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Summary: Current super-resolution microscopy (SRM) methods suffer from an intrinsic complexity that might curtail their routine use in cell biology. We describe here random illumination microscopy (RIM) for live-cell imaging at super-resolutions matching that of 3D structured illumination microscopy, in a robust fashion. Based on speckled illumination and statistical image reconstruction, easy to implement and user-friendly, RIM is unaffected by optical aberrations on the excitation side, linear to brightness, and compatible with multicolor live-cell imaging over extended periods of time. We illustrate the potential of RIM on diverse biological applications, from the mobility of proliferating cell nuclear antigen (PCNA) in U2OS cells and kinetochore dynamics in mitotic S. pombe cells to the 3D motion of myosin minifilaments deep inside Drosophila tissues. RIM's inherent simplicity and extended biological applicability, particularly for imaging at increased depths, could help make SRM accessible to biology laboratories. Motivation: Super-resolution optical microscopy (SRM) has been instrumental to rapid progress in cell biology. Many SRM variants are now available with different compromises between phototoxicity, spatiotemporal resolutions, and sensitivity to aberrations. Yet, established SRM techniques, even implemented as expensive turn-key systems, require expert know-how at the instrumentation or image reconstruction levels to operate at the best of their capabilities. The present challenge is to develop a simple, easy to use, and low-cost SRM technique that would combine artifact-free super-resolution, robustness to aberration, low toxicity, and good temporal resolution for routine functional imaging of live cells within normal or pathological tissues.

Translocations are dramatic genomic rearrangements due to aberrant rejoining of distant DNA ends that can trigger cancer onset and progression. Translocations frequently occur in genes, yet the mechanisms underlying their formation remain poorly understood. One potential mechanism involves DNA Double Strand Break mobility and juxtaposition (i.e. clustering), an event that has been intensively debated over the past decade. Using Capture Hi-C, we recently found that DSBs do in fact cluster in human nuclei but only when induced in transcriptionally active genes. Notably, we found that clustering of damaged genes is regulated by cell cycle progression and coincides with damage persistency. Here, we discuss the mechanisms that could sustain clustering and speculate on the functional consequences of this seemingly double edge sword mechanism that may well stand at the heart of translocation biogenesis.

DNA replication fork stalling poses a major threat to genome stability. This is counteracted in part by the intra-S phase checkpoint, which stabilizes arrested replication machinery, prevents cell-cycle progression and promotes DNA repair. The checkpoint kinase Mec1/ATR and RecQ helicase Sgs1/BLM contribute synergistically to fork maintenance on hydroxyurea (HU). Both enzymes interact with replication protein A (RPA). We identified and deleted the major interaction sites on Sgs1 for Rpa70, generating a mutant called sgs1-r1. In contrast to a helicase-dead mutant of Sgs1, sgs1-r1 did not significantly reduce recovery of DNA polymerase α at HU-arrested replication forks. However, the Sgs1 R1 domain is a target of Mec1 kinase, deletion of which compromises Rad53 activation on HU. Full activation of Rad53 is achieved through phosphorylation of the Sgs1 R1 domain by Mec1, which promotes Sgs1 binding to the FHA1 domain of Rad53 with high affinity. We propose that the recruitment of Rad53 by phosphorylated Sgs1 promotes the replication checkpoint response on HU. Loss of the R1 domain increases lethality selectively in cells lacking Mus81, Slx4, Slx5 or Slx8.

Rad54’s ATPase activity does not affect accumulation of homologous recombination proteins in repair foci, but influences its dissociation and that of Rad51., Rad54, a member of the SWI/SNF protein family of DNA-dependent ATPases, repairs DNA double-strand breaks (DSBs) through homologous recombination. Here we demonstrate that Rad54 is required for the timely accumulation of the homologous recombination proteins Rad51 and Brca2 at DSBs. Because replication protein A and Nbs1 accumulation is not affected by Rad54 depletion, Rad54 is downstream of DSB resection. Rad54-mediated Rad51 accumulation does not require Rad54’s ATPase activity. Thus, our experiments demonstrate that SWI/SNF proteins may have functions independent of their ATPase activity. However, quantitative real-time analysis of Rad54 focus formation indicates that Rad54’s ATPase activity is required for the disassociation of Rad54 from DNA and Rad54 turnover at DSBs. Although the non–DNA-bound fraction of Rad54 reversibly interacts with a focus, independent of its ATPase status, the DNA-bound fraction is immobilized in the absence of ATP hydrolysis by Rad54. Finally, we show that ATP hydrolysis by Rad54 is required for the redistribution of DSB repair sites within the nucleus.

