Abstract

We developed Growth Rate InDex (GRiD) for estimating in situ growth rates of ultra-low coverage (> 0.2×) and de novo-assembled metagenomes. Applying GRiD to human and environmental metagenomic datasets to demonstrate its versatility, we uncovered new associations with previously uncharacterized bacteria whose growth rates were associated with several disease characteristics or environmental interactions. In addition, with GRiD-MG (metagenomic), a high-throughput implementation of GRiD, we estimated growth dynamics of 1756 bacteria species from a healthy skin metagenomic dataset and identified a new Staphylococcus-Corynebacterium antagonism likely mediated by antimicrobial production in the skin. GRiD-MG significantly increases the ability to extract growth rate inferences from complex metagenomic data with minimal input from the user.