Genome modularity and synthetic biology: Engineering systems

Mol, Milsee; Kabra, Ritika; Singh, Shailza

doi:10.1016/j.pbiomolbio.2017.08.002

Cited by 14 publications

(10 citation statements)

References 101 publications

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“…The reason is that modularity confers design and functional benefits to distinct classes of systems. Therefore, for disciplines as diverse as evolutionary robotics [ 7 , 8 ], artificial intelligence [ 9 , 10 ], neuroscience [ 11 , 12 ] and synthetic biology [ 13 , 14 ], it is relevant to study the effects of a modular organization and how to construct modular systems. Advances in this direction may lead to new useful therapeutical and technological applications.…”

Section: Introductionmentioning

confidence: 99%

On the role of sparseness in the evolution of modularity in gene regulatory networks

Espinosa‐Soto

2018

PLoS Comput Biol

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Modularity is a widespread property in biological systems. It implies that interactions occur mainly within groups of system elements. A modular arrangement facilitates adjustment of one module without perturbing the rest of the system. Therefore, modularity of developmental mechanisms is a major factor for evolvability, the potential to produce beneficial variation from random genetic change. Understanding how modularity evolves in gene regulatory networks, that create the distinct gene activity patterns that characterize different parts of an organism, is key to developmental and evolutionary biology. One hypothesis for the evolution of modules suggests that interactions between some sets of genes become maladaptive when selection favours additional gene activity patterns. The removal of such interactions by selection would result in the formation of modules. A second hypothesis suggests that modularity evolves in response to sparseness, the scarcity of interactions within a system. Here I simulate the evolution of gene regulatory networks and analyse diverse experimentally sustained networks to study the relationship between sparseness and modularity. My results suggest that sparseness alone is neither sufficient nor necessary to explain modularity in gene regulatory networks. However, sparseness amplifies the effects of forms of selection that, like selection for additional gene activity patterns, already produce an increase in modularity. That evolution of new gene activity patterns is frequent across evolution also supports that it is a major factor in the evolution of modularity. That sparseness is widespread across gene regulatory networks indicates that it may have facilitated the evolution of modules in a wide variety of cases.

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Section: Introductionmentioning

confidence: 99%

On the role of sparseness in the evolution of modularity in gene regulatory networks

Espinosa‐Soto

2018

PLoS Comput Biol

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“…Minimal genomes can be defined as reduced genomes containing only the genetic material which is essential for a cell to reproduce (Glass et al, 2017). Studying and engineering minimal genomes can be instrumental both to understand the most essential tasks a cell must perform to sustain life, and to obtain optimal chassis for synthetic biology applications, with reduced cell burden and superior robustness (Moya et al, 2009;Hutchison et al, 2016;Ceroni and Ellis, 2018;Mol et al, 2018;Landon et al, 2019).…”

Section: Design and Engineering Of Reduced Genomesmentioning

confidence: 99%

Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology

Marucci

Barberis

Karr

et al. 2020

Front. Bioeng. Biotechnol.

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Computer-aided design (CAD) for synthetic biology promises to accelerate the rational and robust engineering of biological systems. It requires both detailed and quantitative mathematical and experimental models of the processes to (re)design biology, and software and tools for genetic engineering and DNA assembly. Ultimately, the increased precision in the design phase will have a dramatic impact on the production of designer cells and organisms with bespoke functions and increased modularity. CAD strategies require quantitative models of cells that can capture multiscale processes and link genotypes to phenotypes. Here, we present a perspective on how whole-cell, multiscale models could transform design-build-test-learn cycles in synthetic biology. We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems. We also discuss several challenges for the realization of our vision. The possibility to describe and build whole-cells in silico offers an opportunity to develop increasingly automatized, precise and accessible CAD tools and strategies.

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“…To date, three genome editing technologies are available: (1) Transcription activator like effector nucleases (TALENs) [5], (2) zinc finger nucleases (ZFNs) [6], and (3) clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPRassociated protein 9 (Cas9) [7]. These technologies, more CRISPR/Cas9, are carried out in studies where synthetic transcription factors are also involved [8], [9], [10]. The advent of the genome editing technologies has addressed numerous issues in many therapeutic areas, but there has not been made much effort in using these techniques for treating diabetes.…”

Section: Introductionmentioning

confidence: 99%

Modulation of Insulin Gene Expression with CRISPR/Cas9-based Transcription Factors

Alzhanuly

Mukhatayev

Botbayev

et al. 2021

Open Access Maced J Med Sci

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Background: The discovery and use of CRISPR/Cas9 technology have enabled researchers throughout the globe to continuously edit genomes for the benefit of science and medicine. Diabetes type I is one field of medicine where CRISPR/Cas9 has a strong potential for cell therapy development. The long-lasting paucity of healthy cells for clinical transplantation into diabetic patients has led to the search of new methods for producing β-cells from other human cell types. Embryonic stem cells are being studied worldwide as one most promising solution of this need. Aim: The aim of the study is to to check the feasibility of modulating human insulin transcription using CRISPR/Cas9-based synthetic transcription regulation factors. Results: A new approach for creating potential therapeutic donor cells with enhanced and suppressed insulin production based on one of the latest achievements of human genome editing was developed. Both synthetic transcription activator (VP64) and transcription repressor (KRAB) proteins were shown to function adequately well as a part of the whole CRISPR/Cas9-based system. We claim that our results have a lot to offer and can bring light to many studies where numerous labs are struggling on to treat this disease.

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Genome modularity and synthetic biology: Engineering systems

Cited by 14 publications

References 101 publications

On the role of sparseness in the evolution of modularity in gene regulatory networks

On the role of sparseness in the evolution of modularity in gene regulatory networks

Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology

Modulation of Insulin Gene Expression with CRISPR/Cas9-based Transcription Factors

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