Adam P. Rosebrock

A Cell Cycle-Dependent Regulatory Circuit Composed of 53BP1-RIF1 and BRCA1-CtIP Controls DNA Repair Pathway Choice

DNA double-strand break (DSB) repair pathway choice is governed by the opposing activities of 53BP1 and BRCA1. 53BP1 stimulates nonhomologous end joining (NHEJ), whereas BRCA1 promotes end resection and homologous recombination (HR). Here we show that 53BP1 is an inhibitor of BRCA1 accumulation at DSB sites, specifically in the G1 phase of the cell cycle. ATM-dependent phosphorylation of 53BP1 physically recruits RIF1 to DSB sites, and we identify RIF1 as the critical effector of 53BP1 during DSB repair. Remarkably, RIF1 accumulation at DSB sites is strongly antagonized by BRCA1 and its interacting partner CtIP. Lastly, we show that depletion of RIF1 is able to restore end resection and RAD51 loading in BRCA1-depleted cells. This work therefore identifies a cell cycle-regulated circuit, underpinned by RIF1 and BRCA1, that governs DSB repair pathway choice to ensure that NHEJ dominates in G1 and HR is favored from S phase onward.

A global genetic interaction network maps a wiring diagram of cellular function

INTRODUCTION Genetic interactions occur when mutations in two or more genes combine to generate an unexpected phenotype. An extreme negative or synthetic lethal genetic interaction occurs when two mutations, neither lethal individually, combine to cause cell death. Conversely, positive genetic interactions occur when two mutations produce a phenotype that is less severe than expected. Genetic interactions identify functional relationships between genes and can be harnessed for biological discovery and therapeutic target identification. They may also explain a considerable component of the undiscovered genetics associated with human diseases. Here, we describe construction and analysis of a comprehensive genetic interaction network for a eukaryotic cell. RATIONALE Genome sequencing projects are providing an unprecedented view of genetic variation. However, our ability to interpret genetic information to predict inherited phenotypes remains limited, in large part due to the extensive buffering of genomes, making most individual eukaryotic genes dispensable for life. To explore the extent to which genetic interactions reveal cellular function and contribute to complex phenotypes, and to discover the general principles of genetic networks, we used automated yeast genetics to construct a global genetic interaction network. RESULTS We tested most of the ~6000 genes in the yeast Saccharomyces cerevisiae for all possible pairwise genetic interactions, identifying nearly 1 million interactions, including ~550,000 negative and ~350,000 positive interactions, spanning ~90% of all yeast genes. Essential genes were network hubs, displaying five times as many interactions as nonessential genes. The set of genetic interactions or the genetic interaction profile for a gene provides a quantitative measure of function, and a global network based on genetic interaction profile similarity revealed a hierarchy of modules reflecting the functional architecture of a cell. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections associated with defects in cell cycle progression or cellular proteostasis. Importantly, the global network illustrates how coherent sets of negative or positive genetic interactions connect protein complex and pathways to map a functional wiring diagram of the cell. CONCLUSION A global genetic interaction network highlights the functional organization of a cell and provides a resource for predicting gene and pathway function. This network emphasizes the prevalence of genetic interactions and their potential to compound phenotypes associated with single mutations. Negative genetic interactions tend to connect functionally related genes and thus may be predicted using alternative functional information. Although less functionally informative, positive interactions may provide insights into general mechanisms of genetic suppression or resiliency. We anticipate that the ordered topology of the global genetic network, in which genetic interactions connect coherently within and between protein complexes and pathways, may be exploited to decipher genotype-to-phenotype relationships. A global network of genetic interaction profile similarities. (Left) Genes with similar genetic interaction profiles are connected in a global network, such that genes exhibiting more similar profiles are located closer to each other, whereas genes with less similar profiles are positioned farther apart. (Right) Spatial analysis of functional enrichment was used to identify and color network regions enriched for similar Gene Ontology bioprocess terms. We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.

Interspecies Systems Biology Uncovers Metabolites Affecting C. elegans Gene Expression and Life History Traits

Diet greatly influences gene expression and physiology. In mammals, elucidating the effects and mechanisms of individual nutrients is challenging due to the complexity of both the animal and its diet. Here, we used an interspecies systems biology approach with Caenorhabditis elegans and two of its bacterial diets, Escherichia coli and Comamonas aquatica, to identify metabolites that affect the animals gene expression and physiology. We identify vitamin B12 as the major dilutable metabolite provided by Comamonas aq. that regulates gene expression, accelerates development, and reduces fertility but does not affect lifespan. We find that vitamin B12 has a dual role in the animal: it affects development and fertility via the methionine/S-Adenosylmethionine (SAM) cycle and breaks down the short-chain fatty acid propionic acid, preventing its toxic buildup. Our interspecies systems biology approach provides a paradigm for understanding complex interactions between diet and physiology.

