Absolute quantification of microbial taxa is essential for microbial resource management in process- and drinking water

Amplicon sequencing of marker genes, such as the 16S rRNA gene, has become the golden standard for microbial community profiling.  As the abundances generated by this technology are semi-quantitative at best, and observed dynamic changes under different treatment regimens may not accurately reflect those of the actual taxon densities. As the microbial load of specific taxa is often more important than their relative abundance, this could have unforeseen implications in management strategies in e.g. health-related (pathogens or probiotic mixtures) or biotechnological (mixed culture fermentation, process water, drinking water) settings.


By combining an amplicon marker gene NGS approach (16S rRNA gene) with a robust single-cell enumeration technology (microbial flow cytometry) we were able to quantify absolute taxon abundances. We have established multiple cases where we could show that the interpretation of the distinct abundance profiles changes completely upon absolute quantification. In a longitudinal setup, a clear effect of operational cycles in a nuclear power plant secondary cooling water was observed. In a batch setup, clear necrotrophic regrowth could only be seen in given circumstances whereas with the NGS approach alone no clear patterns could be distinguished. Hence, we provide evidence that the enrichment of taxa (increase in relative abundance) does not necessarily relate to the outgrowth of taxa (increase in absolute abundance). Our results highlight that absolute abundances should be considered rather than relative abundances for an accurate biological interpretation of microbiome surveys for monitoring and ultimately, process control.

Authors

Frederiek - Maarten Kerckhof (1)
Ruben Props (1)
Ioanna Chatzigiannidou (1)
Peter Rubbens (2)
Willem Waegeman (2)
Pieter Monsieurs (3)
Frederiek Hammes (4)
Nico Boon (1)

Organisations

Center for Microbial Ecology and Technology (CMET)(1)
KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University (2)
Belgian Nuclear Research Centre (SCK•CEN) (3)
Department of Environmental Microbiology,Eawag—Swiss Federal Institute for Aquatic Science and Technology (4)

Presenting author

Frederiek - Maarten Kerckhof, Postdoctoral research fellow, Ghent University, Faculty of Bioscience Engineering, Center for Microbial Ecology and Technology (CMET)
frederiekmaarten.kerckhof@ugent.be
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