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MIXed plastics biodegradation and UPcycling using microbial communities: EU Horizon 2020 project MIX-UP started January 2020

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ENVIRONMENTAL SCIENCES EUROPE 2021年第1期33卷 1-9页

作者： Ballerstedt, Hendrik Tiso, Till Wierckx, Nick Wei, Ren Averous, Luc Bornscheuer, Uwe O'Connor, Kevin Floehr, Tilman Jupke, Andreas Klankermayer, Jurgen Liu, Luo de Lorenzo, Victor Narancic, Tanja Nogales, Juan Perrin, Remi Pollet, Eric Prieto, Auxiliadora Casey, William Haarmann, Thomas Sarbu, Alexandru Schwaneberg, Ulrich Xin, Fengxue Dong, Weiliang Xing, Jiamin Chen, Guo-Qiang Tan, Tianwei Jiang, Min Blank, Lars M. Institute of Applied Microbiology (iAMB) Aachen Biology and Biotechnology (ABBt) RWTH Aachen University Worringerweg 1 52074 Aachen Germany Institute of Biotechnology (BIOTEC) Aachen Biology and Biotechnology (ABBt) RWTH Aachen University Worringerweg 3 52074 Aachen Germany Institute of Technical and Macromolecular Chemistry (ITMC) RWTH Aachen University Worringerweg 2 52074 Aachen Germany Fluid Process Engineering Aachen Process Technology (AVT) RWTH Aachen University Forckenbeckstraße 51 52074 Aachen Germany Institute of Bio- and Geosciences IBG-1: Biotechnology Research Center Jülich Wilhelm Johnen Straße 52428 Jülich Germany Institute of Biochemistry University of Greifswald Felix-Hausdorff-Str. 4 17487 Greifswald Germany BiOrbic Bioeconomy SFI Research Centre UCD Earth Institute and School of Biomolecular and Biomedical Science University College Dublin Belfield Dublin 4 Ireland Interdisciplinary Platform for Sustainable Plastics Towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC) Biological Research Center (CIB-CSIC) 28040 Madrid Spain BioTeam/ICPEES-ECPM UMR CNRS 7515 Université de Strasbourg 25 rue Becquerel 67087 Strasbourg Cedex 2 France SOPREMA Direction R&D 14 Rue Saint Nazaire 67100 Strasbourg France Bioplastech Ltd. Nova UCD Belfield Innovation Park University College Dublin Belfield Dublin 4 Ireland AB Enzymes GmbH Feldbergstraße 78 64293 Darmstadt Germany everwave GmbH Strüverweg 116 52070 Aachen Germany College of Biotechnology and Pharmaceutical Engineering Nanjing Tech University No. 30 Puzhu Road Nanjing 211816 PR China School of Life Sciences (SLS) Tsinghua University Beijing 100084 PR China State Key Laboratory of Biochemical Engineering Institute of Process Engineering (IPE) Chinese Academy of Sciences 1 North 2nd Street Zhongguancun Beijing 100190 PR China College of Life Science and Technology (CLST) Beijing University of Chemical Technology Beisanhuan EastRoad 15 Chaoyang Distri

This article introduces the EU Horizon 2020 research project MIX-UP, "Mixed plastics biodegradation and upcycling using microbial communities". The project focuses on changing the traditional linear value chain of plastics to a sustainable, biodegradable based one. Plastic mixtures contain five of the top six fossil-based recalcitrant plastics [polyethylene (PE), polyurethane (PUR), polypropylene (PP), polyethylene terephthalate (PET), polystyrene (PS)], along with upcoming bioplastics polyhydroxyalkanoate (PHA) and polylactate (PLA) will be used as feedstock for microbial transformations. Consecutive controlled enzymatic and microbial degradation of mechanically pre-treated plastics wastes combined with subsequent microbial conversion to polymers and value-added chemicals by mixed cultures. Known plastic-degrading enzymes will be optimised by integrated protein engineering to achieve high specific binding capacities, stability, and catalytic efficacy towards a broad spectrum of plastic polymers under high salt and temperature conditions. Another focus lies in the search and isolation of novel enzymes active on recalcitrant polymers. MIX-UP will formulate enzyme cocktails tailored to specific waste streams and strives to enhance enzyme production significantly. In vivo and in vitro application of these cocktails enable stable, self-sustaining microbiomes to convert the released plastic monomers selectively into value-added products, key building blocks, and biomass. Any remaining material recalcitrant to the enzymatic activities will be recirculated into the process by physicochemical treatment. The Chinese-European MIX-UP consortium is multidisciplinary and industry-participating to address the market need for novel sustainable routes to valorise plastic waste streams. The project's new workflow realises a circular (bio)plastic economy and adds value to present poorly recycled plastic wastes where mechanical and chemical plastic recycling show limits.

