title: Flow cytometry and real-time quantitative PCR as tools for assessing plasmid persistence.
abstract: The maintenance of a plasmid in the absence of selection for plasmid-borne genes is not guaranteed. However, plasmid persistence can evolve under selective conditions. Studying the molecular mechanisms behind the evolution of plasmid persistence is key to understanding how plasmids are maintained under nonselective conditions. Given the current crisis of rapid antibiotic resistance spread by multidrug resistance plasmids, this insight is of high medical relevance. The conventional method for monitoring plasmid persistence (i.e., the fraction of plasmid-containing cells in a population over time) is based on cultivation and involves differentiating colonies of plasmid-containing and plasmid-free cells on agar plates. However, this technique is time-consuming and does not easily lend itself to high-throughput applications. Here, we present flow cytometry (FCM) and real-time quantitative PCR (qPCR) as alternative tools for monitoring plasmid persistence. For this, we measured the persistence of a model plasmid, pB10::gfp, in three Pseudomonas hosts and in known mixtures of plasmid-containing and -free cells. We also compared three performance criteria: dynamic range, resolution, and variance. Although not without exceptions, both techniques generated estimates of overall plasmid loss rates that were rather similar to those generated by the conventional plate count (PC) method. They also were able to resolve differences in loss rates between artificial plasmid persistence assays. Finally, we briefly discuss the advantages and disadvantages for each technique and conclude that, overall, both FCM and real-time qPCR are suitable alternatives to cultivation-based methods for routine measurement of plasmid persistence, thereby opening avenues for high-throughput analyses.
authors: Department of Biological Sciences, University of Idaho, Moscow, Idaho, USA Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, Idaho, USA.
authors: Wesley
authors: W
authors: Loftie-Eaton
authors: Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, Idaho, USA Bioinformatics and Computational Biology Program, University of Idaho, Moscow, Idaho, USA Departments of Mathematics and Statistics, University of Idaho, Moscow, Idaho, USA.
authors: Allison
authors: A
authors: Tucker
authors: Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, Idaho, USA.
authors: Ann
authors: A
authors: Norton
authors: Department of Biological Sciences, University of Idaho, Moscow, Idaho, USA Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, Idaho, USA Bioinformatics and Computational Biology Program, University of Idaho, Moscow, Idaho, USA evatop@uidaho.edu.
authors: Eva M
authors: EM
authors: Top
mesh_terms: D005434:Flow Cytometry / Q000379:methods*; D017930:Genes, Reporter; D005827:Genetics, Microbial / Q000379:methods*; D049452:Green Fluorescent Proteins / Q000032:analysis; D010957:Plasmids / Q000032:analysis*; D011549:Pseudomonas / Q000235:genetics; D060888:Real-Time Polymerase Chain Reaction / Q000379:methods*; D013194:Staining and Labeling
chemical_list: D049452:Green Fluorescent Proteins