Numerical study of fluid flow, mass transfer and cell growth in a three-dimensional bioreactor for bone marrow culture

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Instrumentation and control of anaerobic digestion processes: a review and some research challenges

The final publication is available at Springer via http://dx.doi.org/10.1007/s11157-015-9382-6[EN] To enhance energy production from methane or resource recovery from digestate, anaerobic digestion processes require advanced instrumentation and control tools. Over the years, research on these topics has evolved and followed the main fields of application of anaerobic digestion processes: from municipal sewage sludge to liquid mainly industrial then municipal organic fraction of solid waste and agricultural residues. Time constants of the processes have also changed with respect to the treated waste from minutes or hours to weeks or months. Since fast closed loop control is needed for short time constant processes, human operator is now included in the loop when taking decisions to optimize anaerobic digestion plants dealing with complex solid waste over a long retention time. Control objectives have also moved from the regulation of key variables measured online to the prediction of overall process perfor- mance based on global off-line measurements to optimize the feeding of the processes. Additionally, the need for more accurate prediction of methane production and organic matter biodegradation has impacted the complexity of instrumentation and should include a more detailed characterization of the waste (e.g., biochemical fractions like proteins, lipids and carbohydrates)andtheirbioaccessibility andbiodegradability characteristics. However, even if in the literature several methodologies have been developed to determine biodegradability based on organic matter characterization, only a few papers deal with bioaccessibility assessment. In this review, we emphasize the high potential of some promising techniques, such as spectral analysis, and we discuss issues that could appear in the near future concerning control of AD processes.The authors acknowledge the financial support of INRA (the French National Institute for Agricultural Research), the French National Research Agency (ANR) for the "Phycover" project (project ANR-14-CE04-0011) and ADEME for Inter-laboratory assay financial support.Jimenez, J.; Latrille, E.; Harmand, J.; Robles Martínez, Á.; Ferrer Polo, J.; Gaida, D.; Wolf, C.... (2015). Instrumentation and control of anaerobic digestion processes: a review and some research challenges. Reviews in Environmental Science and Biotechnology. 14(4):615-648. doi:10.1007/s11157-015-9382-6S615648144Aceves-Lara CA, Latrille E, Steyer JP (2010) Optimal control of hydrogen production in a continuous anaerobic fermentation bioreactor. 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Development of a turbidostat photo-bioreactor to investigate the effects of process parameters on the physiology and growth of micro-algae

The deployment of micro-algae as a viable bioproduction platform for industrial scale manufacturing has been hampered by low process yields and complex downstream processing. Chlorella variabilis NC64A has recently gathered significant scientific attention due to its relationship with the Paramecium bursaria chloro-virus (PBCV1) which can simplify downstream processing for the bio-production of ethanol or hyaluronan. However, photoautotrophic process optimisation is far from trivial, in part due to the unique characteristics of light as a critical process parameter (CPP) and its complex interactions on the physiology and metabolism of photoautotrophic microalgae. In the present thesis, a formalised statistical Design of Experiments (DoE) approach was employed for the optimisation of biomass concentration during photoautotrophic growth in closed, controlled and artificially illuminated batch cultures. The process design space was explored in two sequential rounds; initially six CPPs were screened using a fractional factorial design before a higher resolution face-centred central composite design was used for further optimisation. In most batch systems, extracellular conditions are highly dynamic as cells continuously grow and proliferate. This constant state of change compounds any efforts to discern whether observed changes are due to an introduced perturbation or due to the cells’ response to the ever-changing culture environment. To this end, a turbidostat module was created for a batch photo-bioreactor (Algem Pro ®) to allow operation in a time invariant and highly controlled continuous fashion. The developed experimental set-up enabled the isolated study of the effect of two CPPs (light intensity and biomass concentration) on the specific growth rate. Furthermore, an optimisation problem was formulated to fit kinetic parameters from a nonlinear model to the experimentally observed specific growth rates of several turbidostatic cultures. Using the model, a dynamic light profile was designed for batch cultures for a given geometry; this profile increased the incident light intensity as a function of biomass concentration, ensuring that the maximum specific growth rate was maintained across the entire growth period. When compared against control light profiles (operated at a constant light intensity), the dynamic light profile lead to a 30% increase in biomass concentration, biomass productivity and photosynthetic efficiency. Thus highlighting the benefits of using dynamic light profiles over constant light profiles in artificially illuminated cultures

