Designing mixed-culture bioprocesses by means of bioenergetics models
Regueira López, Alberte; Bevilacqua, Riccardo; Mauricio Iglesias, Miguel; Lema Rodicio, Juan Manuel; Carballa Arcos, Marta
- Published
- 2017
- Language
- en
Abstract
Mixed culture fermentations (MCFs) are recognised as an inexpensive means to produce high-added-valueproducts from low-grade biomass. However, developing a new bioprocess based on this technology is a challenging task. Although mixed cultures are advantageous when treating complex substrates in a continuous operation, they also pose a fundamental challenge: we are not able to fully understand the mechanisms that control these populations. In consequence, it is difficult to control the operation and to foresee the outcome of the process. In this context, BIOCHEM project (Figure 1) aims at designing a methodology for the development of a novel process based on MCFs focusing on two aspects: reaching a high productivity and achieving a high selectivity of the desired product(s)
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BIOCHEM project: Designing mixed-culture processes for a circular economy Designing mixed-culture bioprocesses by means of bioenergetics models A. Regueira, R. Bevilacqua M. MauricioIglesias, J. M. Lema, M. Carballa Mixed culture processes Future perspectives in BIOCHEM The design of a bioprocess that uses a mixed culture is a hard task. BIOCHEM tackles this issue with a special focus on the use of modelling tools. References González-Cabaleiro et al.2015. Metabolic Energy-Based Modelling Explains Product Yielding in Anaerobic Mixed Culture Fermentations. PLoS ONE, 10. Batstone et al.2002. The IWA Anaerobic Digestion Model No 1 (ADM1). Water Sci Technol, 10, 65-73. Acknowledgements This activity is supported by ERA-IB-2 project BIOCHEM (PCIN2016-102), funded by MINECO, and by the Spanish Ministry of Education through the FPU scholarship (FPU14/05457) 1Determine the stoichiometry and select the pH with the bioenergetics model Results from the model suggest to select a pH≤5.5 to ensure a high butyrate stoichiometric coefficient. 2Select the HRT with the kinetic model Two regions of interest arise from the simulation results: : Maximum productivity. Interesting for very high added-value products : Maximum yield. Appropriate for bulk chemicals and difficult-toseparate products (butyrate). Including•protein and lipids in our models for assessing complex substrates. To•incorporate separation processes (e.g. In situ Product Recovery) in our modelling framework in collaboration with TUHH. The•expected end result is a virtual plant for early stage simulation of mixed culture fermentations. APPROACH USC: Selecting the operating conditions Glucose Butyrate: ?g/L d Case study: to produce butyrate from a glucose-rich waste (4 g/L) Butyrate Acetate Ethanol 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 Stoichio. Coeffs. (mol/mol Glu) pH 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 515 25 35 45 55 65 mol But/mol Glu g But/L d HRT (h) Productivity (g But/L d)Yield (mol But/mol Glu) ConsPros + Treat complex substrates No sterilisation Very variable outcome Complex and not fully understood Novel bioprocesses are hard to design Robust Select the microbial population cathode anode +- CH3COOCH3COOCH3COOCH3COOCH3COOconcentrated product Separate the product Select the operating conditions pH HRT T Protein-rich substrates Carbohydrate-rich substrates Lipid-rich substrates pH = 5.5 HRT ≈ 35 h Yield = 0.4 mol But/mol Glu Productivity = 1 g But/L d EARLY-STAGE DESIGN RESULTS HRT ? pH ?
