Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map

The conserved Tpk1 regulates non-homologous end joining double-strand break repair by phosphorylation of Nej1, a homolog of the human XLF

The yeast cyclic AMP-dependent protein kinase A (PKA) is a ubiquitous serine-threonine kinase, encompassing three catalytic (Tpk1-3) and one regulatory (Bcy1) subunits. Evidence suggests PKA involvement in DNA damage checkpoint response, but how DNA repair pathways are regulated by PKA subunits remains inconclusive. Here, we report that deleting the tpk1 catalytic subunit reduces non-homologous end joining (NHEJ) efficiency, whereas tpk2-3 and bcy1 deletion does not. Epistatic analyses revealed that tpk1, as well as the DNA damage checkpoint kinase (dun1) and NHEJ factor (nej1), co-function in the same pathway, and parallel to the NHEJ factor yku80. Chromatin immunoprecipitation and resection data suggest that tpk1 deletion influences repair protein recruitments and DNA resection. Further, we show that Tpk1 phosphorylation of Nej1 at S298 (a Dun1 phosphosite) is indispensable for NHEJ repair and nuclear targeting of Nej1 and its binding partner Lif1. In mammalian cells, loss of PRKACB (human homolog of Tpk1) also reduced NHEJ efficiency, and similarly, PRKACB was found to phosphorylate XLF (a Nej1 human homolog) at S263, a corresponding residue of the yeast Nej1 S298. Together, our results uncover a new and conserved mechanism for Tpk1 and PRKACB in phosphorylating Nej1 (or XLF), which is critically required for NHEJ repair.

FACT interacts with Set3 HDAC and fine-tunes GAL1 transcription in response to environmental stimulation

The histone chaperone facilitates chromatin transactions (FACT) functions in various DNA transactions. How FACT performs these multiple functions remains largely unknown. Here, we found, for the first time, that the N-terminal domain of its Spt16 subunit interacts with the Set3 histone deacetylase complex (Set3C) and that FACT and Set3C function in the same pathway to regulate gene expression in some settings. We observed that Spt16-G132D mutant proteins show defects in binding to Set3C but not other reported FACT interactors. At the permissive temperature, induction of the GAL1 and GAL10 genes is reduced in both spt16-G132D and set3Δ cells, whereas transient upregulation of GAL10 noncoding RNA (ncRNA), which is transcribed from the 3′ end of the GAL10 gene, is elevated. Mutations that inhibit GAL10 ncRNA transcription reverse the GAL1 and GAL10 induction defects in spt16-G132D and set3Δ mutant cells. Mechanistically, set3Δ and FACT (spt16-G132D) mutants show reduced histone acetylation and increased nucleosome occupancy at the GAL1 promoter under inducing conditions and inhibition of GAL10 ncRNA transcription also partially reverses these chromatin changes. These results indicate that FACT interacts with Set3C, which in turn prevents uncontrolled GAL10 ncRNA expression and fine-tunes the expression of GAL genes upon a change in carbon source.

ReporterSeq reveals genome-wide dynamic modulators of the heat shock response across diverse stressors

Understanding cellular stress response pathways is challenging because of the complexity of regulatory mechanisms and response dynamics, which can vary with both time and the type of stress. We developed a reverse genetic method called ReporterSeq to comprehensively identify genes regulating a stress-induced transcription factor under multiple conditions in a time-resolved manner. ReporterSeq links RNA-encoded barcode levels to pathway-specific output under genetic perturbations, allowing pooled pathway activity measurements via DNA sequencing alone and without cell enrichment or single-cell isolation. We used ReporterSeq to identify regulators of the heat shock response (HSR), a conserved, poorly understood transcriptional program that protects cells from proteotoxicity and is misregulated in disease. Genome-wide HSR regulation in budding yeast was assessed across 15 stress conditions, uncovering novel stress-specific, time-specific, and constitutive regulators. ReporterSeq can assess the genetic regulators of any transcriptional pathway with the scale of pooled genetic screens and the precision of pathway-specific readouts.

Hsp90 Co-chaperones Form Plastic Genetic Networks Adapted to Client Maturation

Heat shock protein 90 (Hsp90) is a molecular chaperone regulating the activity of diverse client proteins together with a plethora of different co-chaperones. Whether these functionally cooperate has remained enigmatic. We analyze all double mutants of 11 Saccharomyces cerevisiae Hsp90 co-chaperones in vivo concerning effects on cell physiology and the activation of specific client proteins. We find that client activation is supported by a genetic network with weak epistasis between most co-chaperones and a few modules with strong genetic interactions. These include an epistatic module regulating protein translation and dedicated epistatic networks for specific clients. For kinases, the bridging of Hsp70 and Hsp90 by Sti1/Hop is essential for activation, whereas for steroid hormone receptors, an epistatic module regulating their dwell time on Hsp90 is crucial, highlighting the specific needs of different clients. Thus, the Hsp90 system is characterized by plastic co-chaperone networks fine-tuning the conformational processing in a client-specific manner.

Chromatin dynamics and DNA replication roadblocks

A broad spectrum of spontaneous and genotoxin-induced DNA lesions impede replication fork progression. The DNA damage response that acts to promote completion of DNA replication is associated with dynamic changes in chromatin structure that include two distinct processes which operate genome-wide during S-phase. The first, often referred to as histone recycling or parental histone segregation, is characterized by the transfer of parental histones located ahead of replication forks onto nascent DNA. The second, known as de novo chromatin assembly, consists of the deposition of new histone molecules onto nascent DNA. Because these two processes occur at all replication forks, their potential to influence a multitude of DNA repair and DNA damage tolerance mechanisms is considerable. The purpose of this review is to provide a description of parental histone segregation and de novo chromatin assembly, and to illustrate how these processes influence cellular responses to DNA replication roadblocks.

Consolidation of network and experimental pharmacology to divulge the antidiabetic action of Ficus benghalensis L. bark

A total of 21 different bioactives were identified from F. benghalensis in which 3 molecules, i.e., apigenin, 3',4',5,7-tetrahydroxy-3-methoxyflavone, and kaempferol were predicted to target the highest number of proteins involved in diabetic pathogenesis in which protein tyrosine phosphatase 1b was primarily targeted. Similarly, a docking study identified ursolic acid to have the highest binding affinity with protein tyrosine phosphatase 1b. The combined synergic network analysis identified PI3K/Akt signaling pathway to be primarily modulated followed by the calcium signaling pathway. Similarly, in oral glucose tolerance test, we observed the efficacy of hydroalcoholic extract of F. benghalensis to lower the total area under the curve of glucose and increase total area under curve of insulin for 2 hours. Likewise, hydroalcoholic extract reversed the altered homeostatic hepatic enzymes after 28 days of treatments. Similarly, the extract also enhanced the antioxidant enzymes level like catalase and superoxide dismutase in liver homogenate. In summary, hydroalcoholic extract of F. benghalensis bark may act as an antidiabetic agent by enhancing the glycolysis, decreasing gluconeogenesis, promoting glucose uptake, enhancing insulin secretion, and maintaining pancreatic β-cell mass via PI3K/Akt signaling pathway and downregulating the function of  protein tyrosine phosphatase 1b.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02788-7.