关键词： PHA Polyhydroxyalkanoate Synthetic biology Plastic recycling Plastic crisis Metabolic engineering Microbial consortia Mixed plastics valorisation Biobased plastic Depolymerisation

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Laccase immobilized on magnetic nanoparticles by dopamine polymerization for 4-chlorophenol removal

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Green Energy & Environment 2017年第4期2卷 393-400页

作者： Di Zhang Manfeng Deng Hongbin Cao Songping Zhang He Zhao Beijing Engineering Research Center of Process Pollution Control Division of Environment Technology and Engineering Institute of Process EngineeringChinese Academy of Sciences Collaborative Innovation Center of Chemical Science and Engineering State Key Laboratory of Biochemical Engineering Institute of Process Engineering Chinese Academy of Sciences

In this work, a new immobilization method based on dopamine(DA) self-polymerization was developed for laccase immobilization on magnetic nanoparticles(Fe_3O_4 NPs). To optimize the immobilization condition including reaction pH, DA concentration and enzyme concentration, a central composite response surface method was applied. The optimal condition was determined as p H value of 5.92, laccase concentration of 0.25 mg mL^(-1) and DA concentration of 12.74 mg mL^(-1), under which a high enzyme activity recovery of 88.17% was *** comparing with free laccase, the stabilities of immobilized laccase towards p H, thermostability, storage were enhanced *** 60% of relative activity for immobilized laccase was remained after being incubated for 6 h at 50℃, but the free laccase only remained 25%. After 40 days of storage at 4℃, the laccase immobilized by DA kept about 89% of its original activity, but the free laccase only retained 48%. After recycled 10 times, the relative activity of immobilized laccase still retained 70%. The immobilized laccase was then applied to catalyze the degradation of 4-chlorophenol(4-CP), 86% percentage of 4-CP was removed within 2 h. After degraded 10 times, the relative activity of immobilized laccase still remained 64% of its initial activity, which exhibits an excellent reusability and operational stability.

关键词： Magnetic nanoparticle Laccase Dopamine Immobilization 4-Chlorophenol removal

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Parameter estimations in predictive microbiology: How to build statistically sound secondary models 9

Parameter estimations in predictive microbiology: How to bui...

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9th International Conference on Simulation and Modelling in the Food and Bio-Industry, FOODSIM 2016

作者： Akkermans, Simen Logist, Filip Vanimpe, Jan F.M. KU Leuven Department of Chemical Engineering BioTeC - Chemical and Biochemical Process Technology and Control OPTEC - Optimization in Engineering Center-of-Excellence CPMF2 - Flemish Cluster Predictive Microbiology in Foods Gebroeders De Smetstraat 1 GentB-9000 Belgium

ISBN: (纸本)9789077381922

When building models to describe the effect of environmental conditions on the microbial growth rate, parameter estimations can be performed either with a onestep method, i.e., directly on the cell density measurements, or in a two-step method, i.e., via the estimated growth rates. The two-step method is often preferred due to its simplicity. The current research demonstrates that the two-step method is, however, only valid if the correct data transformation is applied and a strict experimental protocol is followed for all experiments. Moreover, the one-step method leads to a better approximation of the confidence intervals on the estimated parameters. Therefore, the one-step method is preferred and the two-step method should be avoided.

关键词： Parameter estimation

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Development of vacuum-packed meat-based model systems for the evaluation of the food intrinsic complexity on Listeria monocytogenes growth at refrigeration and abuse temperatures 9

Development of vacuum-packed meat-based model systems for th...

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9th International Conference on Simulation and Modelling in the Food and Bio-Industry, FOODSIM 2016

作者： Baka, Maria Noriega, Estefanía Van Langendonck, Kristof Vanimpe, Jan F.M. KU Leuven Department of Chemical Engineering BioTeC - Chemical and Biochemical Process Technology and Control OPTEC - Optimization in Engineering Center-of-Excellence CPMF2 - Flemish Cluster Predictive Microbiology in Foods Gebroeders De Smetstraat 1 GentB-9000 Belgium

ISBN: (纸本)9789077381922

Food intrinsic complexity ((micro)structure, composition and physicochemical characteristics) influences microbial growth. In this study, food (model) systems with variable (micro)structural complexity, compositional and physicochemical characteristics were developed. The model systems targeted the following (micro)structures: liquids, aqueous gels, emulsions, gelled emulsions, and canned meat, which is a food product, classified as a gelled emulsion. The growth dynamics of Listeria monocytogenes were studied at 4, 8 and 12°C in/on the developed model systems, which covered the whole spectrum of food (micro)structure. The composition and physicochemical characteristics of canned meat and gelled emulsions targeted Frankfurter sausages. Results indicated that L. monocytogenes grows faster on canned meat, indicating that microbial growth is possibly underestimated in/on model systems than real foods.

