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Cell Host Microbe. 2017 Sep 13;22(3):263-268.e4. doi: 10.1016/j.chom.2017.08.001. Epub 2017 Aug 31.

Using Engineered Bacteria to Characterize Infection Dynamics and Antibiotic Effects In Vivo.

Author information

1
Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA; Division of Infectious Diseases, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
2
Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA.
3
Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA; Institute for Medical Engineering and Science, MIT, Cambridge, MA 02139, USA; Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Synthetic Biology Center, MIT, Cambridge, MA 02139, USA; Harvard-MIT Program in Health Sciences and Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA. Electronic address: jimjc@mit.edu.

Abstract

Synthetic biology has focused on engineering microbes to synthesize useful products or to serve as living diagnostics and therapeutics. Here we utilize a host-derived Escherichia coli strain engineered with a genetic toggle switch as a research tool to examine in vivo replicative states in a mouse model of chronic infection, and to compare in vivo and in vitro bacterial behavior. In contrast to the effect of antibiotics in vitro, we find that the fraction of actively dividing bacteria remains relatively high throughout the course of a chronic infection in vivo and increases in response to antibiotics. Moreover, the presence of non-dividing bacteria in vivo does not necessarily lead to an antibiotic-tolerant infection, in contrast to expectations from in vitro experiments. These results demonstrate the utility of engineered bacteria for querying pathogen behavior in vivo, and the importance of validating in vitro studies of antibiotic effects with in vivo models.

KEYWORDS:

chronic infection; genetic toggle switch; synthetic biology

PMID:
28867388
DOI:
10.1016/j.chom.2017.08.001
[Indexed for MEDLINE]
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