The box C/D snoRNP assembly factor Bcd1 interacts with the histone chaperone Rtt106 and controls its transcription dependent activity

Biogenesis of eukaryotic box C/D small nucleolar ribonucleoproteins initiates co-transcriptionally and requires the action of the assembly machinery including the Hsp90/R2TP complex, the Rsa1p:Hit1p heterodimer and the Bcd1 protein. We present genetic interactions between the Rsa1p-encoding gene and genes involved in chromatin organization including RTT106 that codes for the H3-H4 histone chaperone Rtt106p controlling H3K56ac deposition. We show that Bcd1p binds Rtt106p and controls its transcription-dependent recruitment by reducing its association with RNA polymerase II, modulating H3K56ac levels at gene body. We reveal the 3D structures of the free and Rtt106p-bound forms of Bcd1p using nuclear magnetic resonance and X-ray crystallography. The interaction is also studied by a combination of biophysical and proteomic techniques. Bcd1p interacts with a region that is distinct from the interaction interface between the histone chaperone and histone H3. Our results are evidence for a protein interaction interface for Rtt106p that controls its transcription-associated activity.

Biogenesis of small nucleolar RNAs ribonucleoproteins (snoRNPs) requires dedicated assembly machinery. Here, the authors show that a subset of snoRNP assembly factors interacts, genetically or directly, with factors modulating chromatin architecture, suggesting a link between ribosome formation and chromatin functions.

The Amazing Acrobat: Yeast's Histone H3K56 Juggles Several Important Roles While Maintaining Perfect Balance

Acetylation on lysine 56 of histone H3 of the yeast Saccharomyces cerevisiae has been implicated in many cellular processes that affect genome stability. Despite being the object of much research, the complete scope of the roles played by K56 acetylation is not fully understood even today. The acetylation is put in place at the S-phase of the cell cycle, in order to flag newly synthesized histones that are incorporated during DNA replication. The signal is removed by two redundant deacetylases, Hst3 and Hst4, at the entry to G2/M phase. Its crucial location, at the entry and exit points of the DNA into and out of the nucleosome, makes this a central modification, and dictates that if acetylation and deacetylation are not well concerted and executed in a timely fashion, severe genomic instability arises. In this review, we explore the wealth of information available on the many roles played by H3K56 acetylation and the deacetylases Hst3 and Hst4 in DNA replication and repair.

Emergence and propagation of epistasis in metabolic networks

Epistasis is often used to probe functional relationships between genes, and it plays an important role in evolution. However, we lack theory to understand how functional relationships at the molecular level translate into epistasis at the level of whole-organism phenotypes, such as fitness. Here, I derive two rules for how epistasis between mutations with small effects propagates from lower- to higher-level phenotypes in a hierarchical metabolic network with first-order kinetics and how such epistasis depends on topology. Most importantly, weak epistasis at a lower level may be distorted as it propagates to higher levels. Computational analyses show that epistasis in more realistic models likely follows similar, albeit more complex, patterns. These results suggest that pairwise inter-gene epistasis should be common, and it should generically depend on the genetic background and environment. Furthermore, the epistasis coefficients measured for high-level phenotypes may not be sufficient to fully infer the underlying functional relationships.

Cross-species identification of PIP5K1-, splicing- and ubiquitin-related pathways as potential targets for RB1-deficient cells

The RB1 tumor suppressor is recurrently mutated in a variety of cancers including retinoblastomas, small cell lung cancers, triple-negative breast cancers, prostate cancers, and osteosarcomas. Finding new synthetic lethal (SL) interactions with RB1 could lead to new approaches to treating cancers with inactivated RB1. We identified 95 SL partners of RB1 based on a Drosophila screen for genetic modifiers of the eye phenotype caused by defects in the RB1 ortholog, Rbf1. We validated 38 mammalian orthologs of Rbf1 modifiers as RB1 SL partners in human cancer cell lines with defective RB1 alleles. We further show that for many of the RB1 SL genes validated in human cancer cell lines, low activity of the SL gene in human tumors, when concurrent with low levels of RB1 was associated with improved patient survival. We investigated higher order combinatorial gene interactions by creating a novel Drosophila cancer model with co-occurring Rbf1, Pten and Ras mutations, and found that targeting RB1 SL genes in this background suppressed the dramatic tumor growth and rescued fly survival whilst having minimal effects on wild-type cells. Finally, we found that drugs targeting the identified RB1 interacting genes/pathways, such as UNC3230, PYR-41, TAK-243, isoginkgetin, madrasin, and celastrol also elicit SL in human cancer cell lines. In summary, we identified several high confidence, evolutionarily conserved, novel targets for RB1-deficient cells that may be further adapted for the treatment of human cancer.

Numerous Post-translational Modifications of RNA Polymerase II Subunit Rpb4/7 Link Transcription to Post-transcriptional Mechanisms

Rpb4/7 binds RNA polymerase II (RNA Pol II) transcripts co-transcriptionally and accompanies them throughout their lives. By virtue of its capacity to interact with key regulators (e.g., RNA Pol II, eIF3, and Pat1) temporally and spatially, Rpb4/7 regulates the major stages of the mRNA life cycle. Here we show that Rpb4/7 can undergo more than 100 combinations of post-translational modifications (PTMs). Remarkably, the Rpb4/7 PTM repertoire changes as the mRNA/Rpb4/7 complex progresses from one stage to the next. These temporal PTMs regulate Rpb4 interactions with key regulators of gene expression that control transcriptional and post-transcriptional stages. Moreover, one mutant type specifically affects mRNA synthesis, whereas the other affects mRNA synthesis and decay; both types disrupt the balance between mRNA synthesis and decay ("mRNA buffering") and the cell's capacity to respond to the environment. We propose that temporal Rpb4/7 PTMs mediate the cross-talk among the various stages of the mRNA life cycle.

Matrix (factorization) reloaded: flexible methods for imputing genetic interactions with cross-species and side information

MOTIVATION

Mapping genetic interactions (GIs) can reveal important insights into cellular function and has potential translational applications. There has been great progress in developing high-throughput experimental systems for measuring GIs (e.g. with double knockouts) as well as in defining computational methods for inferring (imputing) unknown interactions. However, existing computational methods for imputation have largely been developed for and applied in baker's yeast, even as experimental systems have begun to allow measurements in other contexts. Importantly, existing methods face a number of limitations in requiring specific side information and with respect to computational cost. Further, few have addressed how GIs can be imputed when data are scarce.

RESULTS

In this article, we address these limitations by presenting a new imputation framework, called Extensible Matrix Factorization (EMF). EMF is a framework of composable models that flexibly exploit cross-species information in the form of GI data across multiple species, and arbitrary side information in the form of kernels (e.g. from protein-protein interaction networks). We perform a rigorous set of experiments on these models in matched GI datasets from baker's and fission yeast. These include the first such experiments on genome-scale GI datasets in multiple species in the same study. We find that EMF models that exploit side and cross-species information improve imputation, especially in data-scarce settings. Further, we show that EMF outperforms the state-of-the-art deep learning method, even when using strictly less data, and incurs orders of magnitude less computational cost.