Conserved Regulators of Nucleolar Size Revealed by Global Phenotypic Analyses

Loss-of-function analyses in yeast and flies identify molecular complexes that regulate ribosomal DNA transcription. Regulating Nucleolar Size The higher proliferation rate of cancer cells requires an increased rate of protein synthesis. Thus, cancer cells often show increased rates of ribosomal DNA (rDNA) transcription and have more ribosomes and larger nucleoli, which are nuclear structures that function in ribosome biogenesis. Neumüller et al. identified genes in yeast that, when ablated, resulted in smaller or larger nucleoli. A similar analysis in Drosophila enabled the identification of evolutionarily conserved molecular complexes that increase or decrease nucleolar size when the complex constituents were targeted by RNA interference. Understanding how cells regulate rDNA transcription could provide new therapeutic avenues for interfering with the unrestricted growth that occurs in cancer. Regulation of cell growth is a fundamental process in development and disease that integrates a vast array of extra- and intracellular information. A central player in this process is RNA polymerase I (Pol I), which transcribes ribosomal RNA (rRNA) genes in the nucleolus. Rapidly growing cancer cells are characterized by increased Pol I–mediated transcription and, consequently, nucleolar hypertrophy. To map the genetic network underlying the regulation of nucleolar size and of Pol I–mediated transcription, we performed comparative, genome-wide loss-of-function analyses of nucleolar size in Saccharomyces cerevisiae and Drosophila melanogaster coupled with mass spectrometry–based analyses of the ribosomal DNA (rDNA) promoter. With this approach, we identified a set of conserved and nonconserved molecular complexes that control nucleolar size. Furthermore, we characterized a direct role of the histone information regulator (HIR) complex in repressing rRNA transcription in yeast. Our study provides a full-genome, cross-species analysis of a nuclear subcompartment and shows that this approach can identify conserved molecular modules.

Heritability and genetic basis of protein level variation in an outbred population

The genetic basis of heritable traits has been studied for decades. Although recent mapping efforts have elucidated genetic determinants of transcript levels, mapping of protein abundance has lagged. Here, we analyze levels of 4084 GFP-tagged yeast proteins in the progeny of a cross between a laboratory and a wild strain using flow cytometry and high-content microscopy. The genotype of trans variants contributed little to protein level variation between individual cells but explained >50% of the variance in the populations average protein abundance for half of the GFP fusions tested. To map trans-acting factors responsible, we performed flow sorting and bulk segregant analysis of 25 proteins, finding a median of five protein quantitative trait loci (pQTLs) per GFP fusion. Further, we find that cis-acting variants predominate; the genotype of a gene and its surrounding region had a large effect on protein level six times more frequently than the rest of the genome combined. We present evidence for both shared and independent genetic control of transcript and protein abundance: More than half of the expression QTLs (eQTLs) contribute to changes in protein levels of regulated genes, but several pQTLs do not affect their cognate transcript levels. Allele replacements of genes known to underlie trans eQTL hotspots confirmed the correlation of effects on mRNA and protein levels. This study represents the first genome-scale measurement of genetic contribution to protein levels in single cells and populations, identifies more than a hundred trans pQTLs, and validates the propagation of effects associated with transcript variation to protein abundance.

Drosophila larvae synthesize the putative oncometabolite L-2-hydroxyglutarate during normal developmental growth

Significance Oncometabolites are small molecules that promote tumor formation and growth. L-2-hydroxyglutarate (L-2HG) is a putative oncometabolite that is associated with gliomas and renal cell carcinomas, as well as a severe neurometabolic disorder known as L-2-hydroxyglutaric aciduria. However, despite that L-2HG is commonly considered a metabolic waste product, this compound was recently discovered to control immune cell fate, thereby demonstrating that it has endogenous functions in healthy animal cells. Here, we find that the fruit fly, Drosophila melanogaster, also synthesizes high concentrations of L-2HG during normal larval growth. Our discovery establishes the fly as a genetic model for studying this putative oncometabolite in healthy animal tissues. L-2-hydroxyglutarate (L-2HG) has emerged as a putative oncometabolite that is capable of inhibiting enzymes involved in metabolism, chromatin modification, and cell differentiation. However, despite the ability of L-2HG to interfere with a broad range of cellular processes, this molecule is often characterized as a metabolic waste product. Here, we demonstrate that Drosophila larvae use the metabolic conditions established by aerobic glycolysis to both synthesize and accumulate high concentrations of L-2HG during normal developmental growth. A majority of the larval L-2HG pool is derived from glucose and dependent on the Drosophila estrogen-related receptor (dERR), which promotes L-2HG synthesis by up-regulating expression of the Drosophila homolog of lactate dehydrogenase (dLdh). We also show that dLDH is both necessary and sufficient for directly synthesizing L-2HG and the Drosophila homolog of L-2-hydroxyglutarate dehydrogenase (dL2HGDH), which encodes the enzyme that breaks down L-2HG, is required for stage-specific degradation of the L-2HG pool. In addition, dLDH also indirectly promotes L-2HG accumulation via synthesis of lactate, which activates a metabolic feed-forward mechanism that inhibits dL2HGDH activity and stabilizes L-2HG levels. Finally, we use a genetic approach to demonstrate that dLDH and L-2HG influence position effect variegation and DNA methylation, suggesting that this compound serves to coordinate glycolytic flux with epigenetic modifications. Overall, our studies demonstrate that growing animal tissues synthesize L-2HG in a controlled manner, reveal a mechanism that coordinates glucose catabolism with L-2HG synthesis, and establish the fly as a unique model system for studying the endogenous functions of L-2HG during cell growth and proliferation.

