Evolution of Plasmid-Mediated Antibiotic Resistance in the Clinical Context  Alvaro San Millan  Trends in Microbiology  Volume 26, Issue 12, Pages 978-985 (December 2018) DOI: 10.1016/j.tim.2018.06.007 Copyright © 2018 The Author Terms and Conditions

Figure 1 Key Figure: Studying the Evolution of Plasmid-Mediated Antibiotic Resistance (AR) in the Gut Microbiome For a Figure360 author presentation of Figure 1, see the figure legend at https://doi.org/10.1016/j.tim.2018.06.007. Analysis of the evolutionary dynamics of plasmid-mediated AR in the gut. (A) Evolutionary dynamics of plasmid–bacterium associations in the gut microbiome of a hospitalized patient. A plasmid-carrying nosocomial pathogen colonizes the patient’s gut and transfers an AR plasmid to a resident bacterium in the gut microbiome. The plasmid produces a fitness cost but is selected thanks to antibiotic treatment (see legend: blue, high fitness; white, low fitness). Over time, this cost is compensated for, denoted by the colour change of some of the plasmid-carrying clones. (B) Methods for studying the evolutionary dynamics of plasmid-carrying bacteria from the gut microbiome, combining fitness assays and molecular analyses (omics). Left: Plasmid fitness effects can be measured either by curing existing plasmids from bacterial clones or by constructing a range of new plasmid–bacterium associations. Right: Intrapatient compensatory evolution events can be detected in temporal series of plasmid-carrying clones. Figure360: an author presentation of Figure 1 Trends in Microbiology 2018 26, 978-985DOI: (10.1016/j.tim.2018.06.007) Copyright © 2018 The Author Terms and Conditions

Figure I The Fate of Costly Plasmids. The evolutionary dynamics of a plasmid–bacterium association. The cost imposed by the plasmid is represented by a change in colour in the host bacterium after plasmid acquisition (blue, high fitness; white, low fitness). The table to the right shows the expected fate of the plasmid–bacterium association depending on the selection for plasmid-encoded genes, the ability of the plasmid to conjugate at a high rate (1high enough to survive as a genetic parasite in the population despite the plasmid-associated costs), and access to compensatory mutations. Trends in Microbiology 2018 26, 978-985DOI: (10.1016/j.tim.2018.06.007) Copyright © 2018 The Author Terms and Conditions

Figure I Methods for Determining Plasmid Fitness Effects. (A) Competition assays. Otherwise isogenic plasmid-carrying and plasmid-free clones are mixed and propagated in culture medium. From the initial and final population sizes of the clones, it is possible to calculate their relative fitness. (B) Growth curves. Bacterial growth is measured as the change in optical density at 600nm (OD600) over time in a pure bacterial culture. Information about clone fitness is provided by maximum growth rate (μmax), maximum OD600 (ODmax), the area under the growth curve (AUC), and the duration of the lag phase (lag). Comparing these parameters between plasmid-carrying and plasmid-free clones can help to define the fitness effects of the plasmid. (C) Murine model of gastrointestinal colonization as an example of an experimental system that can be used to measure plasmid fitness effects in vivo. Trends in Microbiology 2018 26, 978-985DOI: (10.1016/j.tim.2018.06.007) Copyright © 2018 The Author Terms and Conditions