Cell death and population heterogeneity affect DNA-replication-based estimates of bacterial growth

Inferring bacterial growth rates is fundamental to understanding microbial interactions and community dynamics, but remains difficult in natural settings where timepoints are limited or organisms are unculturable. A widely used method is the peak-to-trough ratio (PTR), which leverages metagenomic sequencing to estimate DNA replication activity by comparing coverage at the replication origin and terminus. PTR has been shown to correlate well with growth in uniform, idealized conditions, but in natural settings, populations experience fluctuating stress and mortality, and variation within the population. To explore how PTR performs in these settings, we developed a stochastic, cell-based model that explicitly tracks DNA replication and cell death. We find that, as expected, PTR and growth rate are tightly correlated in idealized conditions, but decouple when the population experiences time-dependent death or when the death rate varies within the population. We validated these predictions experimentally by exposing E. coli to osmotic shock or antibiotics, and measuring growth (via spot plating) and PTR (via qPCR). Consistent with the predictions from our model, PTR correlated strongly with growth in standard rich media, but failed under stress. These results provide a mechanistic framework for interpreting when PTR should and should not be used as a proxy for bacterial growth.