关键词： Meats

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Role of differential plating-based methods in the detection of sublethal injury induced to Listeria monocytogenes by natural plant extracts 9

Role of differential plating-based methods in the detection ...

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9th International Conference on Simulation and Modelling in the Food and Bio-Industry, FOODSIM 2016

作者： Verheyen, Davy Baka, Maria Noriega, Estefanía Vanimpe, Jan F.M. KU Leuven Department of Chemical Engineering BioTeC - Chemical and Biochemical Process Technology and Control OPTEC - Optimization in Engineering Center-of-Excellence CPMF2 - Flemish Cluster Predictive Microbiology in Foods Gebroeders De Smetstraat 1 GentB-9000 Belgium

ISBN: (纸本)9789077381922

Recently, food researchers are investigating natural plant extracts as milder food preservation technologies. Milder treatments might cause sublethal injury (SI), which is a major food safety concern. This study demonstrates that both grape seed extract and garlic extract are suitable to inactivate Listeria monocytogenes. Both extracts cause a significant amount of SI, which increases at more severe treatments. Finally, experimental results indicated that the thin agar layer (TAL) method is a promising alternative to the traditional method, which uses the difference between plate counts on general and selective media to determine SI. The TAL method is unable to determine the total viable population of healthy and injured micro-organisms as adequately as the general medium in the traditional method, but can be used to determine SI in real food products.

关键词： Food preservation

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Parametric uncertainty propagation for robust dynamic optimization of biological networks

Parametric uncertainty propagation for robust dynamic optimi...

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American control Conference

作者： Philippe Nimmegeers Dries Telen Mickey Beetens Filip Logist Jan Van Impe KU Leuven BioTeC+ - Chemical and Biochemical Process Technology and Control & OPTEC - Center of Excellence: Optimization in Engineering Department of Chemical Engineering Ghent Belgium

ISBN: (纸本)9781467386838

An important trend in biochemical industry is the search for a more sustainable operation. This requires an improved design and operation of processes with respect to economic, environmental and safety aspects. For an accurate macroscopic process control, multi-scale models based on microscopic systems biology insights are increasingly used. However, model uncertainty as well as external disturbances are inevitably present. Hence, there is a need for approaches which can guarantee process safety despite this presence of uncertainty in the model parameters. Therefore, techniques for the propagation of the parametric uncertainties to the states are vital for a robust process control. In this work, the potential of the polynomial chaos expansion approach is investigated for optimal control of a four step linear pathway with Michaelis-Menten kinetics by manipulating the enzyme expression rates.

关键词： Uncertainty Mathematical model Chaos Robustness Optimization Biological system modeling Linear programming Biological system modeling chaos linear programming Uncertainty Propagation Mathematical Model model parameters Uncertainty Robustness design improvement Parametric external disturbance model uncertainty

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Towards nonlinear model predictive control with integrated experiment design

Towards nonlinear model predictive control with integrated e...

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American control Conference

作者： D. Telen M. Vallerio S. Bhonsale F. Logist J. Van Impe KU Leuven - Department of Chemical Engineering BioTeC - Chemical and Biochemical Process Technology and Control Gebroeders De Smetstraat 1 B9000-Ghent Belgium

ISBN: (纸本)9781467386838

Nonlinear model predictive control (NMPC) has become an important tool in the control and optimization of nonlinear systems in a variety of engineering applications. A requirement for a well-performing NMPC implementation is obtaining and maintaining an appropriate mathematical model of the considered system. For linear dynamic systems, developments have been made to incorporate information content objectives in closed loop, i.e., to solve the dual control problem. However, formulations for nonlinear dynamic systems remain scarce. In this paper we extend the formulation for the integration of experiment design of linear dynamic systems to nonlinear dynamic systems resulting in a NMPC formulation with integrated experiment design (iED-NMPC). This results for nonlinear systems in the presence of a nonlinear matrix inequality. We propose to reformulate this nonlinear matrix inequality using Sylvester's criterion. The suggested approach allows us to replace the nonlinear matrix inequality by additional nonlinear constraints. The resulting formulation can subsequently be implemented in existing NMPC software packages.

