impacts downstream processing. Examples of common scale-up mistakes and the recommended approaches are given. It is advised that engineering resources skilled in integrated process development and scale-up be engaged from the very beginning of microbe and process development to guide ongoing R&D, thus ensuring a smooth and profitable path to the large-scale commercial end.

Comparison of engineered Escherichia coli AF1000 and BL21 strains for (R)-3-hydroxybutyrate production in fed-batch cultivation

Accumulation of acetate is a limiting factor in recombinant production of (R)-3-hydroxybutyrate (3HB) by Escherichia coli in high-cell-density processes. To alleviate this limitation, this study investigated two approaches: (i) deletion of phosphotransacetylase (pta), pyruvate oxidase (poxB), and/or the isocitrate lyase regulator (iclR), known to decrease acetate formation, on bioreactor cultivations designed to achieve high 3HB concentrations. (ii) Screening of different E. coli strain backgrounds (B, BL21, W, BW25113, MG1655, W3110, and AF1000) for their potential as low acetate-forming, 3HB-producing platforms. Deletion of pta and pta-poxB in the AF1000 strain background was to some extent successful in decreasing acetate formation, but also dramatically increased excretion of pyruvate and did not result in increased 3HB production in high-cell-density fed-batch cultivations. Screening of the different E. coli strains confirmed BL21 as a low acetate-forming background. Despite low 3HB titers in low-cell-density screening, 3HB-producing BL21 produced five times less acetic acid per mole of 3HB, which translated into a 2.3-fold increase in the final 3HB titer and a 3-fold higher volumetric 3HB productivity over 3HB-producing AF1000 strains in nitrogen-limited fed-batch cultivations. Consequently, the BL21 strain achieved the hitherto highest described volumetric productivity of 3HB (1.52 g L⁻¹ h⁻¹) and the highest 3HB concentration (16.3 g L⁻¹) achieved by recombinant E. coli. Screening solely for 3HB titers in low-cell-density batch cultivations would not have identified the potential of this strain, reaffirming the importance of screening with the final production conditions in mind.

Bioprocess scale-up/down as integrative enabling technology: from fluid mechanics to systems biology and beyond

Efficient optimization of microbial processes is a critical issue for achieving a number of sustainable development goals, considering the impact of microbial biotechnology in agrofood, environment, biopharmaceutical and chemical industries. Many of these applications require scale-up after proof of concept. However, the behaviour of microbial systems remains unpredictable (at least partially) when shifting from laboratory-scale to industrial conditions. The need for robust microbial systems is thus highly needed in this context, as well as a better understanding of the interactions between fluid mechanics and cell physiology. For that purpose, a full scale-up/down computational framework is already available. This framework links computational fluid dynamics (CFD), metabolic flux analysis and agent-based modelling (ABM) for a better understanding of the cell lifelines in a heterogeneous environment. Ultimately, this framework can be used for the design of scale-down simulators and/or metabolically engineered cells able to cope with environmental fluctuations typically found in large-scale bioreactors. However, this framework still needs some refinements, such as a better integration of gas-liquid flows in CFD, and taking into account intrinsic biological noise in ABM.

Scale-up/Scale-down of microbial bioprocesses: a modern light on an old issue

The bio‐economy is in transit from innovation to commercialization. The bioprocess industry is expected to increasingly deliver bio‐products to the market, in large amounts, at high quality and at competitive cost levels. This requires flawless start‐up of new large‐scale bioprocesses and continuous improvement of running processes. Fermentation scale‐up and operation can benefit from recent advances in three areas: 1. computation‐driven design of scale‐down simulators, 2. omics‐driven metabolic engineering and 3. sensing and understanding of population heterogeneity. Integration of these fields requires a unified computational approach, linked to big data and simulated reality frameworks, of which the contours are becoming visible today.