Modulating Gene Expression within a Microbiome Based on Computational Models
Recent research in the field of bioinformatics and molecular biology has revealed the immense complexity and uniqueness of microbiomes, while also showcasing the impact of the symbiosis between a microbiome and its host or environment. A core property influencing this process is horizontal gene tran...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Biology |
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| Online Access: | https://www.mdpi.com/2079-7737/11/9/1301 |
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| author | Liyam Chitayat Levi Ido Rippin Moran Ben Tulila Rotem Galron Tamir Tuller |
| author_facet | Liyam Chitayat Levi Ido Rippin Moran Ben Tulila Rotem Galron Tamir Tuller |
| author_sort | Liyam Chitayat Levi |
| collection | DOAJ |
| description | Recent research in the field of bioinformatics and molecular biology has revealed the immense complexity and uniqueness of microbiomes, while also showcasing the impact of the symbiosis between a microbiome and its host or environment. A core property influencing this process is horizontal gene transfer between members of the bacterial community used to maintain genetic variation. The essential effect of this mechanism is the exposure of genetic information to a wide array of members of the community, creating an additional “layer” of information in the microbiome named the “plasmidome”. From an engineering perspective, introduction of genetic information to an environment must be facilitated into chosen species which will be able to carry out the desired effect instead of competing and inhibiting it. Moreover, this process of information transfer imposes concerns for the biosafety of genetic engineering of microbiomes as exposure of genetic information into unwanted hosts can have unprecedented ecological impacts. Current technologies are usually experimentally developed for a specific host/environment, and only deal with the transformation process itself at best, ignoring the impact of horizontal gene transfer and gene-microbiome interactions that occur over larger periods of time in uncontrolled environments. The goal of this research was to design new microbiome-specific versions of engineered genetic information, providing an additional layer of compatibility to existing engineering techniques. The engineering framework is entirely computational and is agnostic to the selected microbiome or gene by reducing the problem into the following set up: microbiome species can be defined as wanted or unwanted hosts of the modification. Then, every element related to gene expression (e.g., promoters, coding regions, etc.) and regulation is individually examined and engineered by novel algorithms to provide the defined expression preferences. Additionally, the synergistic effect of the combination of engineered gene blocks facilitates robustness to random mutations that might occur over time. This method has been validated using both computational and experimental tools, stemming from the research done in the iGEM 2021 competition, by the TAU group. |
| first_indexed | 2024-03-10T00:41:03Z |
| format | Article |
| id | doaj.art-4c81c43e343a4debb423360b0a129d76 |
| institution | Directory Open Access Journal |
| issn | 2079-7737 |
| language | English |
| last_indexed | 2024-03-10T00:41:03Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biology |
| spelling | doaj.art-4c81c43e343a4debb423360b0a129d762023-11-23T15:07:15ZengMDPI AGBiology2079-77372022-08-01119130110.3390/biology11091301Modulating Gene Expression within a Microbiome Based on Computational ModelsLiyam Chitayat Levi0Ido Rippin1Moran Ben Tulila2Rotem Galron3Tamir Tuller4Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv 997801, IsraelSackler Faculty of Medicine, Tel-Aviv University, Tel Aviv 997801, IsraelDepartment of Biomedical Engineering, Tel-Aviv University, Tel Aviv 997801, IsraelDepartment of Biomedical Engineering, Tel-Aviv University, Tel Aviv 997801, IsraelDepartment of Biomedical Engineering, Tel-Aviv University, Tel Aviv 997801, IsraelRecent research in the field of bioinformatics and molecular biology has revealed the immense complexity and uniqueness of microbiomes, while also showcasing the impact of the symbiosis between a microbiome and its host or environment. A core property influencing this process is horizontal gene transfer between members of the bacterial community used to maintain genetic variation. The essential effect of this mechanism is the exposure of genetic information to a wide array of members of the community, creating an additional “layer” of information in the microbiome named the “plasmidome”. From an engineering perspective, introduction of genetic information to an environment must be facilitated into chosen species which will be able to carry out the desired effect instead of competing and inhibiting it. Moreover, this process of information transfer imposes concerns for the biosafety of genetic engineering of microbiomes as exposure of genetic information into unwanted hosts can have unprecedented ecological impacts. Current technologies are usually experimentally developed for a specific host/environment, and only deal with the transformation process itself at best, ignoring the impact of horizontal gene transfer and gene-microbiome interactions that occur over larger periods of time in uncontrolled environments. The goal of this research was to design new microbiome-specific versions of engineered genetic information, providing an additional layer of compatibility to existing engineering techniques. The engineering framework is entirely computational and is agnostic to the selected microbiome or gene by reducing the problem into the following set up: microbiome species can be defined as wanted or unwanted hosts of the modification. Then, every element related to gene expression (e.g., promoters, coding regions, etc.) and regulation is individually examined and engineered by novel algorithms to provide the defined expression preferences. Additionally, the synergistic effect of the combination of engineered gene blocks facilitates robustness to random mutations that might occur over time. This method has been validated using both computational and experimental tools, stemming from the research done in the iGEM 2021 competition, by the TAU group.https://www.mdpi.com/2079-7737/11/9/1301population genomicsmicrobiome engineeringgene expressionhorizontal gene transferevolutionary systems biologysynthetic biology |
| spellingShingle | Liyam Chitayat Levi Ido Rippin Moran Ben Tulila Rotem Galron Tamir Tuller Modulating Gene Expression within a Microbiome Based on Computational Models Biology population genomics microbiome engineering gene expression horizontal gene transfer evolutionary systems biology synthetic biology |
| title | Modulating Gene Expression within a Microbiome Based on Computational Models |
| title_full | Modulating Gene Expression within a Microbiome Based on Computational Models |
| title_fullStr | Modulating Gene Expression within a Microbiome Based on Computational Models |
| title_full_unstemmed | Modulating Gene Expression within a Microbiome Based on Computational Models |
| title_short | Modulating Gene Expression within a Microbiome Based on Computational Models |
| title_sort | modulating gene expression within a microbiome based on computational models |
| topic | population genomics microbiome engineering gene expression horizontal gene transfer evolutionary systems biology synthetic biology |
| url | https://www.mdpi.com/2079-7737/11/9/1301 |
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