Estimating plasmid conjugation rates: a new computational tool and a critical comparison of methods

Plasmids are important vectors for the spread of genes among diverse populations of bacteria. However, there is no standard method to determine the rate at which they spread horizontally via conjugation. Here, we compare commonly used methods on simulated and experimental data, and show that the resulting conjugation rate estimates often depend strongly on the time of measurement, the initial population densities, or the initial ratio of donor to recipient populations. Differences in growth rate, e.g. induced by sub-lethal antibiotic concentrations or temperature, can also significantly bias conjugation rate estimates. We derive a new end-point measure to estimate conjugation rates, which extends the well-known Simonsen method to include the effects of differences in population growth and conjugation rates from donors and transconjugants. We further derive analytical expressions for the parameter range in which these approximations remain valid. We present an easy to use R package and web interface which implement both new and previously existing methods to estimate conjugation rates. The result is a set of tools and guidelines for accurate and comparable measurement of plasmid conjugation rates. HighlightsO_LIWe present an R package and Shiny app to estimate conjugation rates from experimental data C_LIO_LIWe highlight the diversity of existing measures used to estimate conjugation rates C_LIO_LIWe show these measures are biased for populations with differing growth and conjugation rates from donors or transconjugants C_LIO_LIWe develop a new end-point measure which accounts for such differences in growth and conjugation rates C_LI