Principles of Modular Design and Control in Complex Systems

A topical collection in Processes (ISSN 2227-9717). This collection belongs to the section "Biological Processes and Systems".

Viewed by 20993

Editor

Department of Chemical and Biomolecular Engineering, The University of Tennessee, Knoxville, TN 37996, USA
Interests: systems and synthetic biology; metabolic engineering; computational biology; CRISPR technology; modular design; modular cell engineering; pathogen inactivation; bioenergy and biofuels; bioesters; microbial robustness

Topical Collection Information

Dear Colleagues,

Modular design is at the core of modern engineering, which enables rapid, efficient, and reproducible construction and maintenance of complex systems across applications. Remarkably, modularity has recently been discovered as a governing principle in natural biological systems from genes to proteins to pathways to cells and microbial communities. The convergent knowledge of natural and engineered modular systems will be the key to drive modern biotechnology to address emergent challenges associated with health, food, energy, and the environment. This Special Issue calls for contributions across a broad range of disciplines that address recent experimental, computational and/or modeling advancements in modular design and control of complex systems.

Dr. Cong T. Trinh
Collection Editor

Manuscript Submission Information

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Keywords

  • Modular design
  • Modular control
  • Modular cell
  • Modular enzyme
  • Protein network
  • Gene regulatory network
  • Multiobjective optimization
  • Metabolic network analysis
  • Graph algorithms
  • Control theory

Published Papers (4 papers)

2023

Jump to: 2020, 2019

15 pages, 712 KiB  
Article
Model-Based Condition Monitoring of Modular Process Plants
by Philipp Wetterich, Maximilian M. G. Kuhr and Peter F. Pelz
Processes 2023, 11(9), 2733; https://doi.org/10.3390/pr11092733 - 13 Sep 2023
Viewed by 754
Abstract
The process industry is confronted with rising demands for flexibility and efficiency. One way to achieve this is modular process plants, which consist of pre-manufactured modules with their own decentralized intelligence. Plants are then composed of these modules as unchangeable building blocks and [...] Read more.
The process industry is confronted with rising demands for flexibility and efficiency. One way to achieve this is modular process plants, which consist of pre-manufactured modules with their own decentralized intelligence. Plants are then composed of these modules as unchangeable building blocks and can be easily re-configured for different products. Condition monitoring of such plants is necessary, but the available solutions are not applicable. The authors of this paper suggest an approach in which model-based symptoms are derived from a few measurements and observers that are based on the manufacturer’s knowledge. The comparisons of redundant observers lead to residuals that are classified to obtain symptoms. These symptoms can be communicated to the plant control and are inputs to an easily adaptable diagnosis. The implementation and validation at a modular mixing plant showcase the feasibility and potential of this approach. Full article
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Graphical abstract

2020

Jump to: 2023, 2019

25 pages, 669 KiB  
Review
Key Challenges in Designing CHO Chassis Platforms
by Anis Hamdi, Diana Széliová, David E. Ruckerbauer, Isabel Rocha, Nicole Borth and Jürgen Zanghellini
Processes 2020, 8(6), 643; https://doi.org/10.3390/pr8060643 - 28 May 2020
Cited by 8 | Viewed by 7845
Abstract
Following the success of and the high demand for recombinant protein-based therapeutics during the last 25 years, the pharmaceutical industry has invested significantly in the development of novel treatments based on biologics. Mammalian cells are the major production systems for these complex biopharmaceuticals, [...] Read more.
Following the success of and the high demand for recombinant protein-based therapeutics during the last 25 years, the pharmaceutical industry has invested significantly in the development of novel treatments based on biologics. Mammalian cells are the major production systems for these complex biopharmaceuticals, with Chinese hamster ovary (CHO) cell lines as the most important players. Over the years, various engineering strategies and modeling approaches have been used to improve microbial production platforms, such as bacteria and yeasts, as well as to create pre-optimized chassis host strains. However, the complexity of mammalian cells curtailed the optimization of these host cells by metabolic engineering. Most of the improvements of titer and productivity were achieved by media optimization and large-scale screening of producer clones. The advances made in recent years now open the door to again consider the potential application of systems biology approaches and metabolic engineering also to CHO. The availability of a reference genome sequence, genome-scale metabolic models and the growing number of various “omics” datasets can help overcome the complexity of CHO cells and support design strategies to boost their production performance. Modular design approaches applied to engineer industrially relevant cell lines have evolved to reduce the time and effort needed for the generation of new producer cells and to allow the achievement of desired product titers and quality. Nevertheless, important steps to enable the design of a chassis platform similar to those in use in the microbial world are still missing. In this review, we highlight the importance of mammalian cellular platforms for the production of biopharmaceuticals and compare them to microbial platforms, with an emphasis on describing novel approaches and discussing still open questions that need to be resolved to reach the objective of designing enhanced modular chassis CHO cell lines. Full article
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2019

