Related Experiment Video
Updated: May 13, 2026

Characterizing Microbiome Dynamics – Flow Cytometry Based Workflows from Pure Cultures to Natural Communities
Published on: July 12, 2018
Converting relative amplicon abundances to absolute abundances via flow cytometry: metagenomic validation and
Nathan L R Williams1, Qicheng Bei1, Yubin Raut2
1Department of Biological Sciences-Marine and Environmental Biology, University of Southern California, Los Angeles, CA 90026, United States.
Abstract:
With microbes critical for ocean ecological and biogeochemical processes, we need to understand their abundance and diversity distributions. While traditional amplicon sequencing provides only relative abundance data, and the strongly preferred absolute abundances can be determined from samples spiked with internal standards, few oceanographic studies with absolute abundances exist. However, many have flow cytometry (FCM) data that should allow us to retrospectively "anchor" the relative abundances into absolute abundances. We tested this hypothesis with data from the 29th Atlantic Meridional Transect (AMT29) cruise where we had FCM of Synechococcus and Prochlorococcus, amplicons corrected with internal standards, and absolute cell count estimates from single copy recA and radA metagenomics. Anchoring the AMT29 amplicon data with Synechococcus FCM (used because phycoerythrin in Synechococcus is reliably detected by FCM in surface waters) yielded results strongly correlated with amplicon data corrected with internal standards (Pearson's r = 0.94, slope = 0.73), FCM (r = 0.80, slope = 0.43), and recA-based genome counts (Pearson's r = 0.94, slope = 0.62). Seeing this method worked reasonably well, we then generated estimates of absolute rRNA gene abundances from the Global rRNA Universal Metabarcoding of Plankton (GRUMP) transects that had FCM data (Pacific ~65 N to ~40S). These FCM-anchored gene copy estimates also showed strong correlations to FCM data (i.e. anchor with Synechococcus and predict Prochlorococcus), with r values ranging from 0.48-0.86. While the results are clearly only reasonable estimates, we believe the approach has the potential to significantly enhance the value of amplicon data which have accompanying FCM data.
Related Concept Videos
Flow Cytometry
In...
Methods to Assess Microbial Populations