AVAILABILITY

Implementations of models and experiments are available at: https://github.com/lrgr/EMF.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

On Biases Of Attention In Scientific Discovery

How do nuances of scientists' attention influence what they discover? We pursue an understanding of the influences of patterns of attention on discovery with a case study about confirmations of protein-protein interactions over time. We find that modeling and accounting for attention can help us to recognize and interpret biases in large-scale and widely used databases of confirmed interactions and to better understand missing data and unknowns. Additionally, we present an analysis of how awareness of patterns of attention and use of debiasing techniques can foster earlier discoveries.

Genetic interaction mapping informs integrative structure determination of protein complexes

Determining structures of protein complexes is crucial for understanding cellular functions. Here, we describe an integrative structure determination approach that relies on in vivo measurements of genetic interactions. We construct phenotypic profiles for point mutations crossed against gene deletions or exposed to environmental perturbations, followed by converting similarities between two profiles into an upper bound on the distance between the mutated residues. We determine the structure of the yeast histone H3-H4 complex based on ~500,000 genetic interactions of 350 mutants. We then apply the method to subunits Rpb1-Rpb2 of yeast RNA polymerase II and subunits RpoB-RpoC of bacterial RNA polymerase. The accuracy is comparable to that based on chemical cross-links; using restraints from both genetic interactions and cross-links further improves model accuracy and precision. The approach provides an efficient means to augment integrative structure determination with in vivo observations.

The functional proteome landscape of Escherichia coli

Recent developments in high-throughput reverse genetics^1,2 have revolutionized our ability to map gene function and interactions^3–6. The power of these approaches lies on their ability to discover functionally-associated genes, which elicit similar phenotypic changes across multiple perturbations (chemical, environmental, or genetic) when knocked out^7–9. However, due to the large number of perturbations, these approaches have been limited to growth or morphological readouts¹⁰. Here, we have used a high-content biochemical readout, thermal proteome profiling¹¹, to measure proteome-wide abundance and thermal stability of 121 genetic perturbations in Escherichia coli. We observed that thermal stability, and therefore the state and interactions of essential proteins is commonly modulated, opening up the possibility to study a protein group that is particularly inaccessible to genetics. We show that functionally-associated proteins have coordinated abundance and thermal stability changes across perturbations, due to their co-regulation and physical interactions (with proteins, metabolites, or co-factors). Finally, we provide mechanistic insights into previously determined growth phenotypes¹² that go beyond the deleted gene. These data, available at http://ecoliTPP.shiny.embl.de, represent a rich resource for inferring protein functions and interactions.

Recruitment of Xrn1 to stress-induced genes allows efficient transcription by controlling RNA polymerase II backtracking

A new paradigm has emerged proposing that the crosstalk between nuclear transcription and cytoplasmic mRNA stability keeps robust mRNA levels in cells under steady-state conditions. A key piece in this crosstalk is the highly conserved 5'-3' RNA exonuclease Xrn1, which degrades most cytoplasmic mRNAs but also associates with nuclear chromatin to activate transcription by not well-understood mechanisms. Here, we investigated the role of Xrn1 in the transcriptional response of Saccharomyces cerevisiae cells to osmotic stress. We show that a lack of Xrn1 results in much lower transcriptional induction of the upregulated genes but in similar high levels of their transcripts because of parallel mRNA stabilization. Unexpectedly, lower transcription in xrn1 occurs with a higher accumulation of RNA polymerase II (RNAPII) at stress-inducible genes, suggesting that this polymerase remains inactive backtracked. Xrn1 seems to be directly implicated in the formation of a competent elongation complex because Xrn1 is recruited to the osmotic stress-upregulated genes in parallel with the RNAPII complex, and both are dependent on the mitogen-activated protein kinase Hog1. Our findings extend the role of Xrn1 in preventing the accumulation of inactive RNAPII at highly induced genes to other situations of rapid and strong transcriptional upregulation.

CAF-1 and Rtt101p function within the replication-coupled chromatin assembly network to promote H4 K16ac, preventing ectopic silencing

Replication-coupled chromatin assembly is achieved by a network of alternate pathways containing different chromatin assembly factors and histone-modifying enzymes that coordinate deposition of nucleosomes at the replication fork. Here we describe the organization of a CAF-1-dependent pathway in Saccharomyces cerevisiae that regulates acetylation of histone H4 K16. We demonstrate factors that function in this CAF-1-dependent pathway are important for preventing establishment of silenced states at inappropriate genomic sites using a crippled HMR locus as a model, while factors specific to other assembly pathways do not. This CAF-1-dependent pathway required the cullin Rtt101p, but was functionally distinct from an alternate pathway involving Rtt101p-dependent ubiquitination of histone H3 and the chromatin assembly factor Rtt106p. A major implication from this work is that cells have the inherent ability to create different chromatin modification patterns during DNA replication via differential processing and deposition of histones by distinct chromatin assembly pathways within the network.

Chromatin regulatory genes differentially interact in networks to facilitate distinct GAL1 activity and noise profiles

Controlling chromatin state constitutes a major regulatory step in gene expression regulation across eukaryotes. While global cellular features or processes are naturally impacted by chromatin state alterations, little is known about how chromatin regulatory genes interact in networks to dictate downstream phenotypes. Using the activity of the canonical galactose network in yeast as a model, here, we measured the impact of the disruption of key chromatin regulatory genes on downstream gene expression, genetic noise and fitness. Using Trichostatin A and nicotinamide, we characterized how drug-based modulation of global histone deacetylase activity affected these phenotypes. Performing epistasis analysis, we discovered phenotype-specific genetic interaction networks of chromatin regulators. Our work provides comprehensive insights into how the galactose network activity is affected by protein interaction networks formed by chromatin regulators.

Interaction between MyD88, TIRAP and IL1RL1 against Helicobacter pylori infection

The Toll-interleukin 1 receptor superfamily includes the genes interleukin 1 receptor-like 1 (IL1RL1), Toll like receptors (TLRs), myeloid differentiation primary-response 88 (MyD88), and MyD88 adaptor-like (TIRAP). This study describes the interaction between MyD88, TIRAP and IL1RL1 against Helicobacter pylori infection. Cases and controls were genotyped at the polymorphic sites MyD88 rs6853, TIRAP rs8177374 and IL1RL1 rs11123923. The results show that specific combinations of IL1RL1-TIRAP (AA-CT; P: 2,8 × 10^–17) and MyD88-TIRAP-IL1RL1 (AA-CT-AA; P: 1,4 × 10^–8) – but not MyD88 alone—act synergistically against Helicobacter pylori. Nuclear magnetic resonance (NMR) clearly discriminates cases from controls by highlighting significantly different expression levels of several metabolites (tyrosine, tryptophan, phenylalanine, branched-chain amino acids, short chain fatty acids, glucose, sucrose, urea, etc.). NMR also identifies the following dysregulated metabolic pathways associated to Helicobacter pylori infection: phenylalanine and tyrosine metabolism, pterine biosynthesis, starch and sucrose metabolism, and galactose metabolism. Furthermore, NMR discriminates between the cases heterozygous at the IL1RL1 locus from those homozygous at the same locus. Heterozygous patients are characterized by high levels of lactate, and IL1RL1—both associated with anti-inflammatory activity—and low levels of the pro-inflammatory molecules IL-1β, TNF-α, COX-2, and IL-6.