Immobilised growth factors for scalable cell therapy manufacturing platforms

Regenerative medicine has the potential to establish or restore normal function in defective tissues and organs. The realisation of such therapies is restricted due to costs, lack of scalability and inefficient manufacturing process controls. A major contributor to cost is the use of expensive growth factors supplemented into media at high concentrations. In vivo, growth factors exist in soluble, immobilised and transmembrane forms, expressed in a spatiotemporal fashion within the stem cell niche. In comparison to soluble equivalents, immobilised growth factors exhibit increased potency, distinct functional activities, improved cell phenotypic control and act in synergy with other soluble and immobilised ligands. To date, most research into immobilised growth factors has been restricted to planar cell culture surfaces such as tissue culture plastics which have limited scalability. To address the scalability limitations, a novel growth factor immobilisation technology was developed using magnetic microparticles which can be scaled with respect to surface area to volume ratio in standard stirred tank bioreactors. Three clinically relevant growth factors, SCF, TPO and GM-CSF were immobilised and were shown to remain functionally active where surface concentration could be manipulated in a number of ways. Through a series of experiments, it was demonstrated that immobilised growth factors exhibited ~10-fold increase in potency compared with soluble equivalents and remain stable for up to 192 hours following recycling during multiple media passages. Immobilised growth factors were able to expand more cells over a longer period of time after transient exposure and finally, the immobilisation technique was successfully applied to the expansion of umbilical cord derived haematopoietic stem cells using immobilised SCF. The immobilisation method described here has the potential to significantly reduce media costs in large scale cell manufacturing processes

Analysis and Control of Bacterial Populations in Synthetic Biology

Synthetic Biology is a new field of research that aims at engineering new functionalities in living beings. Analogously to electronic circuits, more advanced functionalities can be realised by putting together smaller functional modules that perform elementary tasks; however, the interaction of these basic pieces is somewhat complex and fragile. Therefore, to increase the robustness and reliability of the whole system, typical tools from Control Theory, such as feedback loops, can be employed. In the first part of this thesis we propose feedback control strategies to balance the gene expression of a bistable genetic circuit, known as genetic toggle switch, in an unstable region far away from its stable equilibria - a problem analogous to the stabilization of the inverted pendulum in mechanics. The effectiveness of the proposed control strategies is validated via realistic agent-based simulations of a bacterial population endowed with the genetic toggle switch. Later in the thesis we move towards the growth control of bacterial cells in bioreactors, introducing a novel open-source and versatile design of a turbidostat to host in vivo control experiments. In the last part, we want to control bioreactors to guarantee the coexistence of multiple species in the same environment. We analyse the dynamics of a simple one-chamber bioreactor, proposing control strategies to achieve the control goal. However, simple bioreactors have several drawback when the concentrations of multiple species are regulated at the same time; for these reason, we propose a novel layout for a bioreactor, with two growth chambers and a mixing one, to be used in multicellular in vivo control experiments

Multiple Intelligent Agents for Manufacturing Intensification (MIAMI): A Platform for Ranking Clonal Variation in Upstream Bioprocess Development