Jump to: 2023, 2020

13 pages, 1859 KiB  
Article
Comparison of Multi-Objective Evolutionary Algorithms to Solve the Modular Cell Design Problem for Novel Biocatalysis
by Sergio Garcia and Cong T. Trinh
Processes 2019, 7(6), 361; https://doi.org/10.3390/pr7060361 - 11 Jun 2019
Cited by 21 | Viewed by 3697
Abstract
A large space of chemicals with broad industrial and consumer applications could be synthesized by engineered microbial biocatalysts. However, the current strain optimization process is prohibitively laborious and costly to produce one target chemical and often requires new engineering efforts to produce new [...] Read more.
A large space of chemicals with broad industrial and consumer applications could be synthesized by engineered microbial biocatalysts. However, the current strain optimization process is prohibitively laborious and costly to produce one target chemical and often requires new engineering efforts to produce new molecules. To tackle this challenge, modular cell design based on a chassis strain that can be combined with different product synthesis pathway modules has recently been proposed. This approach seeks to minimize unexpected failure and avoid task repetition, leading to a more robust and faster strain engineering process. In our previous study, we mathematically formulated the modular cell design problem based on the multi-objective optimization framework. In this study, we evaluated a library of state-of-the-art multi-objective evolutionary algorithms (MOEAs) to identify the most effective method to solve the modular cell design problem. Using the best MOEA, we found better solutions for modular cells compatible with many product synthesis modules. Furthermore, the best performing algorithm could provide better and more diverse design options that might help increase the likelihood of successful experimental implementation. We identified key parameter configurations to overcome the difficulty associated with multi-objective optimization problems with many competing design objectives. Interestingly, we found that MOEA performance with a real application problem, e.g., the modular strain design problem, does not always correlate with artificial benchmarks. Overall, MOEAs provide powerful tools to solve the modular cell design problem for novel biocatalysis. Full article
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25 pages, 3711 KiB  
Review
Modular Engineering of Biomass Degradation Pathways
by Julie E. Chaves, Gerald N. Presley and Joshua K. Michener
Processes 2019, 7(4), 230; https://doi.org/10.3390/pr7040230 - 23 Apr 2019
Cited by 9 | Viewed by 6992
Abstract
Production of fuels and chemicals from renewable lignocellulosic feedstocks is a promising alternative to petroleum-derived compounds. Due to the complexity of lignocellulosic feedstocks, microbial conversion of all potential substrates will require substantial metabolic engineering. Non-model microbes offer desirable physiological traits, but also increase [...] Read more.
Production of fuels and chemicals from renewable lignocellulosic feedstocks is a promising alternative to petroleum-derived compounds. Due to the complexity of lignocellulosic feedstocks, microbial conversion of all potential substrates will require substantial metabolic engineering. Non-model microbes offer desirable physiological traits, but also increase the difficulty of heterologous pathway engineering and optimization. The development of modular design principles that allow metabolic pathways to be used in a variety of novel microbes with minimal strain-specific optimization will enable the rapid construction of microbes for commercial production of biofuels and bioproducts. In this review, we discuss variability of lignocellulosic feedstocks, pathways for catabolism of lignocellulose-derived compounds, challenges to heterologous engineering of catabolic pathways, and opportunities to apply modular pathway design. Implementation of these approaches will simplify the process of modifying non-model microbes to convert diverse lignocellulosic feedstocks. Full article
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