Summary
Horizontal gene transfer (HGT) –the movement of genetic material between individuals– is a significant force fueling bacterial evolution. Through HGT, bacteria acquire new traits, develop new metabolic capabilities and learn to withstand harsh environmental conditions. However, in some cases, HGT brings genetic information that is not advantageous to its host. Despite its crucial relevance for bacterial ecology and evolution, understanding the selective forces that drive the success (or failure) of HGT remains a major challenge. Previous studies addressing this challenge ignored the fact that not all HGT events are alike: incoming DNA can be integrated into the host genome (e.g., transposons, integrons), or it can stand as a physically separated, autonomous DNA molecule (e.g., plasmids). This difference in genomic context poses several mechanistic constraints that are likely to alter the evolutionary outcome of HGT.
Here, I will present a conceptually novel approach that explicitly considers genomic context to uncover the selective drivers of HGT in bacterial populations. First, I will develop a new genetic technology to obtain high-throughput fitness measurements of thousands of HGT events. Then, I will use these data to identify and quantify the constraints that determine the success of HGT, both considering the intrinsic effects of the transferred DNA and the role of genomic context on host fitness. Specifically, I will measure the fitness effects of genetic transfers mediated by plasmids (Obj. 1) or integrated into the chromosome and, in the latter case, in different regions of the chromosome (Obj. 2). Finally, I will leverage the rules derived from these analyses to reconstruct the role of HGT in the evolution of a relevant human pathogen (Obj. 3). This project will provide a quantitative and mechanistic understanding of the selective forces driving HGT, expanding horizons in evolutionary microbiology.
Here, I will present a conceptually novel approach that explicitly considers genomic context to uncover the selective drivers of HGT in bacterial populations. First, I will develop a new genetic technology to obtain high-throughput fitness measurements of thousands of HGT events. Then, I will use these data to identify and quantify the constraints that determine the success of HGT, both considering the intrinsic effects of the transferred DNA and the role of genomic context on host fitness. Specifically, I will measure the fitness effects of genetic transfers mediated by plasmids (Obj. 1) or integrated into the chromosome and, in the latter case, in different regions of the chromosome (Obj. 2). Finally, I will leverage the rules derived from these analyses to reconstruct the role of HGT in the evolution of a relevant human pathogen (Obj. 3). This project will provide a quantitative and mechanistic understanding of the selective forces driving HGT, expanding horizons in evolutionary microbiology.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101077809 |
| Start date: | 01-03-2023 |
| End date: | 29-02-2028 |
| Total budget - Public funding: | 1 497 613,00 Euro - 1 497 613,00 Euro |
Cordis data
Original description
Horizontal gene transfer (HGT) –the movement of genetic material between individuals– is a significant force fueling bacterial evolution. Through HGT, bacteria acquire new traits, develop new metabolic capabilities and learn to withstand harsh environmental conditions. However, in some cases, HGT brings genetic information that is not advantageous to its host. Despite its crucial relevance for bacterial ecology and evolution, understanding the selective forces that drive the success (or failure) of HGT remains a major challenge. Previous studies addressing this challenge ignored the fact that not all HGT events are alike: incoming DNA can be integrated into the host genome (e.g., transposons, integrons), or it can stand as a physically separated, autonomous DNA molecule (e.g., plasmids). This difference in genomic context poses several mechanistic constraints that are likely to alter the evolutionary outcome of HGT.Here, I will present a conceptually novel approach that explicitly considers genomic context to uncover the selective drivers of HGT in bacterial populations. First, I will develop a new genetic technology to obtain high-throughput fitness measurements of thousands of HGT events. Then, I will use these data to identify and quantify the constraints that determine the success of HGT, both considering the intrinsic effects of the transferred DNA and the role of genomic context on host fitness. Specifically, I will measure the fitness effects of genetic transfers mediated by plasmids (Obj. 1) or integrated into the chromosome and, in the latter case, in different regions of the chromosome (Obj. 2). Finally, I will leverage the rules derived from these analyses to reconstruct the role of HGT in the evolution of a relevant human pathogen (Obj. 3). This project will provide a quantitative and mechanistic understanding of the selective forces driving HGT, expanding horizons in evolutionary microbiology.
Status
SIGNEDCall topic
ERC-2022-STGUpdate Date
31-07-2023
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