Exploring the Histone Acetylation Cycle in the Protozoan Model Tetrahymena thermophila

The eukaryotic histone acetylation cycle is composed of three classes of proteins, histone acetyltransferases (HATs) that add acetyl groups to lysine amino acids, bromodomain (BRD) containing proteins that are one of the most characterized of several protein domains that recognize acetyl-lysine (Kac) and effect downstream function, and histone deacetylases (HDACs) that catalyze the reverse reaction. Dysfunction of selected proteins of these three classes is associated with human disease such as cancer. Additionally, the HATs, BRDs, and HDACs of fungi and parasitic protozoa present potential drug targets. Despite their importance, the function and mechanisms of HATs, BRDs, and HDACs and how they relate to chromatin remodeling (CR) remain incompletely understood. Tetrahymena thermophila (Tt) provides a highly tractable single-celled free-living protozoan model for studying histone acetylation, featuring a massively acetylated somatic genome, a property that was exploited in the identification of the first nuclear/type A HAT Gcn5 in the 1990s. Since then, Tetrahymena remains an under-explored model for the molecular analysis of HATs, BRDs, and HDACs. Studies of HATs, BRDs, and HDACs in Tetrahymena have the potential to reveal the function of HATs and BRDs relevant to both fundamental eukaryotic biology and to the study of disease mechanisms in parasitic protozoa.

An Optimized Competitive-Aging Method Reveals Gene-Drug Interactions Underlying the Chronological Lifespan of Saccharomyces cerevisiae

The chronological lifespan of budding yeast is a model of aging and age-related diseases. This paradigm has recently allowed genome-wide screening of genetic factors underlying post-mitotic viability in a simple unicellular system, which underscores its potential to provide a comprehensive view of the aging process. However, results from different large-scale studies show little overlap and typically lack quantitative resolution to derive interactions among different aging factors. We previously introduced a sensitive, parallelizable approach to measure the chronological-lifespan effects of gene deletions based on the competitive aging of fluorescence-labeled strains. Here, we present a thorough description of the method, including an improved multiple-regression model to estimate the association between death rates and fluorescent signals, which accounts for possible differences in growth rate and experimental batch effects. We illustrate the experimental procedure-from data acquisition to calculation of relative survivorship-for ten deletion strains with known lifespan phenotypes, which is achieved with high technical replicability. We apply our method to screen for gene-drug interactions in an array of yeast deletion strains, which reveals a functional link between protein glycosylation and lifespan extension by metformin. Competitive-aging screening coupled to multiple-regression modeling provides a powerful, straight-forward way to identify aging factors in yeast and their interactions with pharmacological interventions.

Integration of multiple biological contexts reveals principles of synthetic lethality that affect reproducibility

Synthetic lethal screens have the potential to identify new vulnerabilities incurred by specific cancer mutations but have been hindered by lack of agreement between studies. In the case of KRAS, we identify that published synthetic lethal screen hits significantly overlap at the pathway rather than gene level. Analysis of pathways encoded as protein networks could identify synthetic lethal candidates that are more reproducible than those previously reported. Lack of overlap likely stems from biological rather than technical limitations as most synthetic lethal phenotypes are strongly modulated by changes in cellular conditions or genetic context, the latter determined using a pairwise genetic interaction map that identifies numerous interactions that suppress synthetic lethal effects. Accounting for pathway, cellular and genetic context nominates a DNA repair dependency in KRAS-mutant cells, mediated by a network containing BRCA1. We provide evidence for why most reported synthetic lethals are not reproducible which is addressable using a multi-faceted testing framework.

A census of pathway maps in cancer systems biology

A key goal of cancer systems biology is to use big data to elucidate the molecular networks by which cancer develops. However, to date there has been no systematic evaluation of how far these efforts have progressed. In this Analysis, we survey six major systems biology approaches for mapping and modelling cancer pathways with attention to how well their resulting network maps cover and enhance current knowledge. Our sample of 2,070 systems biology maps captures all literature-curated cancer pathways with significant enrichment, although the strong tendency is for these maps to recover isolated mechanisms rather than entire integrated processes. Systems biology maps also identify previously underappreciated functions, such as a potential role for human papillomavirus-induced chromosomal alterations in ovarian tumorigenesis, and they add new genes to known cancer pathways, such as those related to metabolism, Hippo signalling and immunity. Notably, we find that many cancer networks have been provided only in journal figures and not for programmatic access, underscoring the need to deposit network maps in community databases to ensure they can be readily accessed. Finally, few of these findings have yet been clinically translated, leaving ample opportunity for future translational studies. Periodic surveys of cancer pathway maps, such as the one reported here, are critical to assess progress in the field and identify underserved areas of methodology and cancer biology.

Genetic Modifiers and Rare Mendelian Disease

Despite advances in high-throughput sequencing that have revolutionized the discovery of gene defects in rare Mendelian diseases, there are still gaps in translating individual genome variation to observed phenotypic outcomes. While we continue to improve genomics approaches to identify primary disease-causing variants, it is evident that no genetic variant acts alone. In other words, some other variants in the genome (genetic modifiers) may alleviate (suppress) or exacerbate (enhance) the severity of the disease, resulting in the variability of phenotypic outcomes. Thus, to truly understand the disease, we need to consider how the disease-causing variants interact with the rest of the genome in an individual. Here, we review the current state-of-the-field in the identification of genetic modifiers in rare Mendelian diseases and discuss the potential for future approaches that could bridge the existing gap.

The ATAD2/ANCCA homolog Yta7 cooperates with Scm3HJURP to deposit Cse4CENP-A at the centromere in yeast

The AAA⁺ ATPase and bromodomain factor ATAD2/ANCCA is overexpressed in many types of cancer, but how it contributes to tumorigenesis is not understood. Here, we report that the Saccharomyces cerevisiae homolog Yta7^ATAD2 is a deposition factor for the centromeric histone H3 variant Cse4^CENP-A at the centromere in yeast. Yta7^ATAD2 regulates the levels of centromeric Cse4^CENP-A in that yta7∆ causes reduced Cse4^CENP-A deposition, whereas YTA7 overexpression causes increased Cse4^CENP-A deposition. Yta7^ATAD2 coimmunoprecipitates with Cse4^CENP-A and is associated with the centromere, arguing for a direct role of Yta7^ATAD2 in Cse4^CENP-A deposition. Furthermore, increasing centromeric Cse4^CENP-A levels by YTA7 overexpression requires the activity of Scm3^HJURP, the centromeric nucleosome assembly factor. Importantly, Yta7^ATAD2 interacts in vivo with Scm3^HJURP, indicating that Yta7^ATAD2 is a cochaperone for Scm3^HJURP The absence of Yta7 causes defects in growth and chromosome segregation with mutations in components of the inner kinetochore (CTF19/CCAN, Mif2^CENP-C, Cbf1). Since Yta7^ATAD2 is an AAA⁺ ATPase and potential hexameric unfoldase, our results suggest that it may unfold the Cse4^CENP-A histone and hand it over to Scm3^HJURP for subsequent deposition in the centromeric nucleosome. Furthermore, our findings suggest that ATAD2 overexpression may enhance malignant transformation in humans by misregulating centromeric CENP-A levels, thus leading to defects in kinetochore assembly and chromosome segregation.