关键词： Linear matrix inequalities Mathematical model Nonlinear dynamical systems Ellipsoids Computational modeling Optimization linear matrix inequalities nonlinear model predictive control Ellipsoid Nonlinear dynamical systems Experimental Design Computational modeling Mathematical Model Nonlinear dynamic systems Nonlinear systems Dynamic systems management tools

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Predictive modelling under dynamic conditions in food processing environments 9

Predictive modelling under dynamic conditions in food proces...

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9th International Conference on Simulation and Modelling in the Food and Bio-Industry, FOODSIM 2016

作者： Valdramidis, Vasilis P. Dolan, Kirk Telen, Dries Vanimpe, Jan F.M. Department of Food Studies and Environmental Health Faculty of Health Sciences University of Malta MsidaMSD2080 Malta Department of Food Science and Human Nutrition 135 Trout Food Science Building Michigan State University East LansingMI48824 United States KU Leuven Department of Chemical Engineering BioTeC - Chemical and Biochemical Process Technology and Control Gebroeders De Smetstraat 1 GentB-9000 Belgium

ISBN: (纸本)9789077381922

Commercial thermal and non-thermal processes for food are dynamic, where temperature, water activity, and other variables can change with time. An efficient process design requires knowing the parameters of microbial mathematical models describing the underlying dynamic processes. However, most research to obtain these parameters is performed under simulated constant conditions. The objective of this session is to address some of the recent developments to model predictive microbial dynamics of food processes describing examples on how to perform inverse (parameter estimation) problems for a number of different primary-secondary models. Therefore, appropriate experimental designs, such as optimal experimental design, parameter identification under dynamic conditions, and properly statistical indices to discriminate among models are discussed.

关键词： Inverse problems

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Fault Identification in Batch processes Using process Data or Contribution Plots: A Comparative Study ∗

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IFAC-PapersOnLine 2015年第8期48卷 1282-1287页

作者： Sam Wuyts Geert Gins Pieter Van den Kerkhof Jan Van Impe KU Leuven department of Chemical Engineering Chemical & Biochemical Process Technology & Control (BioTeC) Willem de Croylaan 46 3001 Leuven

In statistical process monitoring, contribution plots are commonly used by operators and experts to identify the root cause of abnormal events. Because contribution plots suffer from fault smearing - an effect that possibly masks the cause of an upset - this paper investigates whether automated fault identification can be improved by using process data instead of contributions. Hereto, both approaches (i.e., using either the sensor measurements or their contributions as inputs for a classification model) are tested on the benchmark penicillin fermentation process Pensim, implemented in RAYMOND. To optimize the performance of each approach, different manipulations of both the process data and the variable contributions are introduced based on the nature of the occurring faults. It is observed that these manipulations have a large influence on the classification performance. Furthermore, this paper demonstrates that fault smearing negatively affects the classification based on the variable contributions. It is concluded that automated fault identification is improved by using the process data rather than the variable contributions as model inputs for the case study investigated.

关键词： Batch processes Fault identification Statistical process control (SPC) Classification models Contribution plots

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Structural identifiability analysis of the Anaerobic Digestion Model No. 1 using a local algebraic observability approach

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IFAC-PapersOnLine 2015年第1期48卷 470-475页

作者： Joost Lauwers Philippe Nimmegeers Filip Logist Jan Van Impe KU Leuven Department of Chemical Engineering Chemical and Biochemical Process Technology and Control (BioTeC) W. de Croylaan 46 B-3001 Leuven Belgium.

Structural identifiability is a prerequisite for a successful parameter estimation of a dynamical model. ‘Structural’ relates to the theoretical possibility of estimating the parameters under the idealized conditions that all measurements are perfect and continuous, and that the model is a perfect representation of the real process. In this research, the Anaerobic Digestion Model No. 1 (ADM1) is analysed. The model is of great importance in anaerobic digestion modelling. Due to its numerous parameters, however, its structural identifiability is an open question. The used method investigates the local algebraic observability, which is a sufficient condition for structural local identifiability. Different measurement scenarios were tested, as well as the influence of the choice of inputs. The obtained results are optimistic, since in most conditions, nearly all of the initial conditions of the states and the kinetic, stoichiometric and composition parameters are found to be structurally locally identifiable if almost any one of the states is measured. Unidentifiability occurs for the parameters pertaining to inerts and the cations and anions. For these parameters, nevertheless, structurally identifiable parameter combinations are found.

关键词： Identifiability Observability Parameter Estimation Dynamic modelling ADM1

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