(393b) Dynamics of Cell Induction in Enterococcus Faecalis in Controlled cCF10 and iCF10 Environments
AIChE Annual Meeting
2015 AIChE Annual Meeting Proceedings
Computing and Systems Technology Division
Computational Methods in Biological and Biomedical Systems
Tuesday, November 10, 2015 - 3:33pm to 3:51pm
Dynamics of Cell Induction in Enterococcus faecalis in Controlled cCF10 and iCF10 Environments
Vu Tran, Arpan Bandyopadhyaya, Gary Dunny, Doraiswami Ramkrishna and Wei-Shou Hu
The pathogen, Enterococcus faecalis, is a leading cause of hospital acquired infections. This species utilizes the mechanism of conjugation to transfer antibiotic resistance from plasmid-harboring antibiotic-resistant donors to plasmid-free antibiotic-sensitive recipients. Specifically, the plasmid pCF10 carried in the donors provide cells the ability to resist to antibiotics. The two types of signaling molecules which regulate conjugative transfer of this plasmid are inducer cCF10 and inhibitor iCF10. Peptide cCF10 are produced by recipients. In the presence of both cCF10 and donors in the environment, the peptides enter donor cells, leading to an induction of conjugation. Inhibitor iCF10, on the other hand, are produced by donors and functions to suppress the conjugation. Both types of signaling molecules, which are produced by cells to the environment, can then transfer to the donor cells. Depending on the domination of either cCF10 or iCF10, donors will have different responses: promoting the conjugation when the recipient cells are abundant and restraining the process when the recipient concentration is low.
We have formulated a mathematical stochastic model that describes the dynamic interaction and responses of both recipient and donor populations with respect to cCF10/iCF10 ratio in a planktonic environment. This model accounts for the following effects: 1/ molecular interaction between intracellular quantities prior to conjugation, 2/ mechanistic genetic regulation of the conjugations and the corresponding outcomes, and 3/ population level, signal peptides and donor/recipient population. The mechanism was cross examined using mutants which were impaired cCF10 and/or iCF10. In addition, transcriptome and proteome were evaluated by RNAseq and iTRAQ protemics repectively. Two population balances are constructed for both donors and recipients. Probability of successful transferring event has also been incorporated in the model. We anticipate that the successful rate of plasmid transfer will vary with both populations and also depend on the probability distribution of successful transferring events. A higher donor concentration means a higher number of available plasmids to transfer but also lead to more production of iCF10, suppressing the conjugation to avoid any wasteful plasmid harboring. This model will help evaluate these competitive effects in different scenarios and thus provides a full set of conditions at which some factors can be more dominant than others and has the potential to fully capture all the different effects from both donors and recipients. Understanding the balancing act of the signaling system may shed light on new ways of controlling the spread of antibiotic resistance.
Authors’ contact information:
Vu Tran: email@example.com
Arpan Bandyopadhyaya: firstname.lastname@example.org
Gary Dunny: email@example.com
Doraiswami Ramkrishna: firstname.lastname@example.org
Wei-Shou Hu: email@example.com
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