A Sampling Method Considering Body Size for Detecting the Associated Microbes in Plankton Populations: A Case Study, Using the Bloom-Forming Cyanobacteria, Microcystis

Accurately quantifying associated microbes is essential to understand the interactions between microplankton and their associated microbes. Most DNA-based methods, such as high-throughput sequencing, primarily assess the ratio of target objects to references in microplankton samples. However, simple random sampling (SRS) of individuals may lead to deviations in quantifying these ratios at the population level if these characteristics are associated with the reference content of individuals. This study considered group analysis, which involves detecting <i>k</i> groups with <i>n</i> individuals in each group, as an alternative approach and used simulated data based on the detection of <i>Microcystis</i> populations to evaluate the accuracy of different sampling plans. Our results indicate that increasing the number of individuals in each group could reduce sampling bias and improve the accuracy of comparisons between populations. Group analysis could also minimize the impact of the detection limit. This study demonstrated that, when detection methods only provide the ratio of target objects to references, group analysis is more appropriate than SRS for characterizing microplankton populations. Group analysis can be used not only for detecting associated microbes but also for identifying ingested organisms or the biochemical composition of microplankton. Our results also demonstrate how in situ individual-level studies support ecological investigations.