Biotechnology for secure biocontainment designs in an emerging bioeconomy

Arnolds, Kathleen L.; Dahlin, Lukas R.; Ding, Lin; Wu, Chao; Yu, Jianping; Xiong, Wei; Zuñiga, Cristal; Suzuki, Yo; Zengler, Karsten; Linger, Jeffrey G.; Guarnieri, Michael T.

doi:10.1016/j.copbio.2021.05.004

Cited by 31 publications

(20 citation statements)

References 51 publications

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“…Eukaryotic models are growing both in scale and scope, including organelle-specific metabolic features, multiple compartments, and transport reactions to connect the metabolism across compartments. Expansion of metabolic modeling to eukaryotic organisms envisions their application to increase precursor productiveness for bioenergy [51,52], biocontainment [53], and human health and disease [54,55].…”

Section: The Metabolic Complexity Of Eukaryotes Is Addressed In Gemsmentioning

confidence: 99%

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data

et al. 2021

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Genome-scale metabolic models (GEMs) enable the mathematical simulation of the metabolism of archaea, bacteria, and eukaryotic organisms. GEMs quantitatively define a relationship between genotype and phenotype by contextualizing different types of Big Data (e.g., genomics, metabolomics, and transcriptomics). In this review, we analyze the available Big Data useful for metabolic modeling and compile the available GEM reconstruction tools that integrate Big Data. We also discuss recent applications in industry and research that include predicting phenotypes, elucidating metabolic pathways, producing industry-relevant chemicals, identifying drug targets, and generating knowledge to better understand host-associated diseases. In addition to the up-to-date review of GEMs currently available, we assessed a plethora of tools for developing new GEMs that include macromolecular expression and dynamic resolution. Finally, we provide a perspective in emerging areas, such as annotation, data managing, and machine learning, in which GEMs will play a key role in the further utilization of Big Data.

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Section: The Metabolic Complexity Of Eukaryotes Is Addressed In Gemsmentioning

confidence: 99%

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data

et al. 2021

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“…Biocontainment of Genetically Engineered Algae strategies have been developed for microalgae and other industrially relevant microorganisms which achieve one or more of those aims (reviewed by Lee et al, 2018;Wang and Zhang, 2019;Kim and Lee, 2020;Arnolds et al, 2021;Kallergi et al, 2021). In synthetic auxotrophy, cells are modified to make their growth dependent on an unusual or nonnatural nutrient or an unnaturally high concentration of a nutrient.…”

Section: Introductionmentioning

confidence: 99%

“… Henley et al (2013) therefore, recommended the development of biocontainment strategies which reduce growth fitness in the natural environment, that are conditionally lethal to the cells when they are not in the lab or industrial setting, and that have reduced capability to transfer genetic material to other organisms. Since that report, many new genetic biocontainment strategies have been developed for microalgae and other industrially relevant microorganisms which achieve one or more of those aims (reviewed by Lee et al, 2018 ; Wang and Zhang, 2019 ; Kim and Lee, 2020 ; Arnolds et al, 2021 ; Kallergi et al, 2021 ). In synthetic auxotrophy, cells are modified to make their growth dependent on an unusual or nonnatural nutrient or an unnaturally high concentration of a nutrient.…”

Section: Introductionmentioning

confidence: 99%

“…To address the risks associated with outdoor growth of GE algae, several genetically encoded biocontainment systems have been developed. General strategies have included developing synthetic auxotrophy ( Figure 1B ) where cell growth is made dependent on some unusual nutrient, and genetic circuits that can sense a change in environmental conditions that indicates the cell has left the controlled conditions of the lab and induce expression of toxic proteins or suppress expression of essential genes ( Arnolds et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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Biocontainment of Genetically Engineered Algae

et al. 2022

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Algae (including eukaryotic microalgae and cyanobacteria) have been genetically engineered to convert light and carbon dioxide to many industrially and commercially relevant chemicals including biofuels, materials, and nutritional products. At industrial scale, genetically engineered algae may be cultivated outdoors in open ponds or in closed photobioreactors. In either case, industry would need to address a potential risk of the release of the engineered algae into the natural environment, resulting in potential negative impacts to the environment. Genetic biocontainment strategies are therefore under development to reduce the probability that these engineered bacteria can survive outside of the laboratory or industrial setting. These include active strategies that aim to kill the escaped cells by expression of toxic proteins, and passive strategies that use knockouts of native genes to reduce fitness outside of the controlled environment of labs and industrial cultivation systems. Several biocontainment strategies have demonstrated escape frequencies below detection limits. However, they have typically done so in carefully controlled experiments which may fail to capture mechanisms of escape that may arise in the more complex natural environment. The selection of biocontainment strategies that can effectively kill cells outside the lab, while maintaining maximum productivity inside the lab and without the need for relatively expensive chemicals will benefit from further attention.

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“…Auxotrophic mutants are generated by deleting genes responsible for the biosynthesis of key metabolites such as nucleotides and amino acids (Pronk 2002). Because auxotrophic mutants cannot grow in conditions lacking the key metabolite, they have been used for the biocontainment of various genetically modified organisms (Arnolds et al 2021;Clark and Maselko 2020;Lee et al 2018). Note that biocontainment is a technique for biorisk management to prevent the release of genetically modified organisms such as transformants into outdoor environments (outside the laboratory).…”

Section: Introductionmentioning

confidence: 99%

Selection of a histidine auxotrophic <i>Marchantia polymorpha</i> strain with an auxotrophic selective marker

Fukushima

Kodama

2022

Plant Biotechnology

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Marchantia polymorpha has emerged as a model liverwort species, with molecular tools increasingly available.In the present study, we developed an auxotrophic strain of M. polymorpha and an auxotrophic selective marker gene as new experimental tools for this valuable model system. Using CRISPR (clustered regularly interspaced palindromic repeats)/Cas9-mediated genome editing, we mutated the genomic region for IMIDAZOLEGLYCEROL-PHOSPHATE DEHYDRATASE (IGPD) in M. polymorpha to disrupt the biosynthesis of histidine (igpd). We modified an IGPD gene (IGPDm) with silent mutations, generating a histidine auxotrophic selective marker gene that was not a target of our CRISPR/Cas9-mediated genome editing. The M. polymorpha igpd mutant was a histidine auxotrophic strain, growing only on medium containing histidine. The igpd mutant could be complemented by transformation with the IGPDm gene, indicating that this gene could be used as an auxotrophic selective marker. Using the IGPDm marker in the igpd mutant background, we produced transgenic lines without the need for antibiotic selection. The histidine auxotrophic strain igpd and auxotrophic selective marker IGPDm represent new molecular tools for M. polymorpha research.

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Biotechnology for secure biocontainment designs in an emerging bioeconomy

Cited by 31 publications

References 51 publications

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data

Biocontainment of Genetically Engineered Algae

Selection of a histidine auxotrophic <i>Marchantia polymorpha</i> strain with an auxotrophic selective marker

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