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Ceballos, S.

Publications and source records attributed to Ceballos, S..

2 recordsLinked to original sources

Rad51 determines pathway usage in post-replication repair

Stalled replication forks can be processed by several distinct mechanisms collectively called post-replication repair which includes homologous recombination, fork regression, and translesion DNA synthesis. However, the regulation of the usage between these pathways is not fully understood. The Rad51 protein plays a pivotal role in maintaining genomic stability through its roles in HR and in protecting stalled replication forks from degradation. We report the isolation of separation-of-function mutations in Saccharomyces cerevisiae Rad51 that retain their recombination function but display a defect in fork protection leading to a shift in post-replication repair pathway usage from HR to alternate pathways including mutagenic translesion synthesis. Rad51-E135D and Rad51-K305N show normal in vivo and in vitro recombination despite changes in their DNA binding profiles, in particular to dsDNA, with a resulting effect on their ATPase activities. The mutants lead to a defect in Rad51 recruitment to stalled forks in vivo as well as a defect in the protection of dsDNA from degradation by Dna2-Sgs1 and Exo1 in vitro. A high-resolution cryo-electron microscopy structure of the Rad51-ssDNA filament at 2.4 [A] resolution provides a structural basis for a mechanistic understanding of the mutant phenotypes. Together, the evidence suggests a model in which Rad51 binding to duplex DNA is critical to control pathway usage at stalled replication forks.

molecular biology↗

Characterizing stored red blood cells using ultra-high throughput holographic cytometry

Holographic cytometry is introduced as an ultra-high throughput implementation of quantitative phase image based on off-axis interferometry of cells flowing through parallel microfluidic channels. Here, it is applied for characterizing morphological changes of red blood cells during storage under regular blood bank condition. The approach allows high quality phase imaging of a large number of cells greatly extending our ability to study cellular phenotypes using individual cell images. Holographic cytology measurements show multiple physical traits of the cells, including optical volume and area, which are observed to consistently change over the storage time. In addition, the large volume of cell imaging data can serve as training data for machine learning algorithms. For the study here, logistic regression is used to classify the cells according to the storage time points. The results of the classifiers demonstrate the potential of holographic cytometry as a diagnostic tool.

bioengineering↗