Mec1-Ddc2 (ATR-ATRIP) controls the DNA damage checkpoint and shows differential cell-cycle regulation in yeast. To find regulators of Mec1-Ddc2, we exploited a mec1 mutant that retains catalytic activity in G2 and recruitment to stalled replication forks, but which is compromised for the intra-S phase checkpoint. Two screens, one for spontaneous survivors and an E-MAP screen for synthetic growth effects, identified loss of PP4 phosphatase, pph3Δ and psy2Δ, as the strongest suppressors of mec1-100 lethality on HU. Restored Rad53 phosphorylation accounts for part, but not all, of the pph3Δ-mediated survival. Phosphoproteomic analysis confirmed that 94% of the mec1-100-compromised targets on HU are PP4 regulated, including a phosphoacceptor site within Mec1 itself, mutation of which confers damage sensitivity. Physical interaction between Pph3 and Mec1, mediated by cofactors Psy2 and Ddc2, is shown biochemically and through FRET in subnuclear repair foci. This establishes a physical and functional Mec1-PP4 unit for regulating the checkpoint response.

To protect the genome, cells have evolved a diverse set of pathways designed to sense, signal, and repair multiple types of DNA damage. To assess the degree of coordination and crosstalk among these pathways, we systematically mapped changes in the cell's genetic network across a panel of different DNA-damaging agents, resulting in ~1,800,000 differential measurements. Each agent was associated with a distinct interaction pattern, which, unlike single-mutant phenotypes or gene expression data, has high statistical power to pinpoint the specific repair mechanisms at work. The agent-specific networks revealed roles for the histone acetyltranferase Rtt109 in the mutagenic bypass of DNA lesions and the neddylation machinery in cell-cycle regulation and genome stability, while the network induced by multiple agents implicates Irc21, an uncharacterized protein, in checkpoint control and DNA repair. Our multiconditional genetic interaction map provides a unique resource that identifies agent-specific and general DNA damage response pathways.

Background Epistatic Miniarray Profiling(E-MAP) quantifies the net effect on growth rate of disrupting pairs of genes, often producing phenotypes that may be more (negative epistasis) or less (positive epistasis) severe than the phenotype predicted based on single gene disruptions. Epistatic interactions are important for understanding cell biology because they define relationships between individual genes, and between sets of genes involved in biochemical pathways and protein complexes. Each E-MAP screen quantifies the interactions between a logically selected subset of genes (e.g. genes whose products share a common function). Interactions that occur between genes involved in different cellular processes are not as frequently measured, yet these interactions are important for providing an overview of cellular organization. Results We introduce a method for combining overlapping E-MAP screens and inferring new interactions between them. We use this method to infer with high confidence 2,240 new strongly epistatic interactions and 34,469 weakly epistatic or neutral interactions. We show that accuracy of the predicted interactions approaches that of replicate experiments and that, like measured interactions, they are enriched for features such as shared biochemical pathways and knockout phenotypes. We constructed an expanded epistasis map for yeast cell protein complexes and show that our new interactions increase the evidence for previously proposed inter-complex connections, and predict many new links. We validated a number of these in the laboratory, including new interactions linking the SWR-C chromatin modifying complex and the nuclear transport apparatus. Conclusion Overall, our data support a modular model of yeast cell protein network organization and show how prediction methods can considerably extend the information that can be extracted from overlapping E-MAP screens.

DNA Damage Pathways Revealed Despite the dynamic nature of cellular responses, the genetic networks that govern these responses have been mapped primarily as static snapshots. Bandyopadhyay et al. (p. 1385 ; see the Perspective by Friedman and Schuldiner ) report a comparison of large genetic interactomes measured among all yeast kinases, phosphatases, and transcription factors, as the cell responded to DNA damage. The interactomes revealed were highly dynamic structures that changed dramatically with changing conditions. These dynamic interactions reveal genetic relationships that can be more effective than classical “static” interactions (for example, synthetic lethals and epistasis maps) in identifying pathways of interest.

This work demonstrates how gene association studies can be analyzed to map a global landscape of genetic interactions among protein complexes and pathways. Despite the immense potential of gene association studies, they have been challenging to analyze because most traits are complex, involving the combined effect of mutations at many different genes. Due to lack of statistical power, only the strongest single markers are typically identified. Here, we present an integrative approach that greatly increases power through marker clustering and projection of marker interactions within and across protein complexes. Applied to a recent gene association study in yeast, this approach identifies 2,023 genetic interactions which map to 208 functional interactions among protein complexes. We show that such interactions are analogous to interactions derived through reverse genetic screens and that they provide coverage in areas not yet tested by reverse genetic analysis. This work has the potential to transform gene association studies, by elevating the analysis from the level of individual markers to global maps of genetic interactions. As proof of principle, we use synthetic genetic screens to confirm numerous novel genetic interactions for the INO80 chromatin remodeling complex., Author Summary One of the most important problems in biology and medicine is to identify the genetic mutations that affect human traits such as blood pressure, longevity, and onset of disease. Currently, large scientific teams are examining the genomes of thousands of people in an attempt to find mutations present only in individuals with certain traits. Until now, mutations have been largely examined in isolation, without regard to how they work together inside the cell. However, large pathway maps are now available which describe in detail the network of genes and proteins that underlies cell function. Here we show how to take advantage of these pathway maps to better identify relevant mutations and to show how these mutations work mechanistically. This basic approach of combining genetic information with known maps of the cell will have wide-ranging applications in understanding and treating disease.