Rev7 and 53BP1/Crb2 prevent RecQ helicase-dependent hyper-resection of DNA double-strand breaks

  1. Bryan A Leland
  2. Angela C Chen
  3. Amy Y Zhao
  4. Robert C Wharton
  5. Megan C King  Is a corresponding author
  1. Yale School of Medicine, United States

Abstract

Poly(ADP ribose) polymerase inhibitors (PARPi) target cancer cells deficient in homology-directed repair of DNA double-strand breaks (DSBs). In preclinical models, PARPi resistance is tied to altered nucleolytic processing (resection) at the 5' ends of a DSB. For example, loss of 53BP1 or Rev7/MAD2L2/FANCV derepresses resection to drive PARPi resistance, although the mechanisms are poorly understood. Long-range resection can be catalyzed by two machineries: the exonuclease Exo1, or the combination of a RecQ helicase and Dna2. Here, we develop a single cell microscopy assay that allows the distinct phases and machineries of resection to be interrogated simultaneously in living S. pombe cells. Using this assay, we find that the 53BP1 orthologue and Rev7 specifically repress long-range resection through the RecQ helicase-dependent pathway, thereby preventing hyper-resection. These results suggest that 'rewiring' of BRCA1-deficient cells to employ an Exo1-independent hyper-resection pathway is a driver of PARPi resistance.

Data availability

Raw analysis for all individual cells included in plots, complete code, and other supporting materials are publicly available on GitHub github.com/lelandbr/Leland_King_2018_eLife_Rev7_EndResection. The raw movies for representative cells presented in the figures have been uploaded to Dryad [doi:10.5061/dryad.1db5500] . The full raw datasets (all cells, all fields, all movies) are available on request from the corresponding author (megan.king@yale.edu) as they are TBs in size.

The following data sets were generated

Article and author information

Author details

  1. Bryan A Leland

    Department of Cell Biology, Yale School of Medicine, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Angela C Chen

    Department of Cell Biology, Yale School of Medicine, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Amy Y Zhao

    Department of Cell Biology, Yale School of Medicine, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Robert C Wharton

    Department of Cell Biology, Yale School of Medicine, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Megan C King

    Department of Cell Biology, Yale School of Medicine, New Haven, United States
    For correspondence
    megan.king@yale.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1688-2226

Funding

National Science Foundation (DGE-1122492)

  • Bryan A Leland

National Institutes of Health (DP2OD008429-01)

  • Megan C King

Searle Scholars Program (Scholar Award)

  • Megan C King

National Institutes of Health (T32-HD-007180-40)

  • Bryan A Leland

The Gruber Foundation (Gruber Science Fellowship)

  • Bryan A Leland

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2018, Leland et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,843
    views
  • 349
    downloads
  • 27
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Bryan A Leland
  2. Angela C Chen
  3. Amy Y Zhao
  4. Robert C Wharton
  5. Megan C King
(2018)
Rev7 and 53BP1/Crb2 prevent RecQ helicase-dependent hyper-resection of DNA double-strand breaks
eLife 7:e33402.
https://doi.org/10.7554/eLife.33402

Share this article

https://doi.org/10.7554/eLife.33402

Further reading

    1. Cell Biology
    Dharmendra Kumar Nath, Subash Dhakal, Youngseok Lee
    Research Advance

    Understanding how the brain controls nutrient storage is pivotal. Transient receptor potential (TRP) channels are conserved from insects to humans. They serve in detecting environmental shifts and in acting as internal sensors. Previously, we demonstrated the role of TRPγ in nutrient-sensing behavior (Dhakal et al., 2022). Here, we found that a TRPγ mutant exhibited in Drosophila melanogaster is required for maintaining normal lipid and protein levels. In animals, lipogenesis and lipolysis control lipid levels in response to food availability. Lipids are mostly stored as triacylglycerol in the fat bodies (FBs) of D. melanogaster. Interestingly, trpγ deficient mutants exhibited elevated TAG levels and our genetic data indicated that Dh44 neurons are indispensable for normal lipid storage but not protein storage. The trpγ mutants also exhibited reduced starvation resistance, which was attributed to insufficient lipolysis in the FBs. This could be mitigated by administering lipase or metformin orally, indicating a potential treatment pathway. Gene expression analysis indicated that trpγ knockout downregulated brummer, a key lipolytic gene, resulting in chronic lipolytic deficits in the gut and other fat tissues. The study also highlighted the role of specific proteins, including neuropeptide DH44 and its receptor DH44R2 in lipid regulation. Our findings provide insight into the broader question of how the brain and gut regulate nutrient storage.

    1. Cell Biology
    2. Immunology and Inflammation
    Mykhailo Vladymyrov, Luca Marchetti ... Britta Engelhardt
    Tools and Resources

    The endothelial blood-brain barrier (BBB) strictly controls immune cell trafficking into the central nervous system (CNS). In neuroinflammatory diseases such as multiple sclerosis, this tight control is, however, disturbed, leading to immune cell infiltration into the CNS. The development of in vitro models of the BBB combined with microfluidic devices has advanced our understanding of the cellular and molecular mechanisms mediating the multistep T-cell extravasation across the BBB. A major bottleneck of these in vitro studies is the absence of a robust and automated pipeline suitable for analyzing and quantifying the sequential interaction steps of different immune cell subsets with the BBB under physiological flow in vitro. Here, we present the under-flow migration tracker (UFMTrack) framework for studying immune cell interactions with endothelial monolayers under physiological flow. We then showcase a pipeline built based on it to study the entire multistep extravasation cascade of immune cells across brain microvascular endothelial cells under physiological flow in vitro. UFMTrack achieves 90% track reconstruction efficiency and allows for scaling due to the reduction of the analysis cost and by eliminating experimenter bias. This allowed for an in-depth analysis of all behavioral regimes involved in the multistep immune cell extravasation cascade. The study summarizes how UFMTrack can be employed to delineate the interactions of CD4+ and CD8+ T cells with the BBB under physiological flow. We also demonstrate its applicability to the other BBB models, showcasing broader applicability of the developed framework to a range of immune cell-endothelial monolayer interaction studies. The UFMTrack framework along with the generated datasets is publicly available in the corresponding repositories.