A Quantitative Genetic Interaction Map of HIV Infection

We have developed a platform for quantitative genetic interaction mapping using viral infectivity as a functional readout and constructed a viral host-dependency epistasis map (vE-MAP) of 356 human genes linked to HIV function, comprising >63,000 pairwise genetic perturbations. The vE-MAP provides an expansive view of the genetic dependencies underlying HIV infection and can be used to identify drug targets and study viral mutations. We found that the RNA deadenylase complex, CNOT, is a central player in the vE-MAP and show that knockout of CNOT1, 10, and 11 suppressed HIV infection in primary T cells by upregulating innate immunity pathways. This phenotype was rescued by deletion of IRF7, a transcription factor regulating interferon-stimulated genes, revealing a previously unrecognized host signaling pathway involved in HIV infection. The vE-MAP represents a generic platform that can be used to study the global effects of how different pathogens hijack and rewire the host during infection.

Two factor authentication: Asf1 mediates crosstalk between H3 K14 and K56 acetylation

The ability of histone chaperone Anti-silencing factor 1 (Asf1) to direct acetylation of lysine 56 of histone H3 (H3K56ac) represents an important regulatory step in genome replication and DNA repair. In Saccharomyces cerevisiae, Asf1 interacts functionally with a second chaperone, Vps75, and the lysine acetyltransferase (KAT) Rtt109. Both Asf1 and Vps75 can increase the specificity of histone acetylation by Rtt109, but neither alter selectivity. However, changes in acetylation selectivity have been observed in histones extracted from cells, which contain a plethora of post-translational modifications. In the present study, we use a series of singly acetylated histones to test the hypothesis that histone pre-acetylation and histone chaperones function together to drive preferential acetylation of H3K56. We show that pre-acetylated H3K14ac/H4 functions with Asf1 to drive specific acetylation of H3K56 by Rtt109-Vps75. Additionally, we identified an exosite containing an acidic patch in Asf1 and show that mutations to this region alter Asf1-mediated crosstalk that changes Rtt109-Vps75 selectivity. Our proposed mechanism suggests that Gcn5 acetylates H3K14, recruiting remodeler complexes, allowing for the Asf1-H3K14ac/H4 complex to be acetylated at H3K56 by Rtt109-Vps75. This mechanism explains the conflicting biochemical data and the genetic links between Rtt109, Vps75, Gcn5 and Asf1 in the acetylation of H3K56.

The mRNA degradation factor Xrn1 regulates transcription elongation in parallel to Ccr4

Co-transcriptional imprinting of mRNA by Rpb4 and Rpb7 subunits of RNA polymerase II (RNAPII) and by the Ccr4-Not complex conditions its post-transcriptional fate. In turn, mRNA degradation factors like Xrn1 are able to influence RNAPII-dependent transcription, making a feedback loop that contributes to mRNA homeostasis. In this work, we have used repressible yeast GAL genes to perform accurate measurements of transcription and mRNA degradation in a set of mutants. This genetic analysis uncovered a link from mRNA decay to transcription elongation. We combined this experimental approach with computational multi-agent modelling and tested different possibilities of Xrn1 and Ccr4 action in gene transcription. This double strategy brought us to conclude that both Xrn1-decaysome and Ccr4-Not regulate RNAPII elongation, and that they do it in parallel. We validated this conclusion measuring TFIIS genome-wide recruitment to elongating RNAPII. We found that xrn1Δ and ccr4Δ exhibited very different patterns of TFIIS versus RNAPII occupancy, which confirmed their distinct role in controlling transcription elongation. We also found that the relative influence of Xrn1 and Ccr4 is different in the genes encoding ribosomal proteins as compared to the rest of the genome.

Histone Chaperone Paralogs Have Redundant, Cooperative, and Divergent Functions in Yeast

Gene duplications increase organismal robustness by providing freedom for gene divergence or by increasing gene dosage. The yeast histone chaperones Fpr3 and Fpr4 are paralogs that can assemble nucleosomes in vitro; however, the genomic locations they target and their functional relationship is poorly understood. We refined the yeast synthetic genetic array approach to enable the functional dissection of gene paralogs. Applying this method to Fpr3 and Fpr4 uncovered redundant, cooperative, and divergent functions. While Fpr3 is uniquely involved in chromosome segregation, Fpr3 and Fpr4 cooperate to regulate genes involved in polyphosphate metabolism and ribosome biogenesis. We find that the TRAMP5 RNA exosome is critical for fitness in Δfpr3Δfpr4 yeast and leverage this information to identify an important role for Fpr4 at the 5' ends of protein coding genes. Additionally, Fpr4 and TRAMP5 negatively regulate RNAs from the nontranscribed spacers of ribosomal DNA. Yeast lacking Fpr3 and Fpr4 exhibit a genome instability phenotype at the ribosomal DNA, which implies that these histone chaperones regulate chromatin structure and DNA access at this location. Taken together. we provide genetic and transcriptomic evidence that Fpr3 and Fpr4 operate separately, cooperatively, and redundantly to regulate a variety of chromatin environments.

Actin and Nuclear Envelope Components Influence Ectopic Recombination in the Absence of Swr1

The accuracy of most DNA processes depends on chromatin integrity and dynamics. Our analyses in the yeast Saccharomyces cerevisiae show that an absence of Swr1 (the catalytic and scaffold subunit of the chromatin-remodeling complex SWR) leads to the formation of long-duration Rad52, but not RPA, foci and to an increase in intramolecular recombination. These phenotypes are further increased by MMS, zeocin, and ionizing radiation, but not by double-strand breaks, HU, or transcription/replication collisions, suggesting that they are associated with specific DNA lesions. Importantly, these phenotypes can be specifically suppressed by mutations in: (1) chromatin-anchorage internal nuclear membrane components (mps3∆75-150 and src1∆); (2) actin and actin regulators (act1-157, act1-159, crn1∆, and cdc42-6); or (3) the SWR subunit Swc5 and the SWR substrate Htz1 However, they are not suppressed by global disruption of actin filaments or by the absence of Csm4 (a component of the external nuclear membrane that forms a bridging complex with Mps3, thus connecting the actin cytoskeleton with chromatin). Moreover, swr1∆-induced Rad52 foci and intramolecular recombination are not associated with tethering recombinogenic DNA lesions to the nuclear periphery. In conclusion, the absence of Swr1 impairs efficient recombinational repair of specific DNA lesions by mechanisms that are influenced by SWR subunits, including actin, and nuclear envelope components. We suggest that these recombinational phenotypes might be associated with a pathological effect on homologous recombination of actin-containing complexes.

