Search

Innovative methods to retrieve proteins associated with actively replicating DNA have provided a glimpse into the molecular dynamics of replication fork stalling. We report that a combination of density-based replisome enrichment by isolating proteins on nascent DNA (iPOND2) and label-free quantitative mass spectrometry (iPOND2-DRIPPER) substantially increases both replication factor yields and the dynamic range of protein quantification. Replication protein abundance in retrieved nascent DNA is elevated up to 300-fold over post-replicative controls, and recruitment of replication stress factors upon fork stalling is observed at similar levels. The increased sensitivity of iPOND2-DRIPPER permits direct measurement of ubiquitination events without intervening retrieval of diglycine tryptic fragments of ubiquitin. Using this approach, we find that stalled replisomes stimulate the recruitment of a diverse cohort of DNA repair factors, including those associated with poly-K63-ubiquitination. Finally, we uncover the temporally controlled association of stalled replisomes with nuclear pore complex components and nuclear cytoskeleton networks.

Researchers are increasingly turning to label-free MS1 intensity-based quantification strategies within HPLC–ESI–MS/MS workflows to reveal biological variation at the molecule level. Unfortunately, HPLC–ESI–MS/MS workflows using these strategies produce results with poor repeatability and reproducibility, primarily due to systematic bias and complex variability. While current global normalization strategies can mitigate systematic bias, they fail when faced with complex variability stemming from transient stochastic events during HPLC–ESI–MS/MS analysis. To address these problems, we developed a novel local normalization method, proximity-based intensity normalization (PIN), based on the analysis of compositional data. We evaluated PIN against common normalization strategies. PIN outperforms them in dramatically reducing variance and in identifying 20% more proteins with statistically significant abundance differences that other strategies missed. Our results show the PIN enables the discovery of statistically significant biological variation that otherwise is falsely reported or missed.