Antibody-based therapeutics are an important class of biotherapeutics for therapeutic applications. With the rising demand and increase in biotherapeutic products on the market, there lies the need for rapid bioprocess development. Clone selection is a critical and time-consuming step in upstream bioprocess development and it is a critical step to execute accurately. A Multiple Intelligent Agents for Manufacturing Intensification (MIAMI) is proposed to process raw data and evaluate clones of three commonly used host cells, Chinese Hamster Ovary (CHO), Escherichia coli (E. coli), and Pichia pastoris (P. pastoris). A search conducted for an IP-free protein sequence yielded the Anti-hepatitis B antibody. The whole antibody sequence was truncated to create a Fab’ fragment. Gene designs for three commonly used host cells, CHO, E. coli, and P. pastoris were created using the IP-free Anti-hepatitis B Fab’ fragment. The development of MIAMI identifies and addresses the necessity of creating a sophisticated code that evaluates clonal ranking based upon data sets. These data sets were collected using the IP-free Anti-hepatitis B gene designs and an existing AV4 gene design. The AV4 gene design was transformed into P. pastoris and repurposed as an inverse methanol detector. In 50mL shake flask culture, green fluorescence protein was detected when cultivating the AV4 strain using glycerol and sorbitol carbon source, while protein transcription was inhibited when using a methanol carbon source. Data collected from cultivating the AV4 strain in 800µL microtiter plates was used to develop the MIAMI software. The Anti-hepatitis B gene designs were established and characterized in 50mL shake flasks for E. coli and P. pastoris and a preliminary attempt to establish the gene design CHO. Using the data collected from automated cultivation of 8 different clones of Anti-hepatitis B E. coli and P. pastoris strains in 800µL microtiter plates scale using the TECAN, a manual ranking of the clones was performed. Scaling the cultivation up to 200mL DASGIPs microbioreactors, clonal ranking for both strains remained unchanged. A code was written in python for the processing of raw data. This was demonstrated on the collected HPLC data sets for the Anti-hepatitis B E. coli and P. pastoris strains, and the flow cytometer data set for the AV4 strain. Multiple agents were created for the development of MIAMI. An assay agent was created for analysing raw HPLC and flow cytometry data to identify and remove unwanted clonal variations. A scanning algorithm calculated the mean and standard deviation of the yields at three consecutive time points to identify a period of stable yield. A ranking algorithm takes into consideration the maximum stable yield achieved and the variability in the data point, giving these two factors a 75% and 25% weighting, MIAMI identifies the best performing clone. The MIAMI ranking came to the same conclusion as manual human ranking. The effectiveness of MIAMI was validated on the Anti-hepatitis B E. coli strain, being able to correctly identify a top performing clone with an optimal induction time, with a conservative estimate of 87% decrease in time taken when compared to manual evaluation. The MIAMI software significantly improved the timeliness of bioprocess development by accurately screening and evaluating clones. This frees up the time of the user while removing potential sources of human error. With the incorporation of further bioprocesses, MIAMI will become a powerful and effective tool for bioprocess development

Towards the implementation of distributed systems in synthetic biology

The design and construction of engineered biological systems has made great strides over the last few decades and a growing part of this is the application of mathematical and computational techniques to problems in synthetic biology. The use of distributed systems, in which an overall function is divided across multiple populations of cells, has the potential to increase the complexity of the systems we can build and overcome metabolic limitations. However, constructing biological distributed systems comes with its own set of challenges. In this thesis I present new tools for the design and control of distributed systems in synthetic biology. The first part of this thesis focuses on biological computers. I develop novel design algorithms for distributed digital and analogue computers composed of spatial patterns of communicating bacterial colonies. I prove mathematically that we can program arbitrary digital functions and develop an algorithm for the automated design of optimal spatial circuits. Furthermore, I show that bacterial neural networks can be built using our system and develop efficient design tools to do so. I verify these results using computational simulations. This work shows that we can build distributed biological computers using communicating bacterial colonies and different design tools can be used to program digital and analogue functions. The second part of this thesis utilises a technique from artificial intelligence, reinforcement learning, in first the control and then the understanding of biological systems. First, I show the potential utility of reinforcement learning to control and optimise interacting communities of microbes that produce a biomolecule. Second, I apply reinforcement learning to the design of optimal characterisation experiments within synthetic biology. This work shows that methods utilising reinforcement learning show promise for complex distributed bioprocessing in industry and the design of optimal experiments throughout biology

Optimal control of bioproduction in the presence of population heterogeneity

International audienceCell-to-cell variability, born of stochastic chemical kinetics, persists even in large isogenic populations. In the study of single-cell dynamics this is typically accounted for. However, on the population level this source of heterogeneity is often sidelined to avoid the inevitable complexity it introduces. The homogeneous models used instead are more tractable but risk disagreeing with their heterogeneous counterparts and may thus lead to severely suboptimal control of bioproduction. In this work, we introduce a comprehensive mathematical framework for solving bioproduction optimal control problems in the presence of heterogeneity. We study population-level models in which such heterogeneity is retained, and propose order-reduction approximation techniques. The reduced-order models take forms typical of homogeneous bioproduction models, making them a useful benchmark by which to study the importance of heterogeneity. Moreover, the derivation from the heterogeneous setting sheds light on parameter selection in ways a direct homogeneous outlook cannot, and reveals the source of approximation error. With view to optimally controlling bioproduction in microbial communities, we ask the question: when does optimising the reduced-order models produce strategies that work well in the presence of population heterogeneity? We show that, in some cases, homogeneous approximations provide remarkably accurate surrogate models. Nevertheless, we also demonstrate that this is not uniformly true: overlooking the heterogeneity can lead to significantly suboptimal control strategies. In these cases, the heterogeneous tools and perspective are crucial to optimise bioproduction

