Optimization of polyhydroxyalkanoates bioproduction, based on a cybernetic mathematical model

Piccoli, Rosane A. M.; Quiroz, Luís Henrique Camargo; Fleury, Agenor de Toledo; Oliveira, Vinícius Almeida; Marteleto, Natália Bonifácio; Bonomi, Antonio

doi:10.1007/s43153-020-00047-5

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…Cybernetic models are used to describe the allocation of resources in the cellular system such as biomass into products and enzymes under multi‐substrate conditions (Poccia et al, 2014). For example, growth and PHA production from R. eutropha feeding on glucose, fructose, and propionic acid was modelled by considering the synthesis and decay of two specific enzymes (Piccoli et al, 2020). Richard's model describes a growth curve with lag, exponential, and a stationary phase where the total growth at a given time is represented by its quantitative limit, increase in rate and curve parameter (X. Wang et al, 2016).…”

Section: Dynamic Models In Biomass Growth and Pha Productionmentioning

confidence: 99%

Structural variability, implementational irregularities in mathematical modelling of polyhydroxyalkanoates (PHAs) production—A state‐of‐the‐art review

Lhamo

Mahanty

2022

Biotech & Bioengineering

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The rate and extent of microbial polyhydroxyalkanoates (PHAs) production rely on the availability of substrates, growth of microbial biomass, and intracellular accumulation of polymer under nitrogen‐limited conditions. The dynamics of PHAs production captured through various structured or unstructured models can be extended to design an optimal feeding strategy for process intensification. Large variability in process assumptions, choices of kinetics, and model complexity is expected depending on substrate(s), microbial metabolism, and discretization of the process under consideration. This communication attempts to review the estimation of stoichiometric yield coefficients, metabolic modelling, and choices of unstructured kinetics in microbial PHA production. Implementational irregularities in parameter estimation and quality check in modelling exercises have also been reviewed. It is observed that the scope of the majority of the “modelling” studies is confined to the estimation of stoichiometric parameters with limited utility. In dynamic models, microbial growth is often described using either Monod or logistic variants, while PHAs production adopts a Luedeking–Piret expression with or without substrate inhibition. Though model selection, regression with experimental data, parameter estimation, and model validation are integral parts of the exercise, very few provide sufficient coverage on all those aspects. Application of the model to control or optimize the bioprocess has rarely been attempted.

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Section: Dynamic Models In Biomass Growth and Pha Productionmentioning

confidence: 99%

Structural variability, implementational irregularities in mathematical modelling of polyhydroxyalkanoates (PHAs) production—A state‐of‐the‐art review

Lhamo

Mahanty

2022

Biotech & Bioengineering

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“…The model considers that a key enzyme is required to consume a given substrate in a multisubstrate environment [ 17 , 18 ]. The cybernetic model has been applied to optimize fed-batch recipes for the production of Rifamycin [19] , [20] , [21] and polyhydroxyalkanoates [22] .…”

Section: Introductionmentioning

confidence: 99%

High cell density cultivation of E. coli in shake flasks for the production of recombinant proteins

Ganjave

Dodia

Sunder

et al. 2022

Biotechnology Reports

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Highlights True fed-batch strategy for high cell density cultivation of E. coli in shake flask. Cybernetic model-based optimization of the feeding recipe. Biomass of 19.9–21.5 g DCW/L, in agreement with the model prediction. Volumetric productivity for tested proteins increased 8–34-fold compared to batch. Scale up of fed-batch recipe to bioreactor resulted in further 2.8-fold increase.

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“…Due to previous experience with the software TOMP, e. g. [63], solving a complex control problem where other methods, albeit carefully implemented from [64], were unsuccessful, it was chosen as optimizer.…”

Section: Selection Of Algorithmsmentioning

confidence: 99%

Tomografia de mama por ultrassom usando um modelo de elementos finitos.

Quiróz

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Before officially starting my studies I took two courses as a hearer, did the assignments and at the very end of that year i was victim of a robbery at home. My notebook was stolen, with all my work, and with the external backup drive attached to it, as I was just updating it. Many overdue thanks to the brave policemen from COE -Comando de Operações Especiais (Special Operations Commando), who spotted the burglar fleeing (in my car), pursued and arrested him: corporal MP Sidnei, third Sgt. MP Caetano, and all their patrol colleagues whose names I don't know -there were at least 4 police cars involved. I was unaware that my notebook was also stolen until I received it back at the Police Department, with the external drive still and dangerously hanging by the USB cable! Thanks to CAPES, who paid my PhD scholarship and a training scholarship for almost two months in Colorado, USA.Thanks to Timpel S.A. for the desktop computer they put at the lab for my research and for an additional trip to Fort Collins, when I was able to implement big changes to the simulation software and it began to run much faster.Thanks to my mother, who helped to pay my bills and expenses, they were higher than my humble scholarship! Thanks to prof. Jennifer Mueller, from Colorado State University (CSU), who received me in her Electrical Impedance Tomography (EIT) laboratory. More than that: when Covid-19 stroke and I had to leave Fort Collins in a hurry -in the last plane! -, it was impossible to bring back all my belongings, and she keeps those things in safety till now. Thanks to my neighbor Brendan DeJonge, who stored the backpack with my photo gear I forgot on the sidewalk in front of our houses. Almost a year later Talles Rattis would bring my camera and one lens to me, but, instead, surprised me with the complete backpack: thank you Talles, very much! Special thanks to my colleague Ely, who went to Fort Collins a few weeks earlier than me, and managed to rent a house from CSU and allowed me to be there with him -this made my stay viable, within my expenses allowance -; it was a great experience, with much work and also fun! Thanks to my colleague Rafael Mikio Nakanishi, who helped a lot giving me access to his studies and results, therefore I could compare my finite elements simulation with real data and, later, try to implement new techniques to speed up my simulations, solving the problem in the frequency domain. Thanks to Tayran Milá, also my colleague from the laboratory, who told about softwares I used to create a human breast model.Thanks to my family. Thanks also to all my former teachers, since the first years of school, who always taught me lessons for the life.Thanks to Julio Cezar Neves, a real Linux guru. You are a monster! In our short talk you pointed me in the right direction, and now I can generate lots of graphics using parallelism emphin the shell. You saved me a lot of time!

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Optimization of polyhydroxyalkanoates bioproduction, based on a cybernetic mathematical model

Cited by 3 publications

References 9 publications

Structural variability, implementational irregularities in mathematical modelling of polyhydroxyalkanoates (PHAs) production—A state‐of‐the‐art review

Structural variability, implementational irregularities in mathematical modelling of polyhydroxyalkanoates (PHAs) production—A state‐of‐the‐art review

High cell density cultivation of E. coli in shake flasks for the production of recombinant proteins

Tomografia de mama por ultrassom usando um modelo de elementos finitos.

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