Mapping genetic interactions in cancer: a road to rational combination therapies

The discovery of synthetic lethal interactions between poly (ADP-ribose) polymerase (PARP) inhibitors and BRCA genes, which are involved in homologous recombination, led to the approval of PARP inhibition as a monotherapy for patients with BRCA1/2-mutated breast or ovarian cancer. Studies following the initial observation of synthetic lethality demonstrated that the reach of PARP inhibitors is well beyond just BRCA1/2 mutants. Insights into the mechanisms of action of anticancer drugs are fundamental for the development of targeted monotherapies or rational combination treatments that will synergize to promote cancer cell death and overcome mechanisms of resistance. The development of targeted therapeutic agents is premised on mapping the physical and functional dependencies of mutated genes in cancer. An important part of this effort is the systematic screening of genetic interactions in a variety of cancer types. Until recently, genetic-interaction screens have relied either on the pairwise perturbations of two genes or on the perturbation of genes of interest combined with inhibition by commonly used anticancer drugs. Here, we summarize recent advances in mapping genetic interactions using targeted, genome-wide, and high-throughput genetic screens, and we discuss the therapeutic insights obtained through such screens. We further focus on factors that should be considered in order to develop a robust analysis pipeline. Finally, we discuss the integration of functional interaction data with orthogonal methods and suggest that such approaches will increase the reach of genetic-interaction screens for the development of rational combination therapies.

Recent insights into the genotype-phenotype relationship from massively parallel genetic assays

With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype-fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry (e.g. enzyme activity) and medicine (e.g. antibody binding) can be quantified and even selected directly by these assays. This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype-phenotype relationship (distribution of mutation effects, epistasis), their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.

Nucleosome Remodeling by Fun30SMARCAD1 in the DNA Damage Response

Many cellular pathways are dedicated to maintain the integrity of the genome. In eukaryotes, the underlying DNA transactions occur in the context of chromatin. Cells utilize chromatin and its dynamic nature to regulate those genome integrity pathways. Accordingly, chromatin becomes restructured and modified around DNA damage sites. Here, we review the current knowledge of a chromatin remodeler Fun30^SMARCAD1, which plays a key role in genome maintenance. Fun30^SMARCAD1 promotes DNA end resection and the repair of DNA double-stranded breaks (DSBs). Notably, however, Fun30^SMARCAD1 plays additional roles in maintaining heterochromatin and promoting transcription. Overall, Fun30^SMARCAD1 is involved in distinct processes and the specific roles of Fun30^SMARCAD1 at DSBs, replication forks and sites of transcription appear discordant at first view. Nonetheless, a picture emerges in which commonalities within these context-dependent roles of Fun30^SMARCAD1 exist, which may help to gain a more global understanding of chromatin alterations induced by Fun30^SMARCAD1.

Network Clustering Analysis Using Mixture Exponential-Family Random Graph Models and Its Application in Genetic Interaction Data

MOTIVATION

Epistatic miniarrary profile (EMAP) studies have enabled the mapping of large-scale genetic interaction networks and generated large amounts of data in model organisms. It provides an incredible set of molecular tools and advanced technologies that should be efficiently understanding the relationship between the genotypes and phenotypes of individuals. However, the network information gained from EMAP cannot be fully exploited using the traditional statistical network models. Because the genetic network is always heterogeneous, for example, the network structure features for one subset of nodes are different from those of the left nodes. Exponential-family random graph models (ERGMs) are a family of statistical models, which provide a principled and flexible way to describe the structural features (e.g., the density, centrality, and assortativity) of an observed network. However, the single ERGM is not enough to capture this heterogeneity of networks. In this paper, we consider a mixture ERGM (MixtureEGRM) networks, which model a network with several communities, where each community is described by a single EGRM.

RESULTS

EM algorithm is a classical method to solve the mixture problem, however, it will be very slow when the data size is huge in the numerous applications. We adopt an efficient novel online graph clustering algorithm to classify the graph nodes and estimate the ERGM parameters for the MixtureERGM. In comparison studies, the MixtureERGM outperforms the role analysis for the network cluster in which the mixture of exponential-family random graph model is developed for many ego-network according to their roles. One genetic interaction network of yeast and two real social networks (provided as supplemental materials, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TCBB.2017.2743711) show the wide potential application of the MixtureERGM.

Systematical Analysis of the Protein Targets of Lactoferricin B and Histatin-5 Using Yeast Proteome Microarrays

Antimicrobial peptides (AMPs) have potential antifungal activities; however, their intracellular protein targets are poorly reported. Proteome microarray is an effective tool with high-throughput and rapid platform that systematically identifies the protein targets. In this study, we have used yeast proteome microarrays for systematical identification of the yeast protein targets of Lactoferricin B (Lfcin B) and Histatin-5. A total of 140 and 137 protein targets were identified from the triplicate yeast proteome microarray assays for Lfcin B and Histatin-5, respectively. The Gene Ontology (GO) enrichment analysis showed that Lfcin B targeted more enrichment categories than Histatin-5 did in all GO biological processes, molecular functions, and cellular components. This might be one of the reasons that Lfcin B has a lower minimum inhibitory concentration (MIC) than Histatin-5. Moreover, pairwise essential proteins that have lethal effects on yeast were analyzed through synthetic lethality. A total of 11 synthetic lethal pairs were identified within the protein targets of Lfcin B. However, only three synthetic lethal pairs were identified within the protein targets of Histatin-5. The higher number of synthetic lethal pairs identified within the protein targets of Lfcin B might also be the reason for Lfcin B to have lower MIC than Histatin-5. Furthermore, two synthetic lethal pairs were identified between the unique protein targets of Lfcin B and Histatin-5. Both the identified synthetic lethal pairs proteins are part of the Spt-Ada-Gcn5 acetyltransferase (SAGA) protein complex that regulates gene expression via histone modification. Identification of synthetic lethal pairs between Lfcin B and Histatin-5 and their involvement in the same protein complex indicated synergistic combination between Lfcin B and Histatin-5. This hypothesis was experimentally confirmed by growth inhibition assay.

A Gaussian process-based definition reveals new and bona fide genetic interactions compared to a multiplicative model in the Gram-negative Escherichia coli

MOTIVATION

A digenic genetic interaction (GI) is observed when mutations in two genes within the same organism yield a phenotype that is different from the expected, given each mutation's individual effects. While multiplicative scoring is widely applied to define GIs, revealing underlying gene functions, it remains unclear if it is the most suitable choice for scoring GIs in Escherichia coli. Here, we assess many different definitions, including the multiplicative model, for mapping functional links between genes and pathways in E.coli.

RESULTS

Using our published E.coli GI datasets, we show computationally that a machine learning Gaussian process (GP)-based definition better identifies functional associations among genes than a multiplicative model, which we have experimentally confirmed on a set of gene pairs. Overall, the GP definition improves the detection of GIs, biological reasoning of epistatic connectivity, as well as the quality of GI maps in E.coli, and, potentially, other microbes.

AVAILABILITY AND IMPLEMENTATION

The source code and parameters used to generate the machine learning models in WEKA software were provided in the Supplementary information.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Flux balance analysis with or without molecular crowding fails to predict two thirds of experimentally observed epistasis in yeast

Computational predictions of double gene knockout effects by flux balance analysis (FBA) have been used to characterized genome-wide patterns of epistasis in microorganisms. However, it is unclear how in silico predictions are related to in vivo epistasis, as FBA predicted only a minority of experimentally observed genetic interactions between non-essential metabolic genes in yeast. Here, we perform a detailed comparison of yeast experimental epistasis data to predictions generated with different constraint-based metabolic modeling algorithms. The tested methods comprise standard FBA; a variant of MOMA, which was specifically designed to predict fitness effects of non-essential gene knockouts; and two alternative implementations of FBA with macro-molecular crowding, which account approximately for enzyme kinetics. The number of interactions uniquely predicted by one method is typically larger than its overlap with any alternative method. Only 20% of negative and 10% of positive interactions jointly predicted by all methods are confirmed by the experimental data; almost all unique predictions appear to be false. More than two thirds of epistatic interactions are undetectable by any of the tested methods. The low prediction accuracies indicate that the physiology of yeast double metabolic gene knockouts is dominated by processes not captured by current constraint-based analysis methods.

