Hybrid semiparametric systems for quantitative sequence-activity modeling of synthetic biological parts

Portela, Rui M C; Stosch, Moritz von; Oliveira, Rui

doi:10.1093/synbio/ysy010

Cited by 7 publications

(2 citation statements)

References 39 publications

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“…[45] Mathematical models have been used to engineer and optimize RBSs. [42,[46][47][48][49][50][51] The design of tailor-made RBSs for translation optimization of specific mRNAs considers the mRNA folding in the cell, which is determined by the sequence of the transcribed gene. [42,46,50] We made use of the RBS calculator devised by Salis in 2011, [42] whose thermodynamic model has been constantly updated.…”

Section: Strong Rbs Enhances Expression Of Basp By One Order Of Magnimentioning

confidence: 99%

Plasmid Design for Tunable Two‐Enzyme Co‐Expression Promotes Whole‐Cell Production of Cellobiose

Schwaiger

Voit

Dobiášová

et al. 2020

Biotechnology Journal

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Catalyst development for biochemical cascade reactions often follows a “whole‐cell‐approach” in which a single microbial cell is made to express all required enzyme activities. Although attractive in principle, the approach can encounter limitations when efficient overall flux necessitates precise balancing between activities. This study shows an effective integration of major design strategies from synthetic biology to a coherent development of plasmid vectors, enabling tunable two‐enzyme co‐expression in E. coli, for whole‐cell‐production of cellobiose. An efficient transformation of sucrose and glucose into cellobiose by a parallel (countercurrent) cascade of disaccharide phosphorylases requires the enzyme co‐expression to cope with large differences in specific activity of cellobiose phosphorylase (14 U mg−1) and sucrose phosphorylase (122 U mg−1). Mono‐ and bicistronic co‐expression strategies controlling transcription, transcription‐translation coupling or plasmid replication are analyzed for effect on activity and stable producibility of the whole‐cell‐catalyst. A key role of bom (basis of mobility) for plasmid stability dependent on the ori is reported and the importance of RBS (ribosome binding site) strength is demonstrated. Whole cell catalysts show high specific rates (460 µmol cellobiose min−1 g−1 dry cells) and performance metrics (30 g L−1; ∼82% yield; 3.8 g L−1 h−1 overall productivity) promising for cellobiose production.

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Section: Strong Rbs Enhances Expression Of Basp By One Order Of Magnimentioning

confidence: 99%

Plasmid Design for Tunable Two‐Enzyme Co‐Expression Promotes Whole‐Cell Production of Cellobiose

Schwaiger

Voit

Dobiášová

et al. 2020

Biotechnology Journal

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“…The structure of a hybrid model is flexible depending on the approach to combine data‐driven models and mechanistic models (von Stosch, Oliveira, Peres, & Feyo de Azevedo, 2014). In recent years, there have been several studies attempting to apply this strategy into biochemical and general chemical engineering applications (Bangi & Kwon, 2020; Carinhas et al, 2011; Portela, von Stosch, & Oliveira, 2018).…”

Section: Introductionmentioning

confidence: 99%

Combining model structure identification and hybrid modelling for photo‐production process predictive simulation and optimisation

Zhang

Savage

Cho

2020

Biotech & Bioengineering

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Integrating physical knowledge and machine learning is a critical aspect of developing industrially focused digital twins for monitoring, optimisation, and design of microalgal and cyanobacterial photo-production processes. However, identifying the correct model structure to quantify the complex biological mechanism poses a severe challenge for the construction of kinetic models, while the lack of data due to the time-consuming experiments greatly impedes applications of most data-driven models. This study proposes the use of an innovative hybrid modelling approach that consists of a simple kinetic model to govern the overall process dynamic trajectory and a data-driven model to estimate mismatch between the kinetic equations and the real process. An advanced automatic model structure identification strategy is adopted to simultaneously identify the most physically probable kinetic model structure and minimum number of data-driven model parameters that can accurately represent multiple data sets over a broad spectrum of process operating conditions. Through this hybrid modelling and automatic structure identification framework, a highly accurate mathematical model was constructed to simulate and optimise an algal lutein production process. Performance of this hybrid model for long-term predictive modelling, optimisation, and online self-calibration is demonstrated and thoroughly discussed, indicating its significant potential for future industrial application.

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Hybrid Semiparametric Modeling: A Modular Process Systems Engineering Approach for the Integration of Available Knowledge Sources

Azevedo¹,

Diaz²,

Prado-Rúbio³

et al. 2019

Systems Engineering in the Fourth Industrial Revolution

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Hybrid semiparametric systems for quantitative sequence-activity modeling of synthetic biological parts

Cited by 7 publications

References 39 publications

Plasmid Design for Tunable Two‐Enzyme Co‐Expression Promotes Whole‐Cell Production of Cellobiose

Plasmid Design for Tunable Two‐Enzyme Co‐Expression Promotes Whole‐Cell Production of Cellobiose

Combining model structure identification and hybrid modelling for photo‐production process predictive simulation and optimisation

Hybrid Semiparametric Modeling: A Modular Process Systems Engineering Approach for the Integration of Available Knowledge Sources

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