Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids
Inactivation of β‐lactam antibiotics by resistant bacteria is a ‘cooperative’ behavior that may allow sensitive bacteria to survive antibiotic treatment. However, the factors that determine the fraction of resistant cells in the bacterial population remain unclear, indicating a fundamental gap in ou...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | en_US |
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Nature Publishing Group
2015
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| Online Access: | http://hdl.handle.net/1721.1/98066 https://orcid.org/0000-0001-6843-9843 https://orcid.org/0000-0002-4083-7433 https://orcid.org/0000-0003-4583-8555 https://orcid.org/0000-0001-5532-2822 |
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| author | Chao, Hui Xiao Artemova, Tatiana Gore, Jeff Yurtsev, Eugene Datta, Manoshi Sen |
| author2 | Massachusetts Institute of Technology. Computational and Systems Biology Program |
| author_facet | Massachusetts Institute of Technology. Computational and Systems Biology Program Chao, Hui Xiao Artemova, Tatiana Gore, Jeff Yurtsev, Eugene Datta, Manoshi Sen |
| author_sort | Chao, Hui Xiao |
| collection | MIT |
| description | Inactivation of β‐lactam antibiotics by resistant bacteria is a ‘cooperative’ behavior that may allow sensitive bacteria to survive antibiotic treatment. However, the factors that determine the fraction of resistant cells in the bacterial population remain unclear, indicating a fundamental gap in our understanding of how antibiotic resistance evolves. Here, we experimentally track the spread of a plasmid that encodes a β‐lactamase enzyme through the bacterial population. We find that independent of the initial fraction of resistant cells, the population settles to an equilibrium fraction proportional to the antibiotic concentration divided by the cell density. A simple model explains this behavior, successfully predicting a data collapse over two orders of magnitude in antibiotic concentration. This model also successfully predicts that adding a commonly used β‐lactamase inhibitor will lead to the spread of resistance, highlighting the need to incorporate social dynamics into the study of antibiotic resistance. |
| first_indexed | 2024-09-23T08:45:07Z |
| format | Article |
| id | mit-1721.1/98066 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:45:07Z |
| publishDate | 2015 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/980662022-09-23T14:18:02Z Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids Chao, Hui Xiao Artemova, Tatiana Gore, Jeff Yurtsev, Eugene Datta, Manoshi Sen Massachusetts Institute of Technology. Computational and Systems Biology Program Massachusetts Institute of Technology. Department of Physics Yurtsev, Eugene Chao, Hui Xiao Datta, Manoshi Sen Artemova, Tatiana Gore, Jeff Inactivation of β‐lactam antibiotics by resistant bacteria is a ‘cooperative’ behavior that may allow sensitive bacteria to survive antibiotic treatment. However, the factors that determine the fraction of resistant cells in the bacterial population remain unclear, indicating a fundamental gap in our understanding of how antibiotic resistance evolves. Here, we experimentally track the spread of a plasmid that encodes a β‐lactamase enzyme through the bacterial population. We find that independent of the initial fraction of resistant cells, the population settles to an equilibrium fraction proportional to the antibiotic concentration divided by the cell density. A simple model explains this behavior, successfully predicting a data collapse over two orders of magnitude in antibiotic concentration. This model also successfully predicts that adding a commonly used β‐lactamase inhibitor will lead to the spread of resistance, highlighting the need to incorporate social dynamics into the study of antibiotic resistance. National Science Foundation (U.S.). Graduate Research Fellowship (Grant 0645960) Massachusetts Institute of Technology. Undergraduate Research Opportunities Program American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowship 2015-08-11T14:31:07Z 2015-08-11T14:31:07Z 2013-08 2013-10 Article http://purl.org/eprint/type/JournalArticle 1744-4292 http://hdl.handle.net/1721.1/98066 Yurtsev, Eugene A, Hui Xiao Chao, Manoshi S Datta, Tatiana Artemova, and Jeff Gore. “Bacterial Cheating Drives the Population Dynamics of Cooperative Antibiotic Resistance Plasmids.” Molecular Systems Biology 9 (August 6, 2013). © 2013 EMBO and Macmillan Publishers Limit https://orcid.org/0000-0001-6843-9843 https://orcid.org/0000-0002-4083-7433 https://orcid.org/0000-0003-4583-8555 https://orcid.org/0000-0001-5532-2822 en_US http://dx.doi.org/10.1038/msb.2013.39 Molecular Systems Biology Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf Nature Publishing Group Nature |
| spellingShingle | Chao, Hui Xiao Artemova, Tatiana Gore, Jeff Yurtsev, Eugene Datta, Manoshi Sen Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids |
| title | Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids |
| title_full | Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids |
| title_fullStr | Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids |
| title_full_unstemmed | Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids |
| title_short | Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids |
| title_sort | bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids |
| url | http://hdl.handle.net/1721.1/98066 https://orcid.org/0000-0001-6843-9843 https://orcid.org/0000-0002-4083-7433 https://orcid.org/0000-0003-4583-8555 https://orcid.org/0000-0001-5532-2822 |
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