Cell cycle-regulated oscillator coordinates core histone gene transcription through histone acetylation

Significance DNA replication and histone gene transcription are tightly linked and occur during the S phase of the eukaryotic cell cycle. Histone production outside of S phase is highly toxic, underscoring the importance of regulatory pathways that control histone gene expression. Although various histone regulators have been discovered, the molecular mechanisms responsible for the spatial and temporal control of histone gene expression have remained elusive. Here, we describe the discovery of Spt21 as a long-elusive cell cycle oscillator responsible for restricting histone gene transcription to the S phase of the eukaryotic cell cycle. We show here that Spt21, together with its partner protein Spt10, regulates histone gene transcription by enabling the recruitment of a roster of chromatin-remodeling proteins. DNA replication occurs during the synthetic (S) phase of the eukaryotic cell cycle and features a dramatic induction of histone gene expression for concomitant chromatin assembly. Ectopic production of core histones outside of S phase is toxic, underscoring the critical importance of regulatory pathways that ensure proper expression of histone genes. Several regulators of histone gene expression in the budding yeast Saccharomyces cerevisiae are known, yet the key oscillator responsible for restricting gene expression to S phase has remained elusive. Here, we show that suppressor of Ty (Spt)10, a putative histone acetyltransferase, and its binding partner Spt21 are key determinants of S-phase–specific histone gene expression. We show that Spt21 abundance is restricted to S phase in part by anaphase promoting complex Cdc20-homologue 1 (APCCdh1) and that it is recruited to histone gene promoters in S phase by Spt10. There, Spt21-Spt10 enables the recruitment of a cascade of regulators, including histone chaperones and the histone-acetyltransferase general control nonderepressible (Gcn) 5, which we hypothesize lead to histone acetylation and consequent transcription activation.

Analysis of the Budding Yeast Cell Cycle by Flow Cytometry

DNA synthesis is one of the landmark events in the cell cycle: G1 cells have one copy of the genome, S phase cells are actively engaged in DNA synthesis, and G2 cells have twice as much nuclear DNA as G1 cells. Cellular DNA content can be measured by staining with a fluorescent dye followed by a flow-cytometric readout. This method provides a quantitative measurement of cell cycle position on a cell-by-cell basis at high speed. Using flow cytometry, tens of thousands of single-cell measurements can be generated in a few seconds. This protocol details staining of cells of the budding yeast Saccharomyces cerevisiae for flow cytometry using Sytox Green dye in a method that can be scaled widely-from one sample to many thousands and operating on inputs ranging from 1 million to more than 100 million cells. Flow cytometry is preferred over light microscopy or Coulter analyses for the analysis of the cell cycle as DNA content and cell cycle position are being directly measured.

Synchronization and Arrest of the Budding Yeast Cell Cycle Using Chemical and Genetic Methods

The cell cycle of budding yeast can be arrested at specific positions by different genetic and chemical methods. These arrests enable study of cell cycle phase-specific phenotypes that would be missed during examination of asynchronous cultures. Some methods for arrest are reversible, with kinetics that enable release of cells back into a synchronous cycling state. Benefits of chemical and genetic methods include scalability across a large range of culture sizes from a few milliliters to many liters, ease of execution, the absence of specific equipment requirements, and synchronization and release of the entire culture. Of note, cell growth and division are decoupled during arrest and block-release experiments. Cells will continue transcription, translation, and accumulation of protein while arrested. If allowed to reenter the cell cycle, cells will do so as a population of mixed, larger-than-normal cells. Despite this important caveat, many aspects of budding yeast physiology are accessible using these simple chemical and genetic tools. Described here are methods for the block and release of cells in G1 phase and at the M/G1 transition using α-factor mating pheromone and the temperature-sensitive cdc15-2 allele, respectively, in addition to methods for arresting the cell cycle in early S phase and at G2/M by using hydroxyurea and nocodazole, respectively.

Methods for Synchronization and Analysis of the Budding Yeast Cell Cycle

Like other eukaryotes, budding yeast temporally separate cell growth and division. DNA synthesis is distinct from chromosome segregation. Storage carbohydrates are accumulated slowly and then rapidly liquidated once per cycle. Cyclin-dependent kinase associates with multiple different transcriptionally and posttranslationally regulated cyclins to drive the cell cycle. These and other crucial events of cellular growth and division are limited to narrow windows of the cell cycle. Many experiments in the yeast laboratory treat a culture of cells as a homogeneous mixture. Measurements of asynchronous cultures are, however, confounded by the presence of cells in various cell cycle stages; measuring a population average in unsynchronized cells provides at best a decreased signal and at worst an artifactual result. A number of experimentally tractable methods have been developed to generate populations of yeast cells that are synchronized with respect to cell cycle phase. Robust methods for determining cell cycle position have also been developed. These methods are introduced here.