Microbial Experimental Evolution - a proving ground for evolutionary theory and a tool for discovery

Microbial experimental evolution uses controlled laboratory populations to study the mechanisms of evolution. The molecular analysis of evolved populations enables empirical tests that can confirm the predictions of evolutionary theory, but can also lead to surprising discoveries. As with other fields in the life sciences, microbial experimental evolution has become a tool, deployed as part of the suite of techniques available to the molecular biologist. Here, I provide a review of the general findings of microbial experimental evolution, especially those relevant to molecular microbiologists that are new to the field. I also relate these results to design considerations for an evolution experiment and suggest future directions for those working at the intersection of experimental evolution and molecular biology.

The elongation factor Spn1 is a multi-functional chromatin binding protein

The process of transcriptional elongation by RNA polymerase II (RNAPII) in a chromatin context involves a large number of crucial factors. Spn1 is a highly conserved protein encoded by an essential gene and is known to interact with RNAPII and the histone chaperone Spt6. Spn1 negatively regulates the ability of Spt6 to interact with nucleosomes, but the chromatin binding properties of Spn1 are largely unknown. Here, we demonstrate that full length Spn1 (amino acids 1–410) binds DNA, histones H3–H4, mononucleosomes and nucleosomal arrays, and has weak nucleosome assembly activity. The core domain of Spn1 (amino acids 141–305), which is necessary and sufficient in Saccharomyces cerevisiae for growth under ideal growth conditions, is unable to optimally interact with histones, nucleosomes and/or DNA and fails to assemble nucleosomes in vitro. Although competent for binding with Spt6 and RNAPII, the core domain derivative is not stably recruited to the CYC1 promoter, indicating chromatin interactions are an important aspect of normal Spn1 functions in vivo. Moreover, strong synthetic genetic interactions are observed with Spn1 mutants and deletions of histone chaperone genes. Taken together, these results indicate that Spn1 is a histone binding factor with histone chaperone functions.

GEMINI: a variational Bayesian approach to identify genetic interactions from combinatorial CRISPR screens

Systems for CRISPR-based combinatorial perturbation of two or more genes are emerging as powerful tools for uncovering genetic interactions. However, systematic identification of these relationships is complicated by sample, reagent, and biological variability. We develop a variational Bayes approach (GEMINI) that jointly analyzes all samples and reagents to identify genetic interactions in pairwise knockout screens. The improved accuracy and scalability of GEMINI enables the systematic analysis of combinatorial CRISPR knockout screens, regardless of design and dimension. GEMINI is available as an open source R package on GitHub at https://github.com/sellerslab/gemini.

Network dynamics of the yeast methyltransferome

Sulfur assimilation and the biosynthesis of methionine, cysteine and S-adenosylmethionine (SAM) are critical to life. As a cofactor, SAM is required for the activity of most methyltransferases (MTases) and as such has broad impact on diverse cellular processes. Assigning function to MTases remains a challenge however, as many MTases are partially redundant, they often have multiple cellular roles and these activities can be condition-dependent. To address these challenges, we performed a systematic synthetic genetic analysis of all pairwise MTase double mutations in normal and stress conditions (16°C, 37°C, and LiCl) resulting in an unbiased comprehensive overview of the complexity and plasticity of the methyltransferome. Based on this network, we performed biochemical analysis of members of the histone H3K4 COMPASS complex and the phospholipid methyltransferase OPI3 to reveal a new role for a phospholipid methyltransferase in mediating histone methylation (H3K4) which underscores a potential link between lipid homeostasis and histone methylation. Our findings provide a valuable resource to study methyltransferase function, the dynamics of the methyltransferome, genetic crosstalk between biological processes and the dynamics of the methyltransferome in response to cellular stress.

Heme promotes transcriptional and demethylase activities of Gis1, a member of the histone demethylase JMJD2/KDM4 family

The yeast Gis1 protein is a transcriptional regulator belonging to the JMJD2/KDM4 subfamily of demethylases that contain a JmjC domain, which are highly conserved from yeast to humans. They have important functions in histone methylation, cellular signaling and tumorigenesis. Besides serving as a cofactor in many proteins, heme is known to directly regulate the activities of proteins ranging from transcriptional regulators to potassium channels. Here, we report a novel mechanism governing heme regulation of Gis1 transcriptional and histone demethylase activities. We found that two Gis1 modules, the JmjN + JmjC domain and the zinc finger (ZnF), can bind to heme specifically in vitro. In vivo functional analysis showed that the ZnF, not the JmjN + JmjC domain, promotes heme activation of transcriptional activity. Likewise, measurements of the demethylase activity of purified Gis1 proteins showed that full-length Gis1 and the JmjN + JmjC domain both possess demethylase activity. However, heme potentiates the demethylase activity of full-length Gis1, but not that of the JmjN + JmjC domain, which can confer heme activation of transcriptional activity in an unrelated protein. These results demonstrate that Gis1 represents a novel class of multi-functional heme sensing and signaling proteins, and that heme binding to the ZnF stimulates Gis1 demethylase and transcriptional activities.

Mapping the protein-protein and genetic interactions of cancer to guide precision medicine

Massive efforts to sequence cancer genomes have compiled an impressive catalogue of cancer mutations, revealing the recurrent exploitation of a handful of 'hallmark cancer pathways'. However, unraveling how sets of mutated proteins in these and other pathways hijack pro-proliferative signaling networks and dictate therapeutic responsiveness remains challenging. Here, we show that cancer driver protein-protein interactions are enriched for additional cancer drivers, highlighting the power of physical interaction maps to explain known, as well as uncover new, disease-promoting pathway interrelationships. We hypothesize that by systematically mapping the protein-protein and genetic interactions in cancer-thereby creating Cancer Cell Maps-we will create resources against which to contextualize a patient's mutations into perturbed pathways/complexes and thereby specify a matching targeted therapeutic cocktail.

