Improved functional overview of protein complexes using inferred epistatic relationships

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

ATP-dependent and independent functions of Rad54 in genome maintenance

Rad54’s ATPase activity does not affect accumulation of homologous recombination proteins in repair foci, but influences its dissociation and that of Rad51

Genome-Wide Association Data Reveal a Global Map of Genetic Interactions among Protein Complexes

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

Rewiring of genetic networks in response to DNA damage

Although cellular behaviors are dynamic, the networks that govern these behaviors have been mapped primarily as static snapshots. Using an approach called differential epistasis mapping, we have discovered widespread changes in genetic interaction among yeast kinases, phosphatases, and transcription factors as the cell responds to DNA damage. Differential interactions uncover many gene functions that go undetected in static conditions. They are very effective at identifying DNA repair pathways, highlighting new damage-dependent roles for the Slt2 kinase, Pph3 phosphatase, and histone variant Htz1. The data also reveal that protein complexes are generally stable in response to perturbation, but the functional relations between these complexes are substantially reorganized. Differential networks chart a new type of genetic landscape that is invaluable for mapping cellular responses to stimuli

Super-resolved live-cell imaging using Random Illumination Microscopy

International audienceSuper-resolution fluorescence microscopy has been instrumental to progress in biology. Yet, the photo-induced toxicity, the loss of resolution into scattering samples or the complexity of the experimental setups curtail its general use for functional cell imaging. Here, we describe a new technology for tissue imaging reaching a 114nm/8Hz resolution at 30 µm depth. Random Illumination Microscopy (RIM) consists in shining the sample with uncontrolled speckles and extracting a high-fidelity super-resolved image from the variance of the data using a reconstruction scheme accounting for the spatial correlation of the illuminations. Super-resolution unaffected by optical aberrations, undetectable phototoxicity, fast image acquisition rate and ease of use, altogether, make RIM ideally suited for functional live cell imaging in situ . RIM ability to image molecular and cellular processes in three dimensions and at high resolution is demonstrated in a wide range of biological situations such as the motion of Myosin II minifilaments in Drosophila

Dissection of DNA Damage Responses Using Multiconditional Genetic Interaction Maps

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

An N-terminal acidic region of Sgs1 interacts with Rpa70 and recruits Rad53 kinase to stalled forks

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