Using Metagenomics to Measure In-Situ Microbial Growth Rates

Growth rates are central to understanding microbial interactions and community dynamics. The Fuhrman Lab, which uses ‘omics data to seek a better understanding of microbial growth, interactions, and biogeographies has been evaluating a promising new approach to simultaneously determine the growth rates of many different kinds of microbes from the within-genome distributions of DNA extracted from in-situ (mixed) ocean populations.

Reporting by Helen Hill for CBIOMES

“An organism’s growth rate is fundamental to its ecology and necessary to conceptually or mathematically model microbial community composition and dynamics,” says Andrew Long, lead author of the lab’s recent ISME paper “Benchmarking microbial growth rate predictions from metagenomes.”

“Historically, growth rate estimates have used time-course incubations of mixed communities,” Long explains. “Unfortunately, although such studies provide valuable information on the bulk growth of mixed communities because they do not distinguish the contribution of individual phylogenetic groups from community-wide rates, such estimates cannot be readily applied to native uncultivated microbes in a taxon by taxon manner in their natural habitats.”

To address this the team (which also included CBIOMES members Shengwei Hou, J. Cesar Ignacio-Espinoza, and Jed Fuhrman), using seawater obtained as part of the monthly collection for the San Pedro Ocean Time-series (SPOT), carried out experiments based on two metagenomic growth estimators: codon usage bias (CUB) for maximum growth rates and “peak-to-trough ratio (PTR)”

Prefiltering and diluting samples to remove grazers and greatly reduce virus infection (so net growth would approximate gross growth) then sampling over two days for abundances and metagenomes the team was able to generate 101 metagenome-assembled genomes (MAGs). Tracking each MAG population by cell-abundance-normalized read recruitment, the authors found growth rates ranging from zero to almost six per day, including the first reported rates for several groups, and used these rates as benchmarks.

“PTR, calculated by three methods, rarely correlated to growth (r ~−0.26–0.08), except for rapidly growing γ-Proteobacteria (r ~0.63–0.92), while CUB correlated moderately well to observed maximum growth rates (r = 0.57),” says Long.

The take-home? The team says, based on their results, current PTR approaches poorly predict the actual growth of most marine bacterial populations, but that maximum growth rates can be approximated from genomic characteristics.

Andrew talked about this work in his April 2019 monthly e-meeting presentation.


Long, Andrew M., Shengwei HouJ. Cesar Ignacio-Espinoza, Jed A. Fuhrman (2020), Benchmarking microbial growth rate predictions from metagenomesISME Journal, doi: 10.1038/s41396-020-00773-1

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About the Researcher:

Andrew is now a postdoc in the Geaux Marine Viral Ecology Lab at Louisiana State University working on community ecology of marine viruses in oxygen minimum zones with Jennifer Brum.

Other Links

Microbial Growth, Interactions and Biogeographies from ‘Omics Data – Fuhrman Lab Research Page