Biology subjects

Kudlicki, A.

Publications and source records attributed to Kudlicki, A..

3 recordsLinked to original sources

bioRxiv2017

Integrated analysis of DSB patterns reveals precisely DSB formation mechanisms following replication fork collapse

DNA double-strand breaks (DSBs) can be detected by label-based sequencing or pulsed-field gel electrophoresis (PFGE). Sequencing yields population-average DSB frequencies genome-wide, while PFGE reveals percentages of broken chromosomes. We constructed a mathematical framework to combine advantages of both: high-resolution DSB locations and their population distribution. We also use sequencing read patterns to identify replication-induced DSBs and active replication origins. We describe changes in spatiotemporal replication program upon hydroxyurea-induced replication stress. We found that one-ended DSBs, resulting from collapsed replication forks, are population-representative, while majority of two-ended DSBs (79-100%) are not. To study replication fork collapse, we used strains lacking the checkpoint protein Mec1 and the endonuclease Mus81 and quantified that 19% and 13% of hydroxyurea-induced one-ended DSBs are Mec1-and Mus81-dependent, respectively. We also clarified that Mus81-induced one-ended DSBs are Mec1-dependent.

genomics↗

bioRxiv2017

Inferring proteome dynamics during yeast cell cycle using gene expression data

Protein levels are most relevant physiologically, but measuring them genome-wide remains a challenge. In contrast, mRNA levels are much easier and less expensive to measure globally. Therefore, RNA levels are typically used to infer the corresponding protein levels. The steady-state condition (assumption that protein levels remain constant) is typically used to calculate protein abundances, as it is mathematically very convenient, even though it is often clear that it is not satisfied for proteins of interest. Here, we propose a simple, yet very effective, method to estimate genome wide protein abundances, which does not require the assumption that protein levels remain constant, and thus allows us to also predict proteome dynamics. Instead, we assume that the system returns to the baseline at the end of experiments; such an assumption is satisfied in many time-course experiments and in all periodic conditions (e.g. cell cycle). The approach only requires availability of gene expression and protein half-life data. As proof-of-concept, we calculated the predicted proteome dynamics for the budding yeast proteome during the cell cycle, which can be conveniently browsed online. The approach was validated experimentally by verifying that the predicted protein concentration changes were consistent with measurements for all proteins tested. Additionally, if proteomic data are also available, our approach can be used to predict how half-lives change in response to posttranslational regulation. We illustrated this application of our method with de novo prediction of changes in the degradation rate of Clb2 in response to post-translational modifications. The predicted changes were consistent with earlier observations in the literature.

bioinformatics↗

bioRxiv2017

The High-resolution Timeline of Expression of Ribosomal Protein Genes in Yeast

The yeast ribosome is a complex molecular machine built from four rRNAs and over 70 r-proteins. Ribosome biogenesis involves ordered incorporation of ribosomal proteins, accompanied by and association and dissociation of other proteins specific to different stages of the process. By model-based analysis of temporal profiles of gene expression in a metabolically regulated system, we obtained an accurate, high-resolution estimation of the time of expression of genes coding for proteins involved in ribosome biogenesis. The ribosomal proteins are expressed in a sequence that spans approximately 25-minutes under metabolically regulated conditions. The genes coding for proteins incorporated into the mature ribosome are expressed significantly later than those that are not incorporated, but are otherwise involved in ribosome biogenesis, localization and assembly, rRNA processing and translational initiation. The relative expression time of proteins localized within specified neighborhood is significantly correlated with the distance to the centroid of the mature ribosome: protein localized closer to the center of mass of the entire complex tend to be expressed earlier than the protein localized further from the center. The timeline of gene expression also agrees with the known dependencies between recruitment of specific proteins into the mature ribosome. These findings are consistent in two independent experiments. We have further identified regulatory elements correlated with the time of regulation, including a possible dependence of expression time on the position of the RAP1 binding site within the 5UTR.

biochemistry↗