Tolerance of DNA Replication Stress Is Promoted by Fumarate Through Modulation of Histone Demethylation and Enhancement of Replicative Intermediate Processing in Saccharomyces cerevisiae

Fumarase is a well-characterized TCA cycle enzyme that catalyzes the reversible conversion of fumarate to malate. In mammals, fumarase acts as a tumor suppressor, and loss-of-function mutations in the FH gene in hereditary leiomyomatosis and renal cell cancer result in the accumulation of intracellular fumarate-an inhibitor of α-ketoglutarate-dependent dioxygenases. Fumarase promotes DNA repair by nonhomologous end joining in mammalian cells through interaction with the histone variant H2A.Z, and inhibition of KDM2B, a H3 K36-specific histone demethylase. Here, we report that Saccharomyces cerevisiae fumarase, Fum1p, acts as a response factor during DNA replication stress, and fumarate enhances survival of yeast lacking Htz1p (H2A.Z in mammals). We observed that exposure to DNA replication stress led to upregulation as well as nuclear enrichment of Fum1p, and raising levels of fumarate in cells via deletion of FUM1 or addition of exogenous fumarate suppressed the sensitivity to DNA replication stress of htz1Δ mutants. This suppression was independent of modulating nucleotide pool levels. Rather, our results are consistent with fumarate conferring resistance to DNA replication stress in htz1Δ mutants by inhibiting the H3 K4-specific histone demethylase Jhd2p, and increasing H3 K4 methylation. Although the timing of checkpoint activation and deactivation remained largely unaffected by fumarate, sensors and mediators of the DNA replication checkpoint were required for fumarate-dependent resistance to replication stress in the htz1Δ mutants. Together, our findings imply metabolic enzymes and metabolites aid in processing replicative intermediates by affecting chromatin modification states, thereby promoting genome integrity.

Dot1 promotes H2B ubiquitination by a methyltransferase-independent mechanism

The histone methyltransferase Dot1 is conserved from yeast to human and methylates lysine 79 of histone H3 (H3K79) on the core of the nucleosome. H3K79 methylation by Dot1 affects gene expression and the response to DNA damage, and is enhanced by monoubiquitination of the C-terminus of histone H2B (H2Bub1). To gain more insight into the functions of Dot1, we generated genetic interaction maps of increased-dosage alleles of DOT1. We identified a functional relationship between increased Dot1 dosage and loss of the DUB module of the SAGA co-activator complex, which deubiquitinates H2Bub1 and thereby negatively regulates H3K79 methylation. Increased Dot1 dosage was found to promote H2Bub1 in a dose-dependent manner and this was exacerbated by the loss of SAGA-DUB activity, which also caused a negative genetic interaction. The stimulatory effect on H2B ubiquitination was mediated by the N-terminus of Dot1, independent of methyltransferase activity. Our findings show that Dot1 and H2Bub1 are subject to bi-directional crosstalk and that Dot1 possesses chromatin regulatory functions that are independent of its methyltransferase activity.

SAGA DUBm-mediated surveillance regulates prompt export of stress-inducible transcripts for proteostasis

During stress, prompt export of stress-inducible transcripts is critical for cell survival. Here, we characterize a function of the SAGA (Spt-Ada-Gcn5 acetyltransferase) deubiquitylating module (DUBm) in monitoring messenger ribonucleoprotein (mRNP) biogenesis to regulate non-canonical mRNA export of stress-inducible transcripts. Our genetic and biochemical analyses suggest that there is a functional relationship between Sgf73p of DUBm and the essential mRNA export factor, Yra1p. Under physiological conditions, Sgf73p is critical for the proper chromatin localization and RNA binding of Yra1p, while also quality controlling the biogenesis of mRNPs in conjunction with the nuclear exosome exonuclease, Rrp6p. Under environmental stress, when immediate transport of stress-inducible transcripts is imperative, Sgf73p facilitates the bypass of canonical surveillance and promotes the timely export of necessary transcripts. Overall, our results show that the Sgf73p-mediated plasticity of gene expression is important for the ability of cells to tolerate stress and regulate proteostasis to survive under environmental uncertainty.

Stress-inducible transcripts are quickly exported to preserve cell survival when cells are under stress. Here, the authors suggest that Sgf73p of the SAGA deubiquitylating module monitors messenger ribonucleoprotein biogenesis to regulate non-canonical export of stress-inducible transcripts.

Functional protein representations from biological networks enable diverse cross-species inference

Transferring knowledge between species is key for many biological applications, but is complicated by divergent and convergent evolution. Many current approaches for this problem leverage sequence and interaction network data to transfer knowledge across species, exemplified by network alignment methods. While these techniques do well, they are limited in scope, creating metrics to address one specific problem or task. We take a different approach by creating an environment where multiple knowledge transfer tasks can be performed using the same protein representations. Specifically, our kernel-based method, MUNK, integrates sequence and network structure to create functional protein representations, embedding proteins from different species in the same vector space. First we show proteins in different species that are close in MUNK-space are functionally similar. Next, we use these representations to share knowledge of synthetic lethal interactions between species. Importantly, we find that the results using MUNK-representations are at least as accurate as existing algorithms for these tasks. Finally, we generalize the notion of a phenolog ('orthologous phenotype') to use functionally similar proteins (i.e. those with similar representations). We demonstrate the utility of this broadened notion by using it to identify known phenologs and novel non-obvious ones supported by current research.

The ability of transcription factors to differentially regulate gene expression is a crucial component of the mechanism underlying inversion, a frequently observed genetic interaction pattern

Genetic interactions, a phenomenon whereby combinations of mutations lead to unexpected effects, reflect how cellular processes are wired and play an important role in complex genetic diseases. Understanding the molecular basis of genetic interactions is crucial for deciphering pathway organization as well as understanding the relationship between genetic variation and disease. Several hypothetical molecular mechanisms have been linked to different genetic interaction types. However, differences in genetic interaction patterns and their underlying mechanisms have not yet been compared systematically between different functional gene classes. Here, differences in the occurrence and types of genetic interactions are compared for two classes, gene-specific transcription factors (GSTFs) and signaling genes (kinases and phosphatases). Genome-wide gene expression data for 63 single and double deletion mutants in baker's yeast reveals that the two most common genetic interaction patterns are buffering and inversion. Buffering is typically associated with redundancy and is well understood. In inversion, genes show opposite behavior in the double mutant compared to the corresponding single mutants. The underlying mechanism is poorly understood. Although both classes show buffering and inversion patterns, the prevalence of inversion is much stronger in GSTFs. To decipher potential mechanisms, a Petri Net modeling approach was employed, where genes are represented as nodes and relationships between genes as edges. This allowed over 9 million possible three and four node models to be exhaustively enumerated. The models show that a quantitative difference in interaction strength is a strict requirement for obtaining inversion. In addition, this difference is frequently accompanied with a second gene that shows buffering. Taken together, these results provide a mechanistic explanation for inversion. Furthermore, the ability of transcription factors to differentially regulate expression of their targets provides a likely explanation why inversion is more prevalent for GSTFs compared to kinases and phosphatases.

iSeq 2.0: A Modular and Interchangeable Toolkit for Interaction Screening in Yeast

We developed a flexible toolkit for combinatorial screening in Saccharomyces cerevisiae, which generates large libraries of cells, each uniquely barcoded to mark a combination of DNA elements. This interaction sequencing platform (iSeq 2.0) includes genomic landing pads that assemble combinations through sequential integration of plasmids or yeast mating, 15 barcoded plasmid libraries containing split selectable markers (URA3AI, KanMXAI, HphMXAI, and NatMXAI), and an array of ∼24,000 "double-barcoder" strains that can make existing yeast libraries iSeq compatible. Various DNA elements are compatible with iSeq: DNA introduced on integrating plasmids, engineered genomic modifications, or entire genetic backgrounds. DNA element libraries are modular and interchangeable, and any two libraries can be combined, making iSeq capable of performing many new combinatorial screens by short-read sequencing.