A Rapid, Small-Scale Method for Improving Fermentation Medium Performance

Cell biomass and chemicals (e.g. bioactive compounds) can be produced by fermentation. Optimising a fermentation system involves optimizing many variables such as determining the effect of inoculum quality and media components, and selecting the most appropriate fermenter design and operating conditions (such as agitation aeration and fermentation mode). Identifying the optimal media is very important because it can significantly affect product concentration, yield and productivity. However, the media contains many components so many trials need to be done, which makes the process laborious, expensive, open-ended, and often time-consuming. The data generated from the many trials can be difficult to analyse. This study developed a rapid, inexpensive small-scale technique to identify how media components affected the growth of Streptomyces hygroscopicus and its production of a secondary metabolite, the anti-tumour agent rapamycin. A method was developed using microtitre plates to screen the effect of three concentrations of nine media components on cell growth and rapamycin production using the Box-Behnken experimental design. Firstly, the methodology for microtitre plates was developed, which involved characterizing the physical parameters of a fermentation system, identifying the incubation time to minimize evaporation, modifying the assay method to deal with the small sample volumes, and developing an alternative method to determinate the rapamycin concentration that was cheaper than the HPLC method. Data from shake flasks trials (the normal screening method) were used to validate the microtitre method and to assess the latter's usefulness in predicting scale-up effects. Six media components - sodium chloride (NaCl), di-potassium orthophosphate (K2HPO4), l-aspartic acid, l-arginine, l-histidine and salt (formula 1) solution - significantly affected culture growth and/or rapamycin concentration. The regression tree method was used to indicate the importance and critical concentration range of each factor. The Pearson's product-moment value indicated a good correlation between data from microtitre plates and shake flasks (cell growth: r=0.75 p=0.016 n=8; rapamycin concentration r=0.92 p=0.08 n=6). The speed of the microtitre plate and shake methods were compared by assessing the total cycle time and the time required for various stages in the method. Performance of each method was assessed as cost of media and equipment. Using microtitre plates to screen and optimise media in terms of biomass and secondary metabolite production is faster and cheaper than using shake flasks. Labour efficiency for the numerous, repetitive, small-scale experiments was substantially increased. Trials could be run without well-to-well cross contamination. The regression tree statistics methodology successfully showed the effect of input variables on target variables and identified effective medium component concentrations and any interactions. It is recommended that the microtitre plate procedure developed in this research may be applied to any study investigating the optimum media composition for growing other Streptomyces spp. strains, in screening studies when searching for new bioactive molecules, or for characterizing natural or recombinant/mutated micro-organisms

Development of an eicosapentaenoic acid production bioprocess using an indigenous microalgal isolate

Eicosapentaenoic acid (EPA; 20:5) is an omega-3 polyunsaturated fatty acid of increasing interest as a nutraceutical. An indigenous microalgal isolate suitable for an EPA bioprocess was selected by screening monoalgal isolates from the Council for Scientific and Industrial Research (CSIR) micro-algal culture collection. A Cymbella diatom (A23.2) was selected for superior EPA production in both growth and stress conditions, using both fluorescent microscopy and flask studies. Studies investigated increasing biomass, improving EPA content, and optimising overall EPA productivity in a multi-stage bioprocess. Growth studies found self-regulatory systems in both phosphate and nitrate metabolism. These mechanisms were absent in silicate and bicarbonate consumption, prompting their optimisation in the bioprocess medium. Cultivation pH was found to have a statistically modelled optimal value of 7.2 and a light intensity at a low range of 60 – 70 ìmol.m-2.s-1 was found to be suitable. Nutrient and physicochemical parameters were assayed individually, and revealed cell productivities of between 2.0 x 108 to 3.0 x 108 cell.L-1.hr-1 in batch culture bioreactor studies. Further studies demonstrated the use of both nutrient stress and physicochemical stress to enhance EPA production. These results informed the choice of operating parameters for a proof of concept, multistage raceway-based EPA bioprocess, consisting of a single growth pond and three stress ponds linked in series. The growth phase EPA productivity data of 0.68 mg.L-1.day-1, was higher than that of the stress phase, supporting its classification as a growth-associated product. Further, the EPA productivity in the raceway was more than twice that of initial batch culture screening. Once experimental limitations are addressed, a re-design of the bioprocess can be undertaken by optimising growth phase residence time, medium flow-rate and partial/complete elimination of the stress phase. The EPA productivity of the diatom used in this work has the potential of reaching commercially viable values. The development of a commercial indigenous EPA producer has a dual impact, as it addresses various nutritional and medicinal market demands and improves the sustainability of the world’s fish stocks