Single molecule dynamics at a bacterial replication fork after nutritional downshift

Abstract

Replication forks must respond to changes in nutrient conditions, especially in bacterial cells. By investigating the single molecule dynamics of replicative helicase DnaC, DNA primase DnaG, and of lagging strand polymerase DnaE in the model bacterium Bacillus subtilis in response to transient replication blocks due to DNA damage, to inhibition of the replicative polymerase, or to downshift of serine availability, we show that proteins react differentially to the stress conditions. DnaG appears to be recruited to the forks by a diffusion and capture mechanism, becomes more statically associated after arrest of polymerase PolC, but binds much less often after fork blocks due to DNA damage or to nutritional downshift. These results indicate that binding of the alarmone ppGpp due to the stringent response prevents DnaG from binding to forks rather than blocking bound primase. Dissimilar behaviour of DnaG and of DnaE suggest that both proteins are recruited independently to the forks, rather than jointly. Turnover of all three proteins was increased during replication block after nutritional downshift, different from the situation due to DNA damage or polymerase inhibition, showing high plasticity of forks in response to different stress conditions. Forks persisted during all stress conditions, apparently ensuring rapid return to replication extension.

The CTPase activity of ParB acts as a timing mechanism to control the dynamics and function of prokaryotic DNA partition complexes

“…Spots were merged into tracks via the Simple LAP Tracker of TrackMate, with a maximum linking distance of 300 nm, no frame gaps allowed, and a minimum track length of 5, yielding a minimum n of total tracks per sample of 1800. To identify differences in protein mobility and in the proportions of mobile and static molecules between strains, the resulting tracks were subjected to mean-squared-displacement (MSD) and Gaussian-mixture-model (GMM) analysis in SMTracker 2.0 (Rosch et al, 2018) as described previously (Hernandez-Tamayo et al, 2021; Rosch et al, 2018). The average MSD was calculated for five separate time points per strain (τ = 30, 60, 90, 120 and 150 ms), followed by fitting of the data to a linear equation.…”