Assessing cell cycle-based methods of measuring Prochlorococcus division rates using an individual-based model

Abstract

The picocyanobacterium Prochlorococcus is a major contributor to primary production in tropical and temperate oceans. Division rates (μpop) of Prochlorococcus populations can be calculated by following their partially synchronized cell cycles, but one major source of error in these calculations is the estimation of the duration of the S and G2 phases, TSG2. Here we have used data generated by an individual-based model (IBM) of the Prochlorococcus cell cycle to analyze an array of estimation methods and range of sample intervals to determine the best way to calculate μpop from time course data. Among the traditional methods using the cell cycle approach, areal median gave the best estimate of μpop; optimizing the IBM itself gave the best estimate overall. A size-based matrix model also gave reasonable results, except at ultradian growth rates. These methods were applied to a time series in the Sargasso Sea to measure Prochlorococcus μpop in situ. The IBM was an effective test bed to investigate division rate estimates and provide recommendations for applying these estimates to field populations.