RESUMEN
Polypharmacology drugs-compounds that inhibit multiple proteins-have many applications but are difficult to design. To address this challenge we have developed POLYGON, an approach to polypharmacology based on generative reinforcement learning. POLYGON embeds chemical space and iteratively samples it to generate new molecular structures; these are rewarded by the predicted ability to inhibit each of two protein targets and by drug-likeness and ease-of-synthesis. In binding data for >100,000 compounds, POLYGON correctly recognizes polypharmacology interactions with 82.5% accuracy. We subsequently generate de-novo compounds targeting ten pairs of proteins with documented co-dependency. Docking analysis indicates that top structures bind their two targets with low free energies and similar 3D orientations to canonical single-protein inhibitors. We synthesize 32 compounds targeting MEK1 and mTOR, with most yielding >50% reduction in each protein activity and in cell viability when dosed at 1-10 µM. These results support the potential of generative modeling for polypharmacology.
Asunto(s)
Simulación del Acoplamiento Molecular , Humanos , Serina-Treonina Quinasas TOR/metabolismo , Polifarmacología , MAP Quinasa Quinasa 1/antagonistas & inhibidores , MAP Quinasa Quinasa 1/metabolismo , MAP Quinasa Quinasa 1/química , Inhibidores de Proteínas Quinasas/farmacología , Inhibidores de Proteínas Quinasas/química , Unión Proteica , Descubrimiento de Drogas/métodos , Diseño de Fármacos , Supervivencia Celular/efectos de los fármacosRESUMEN
The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.
Asunto(s)
Cromosomas , Proteoma , Antígenos Nucleares/genética , Antígenos Nucleares/metabolismo , Cromatina/genética , Cromosomas/metabolismo , Humanos , Proteínas Asociadas a Matriz Nuclear/metabolismo , Proteoma/metabolismo , ARN Ribosómico , Proteínas de Unión al ARN/genéticaRESUMEN
A major goal of cancer research is to understand how mutations distributed across diverse genes affect common cellular systems, including multiprotein complexes and assemblies. Two challengeshow to comprehensively map such systems and how to identify which are under mutational selectionhave hindered this understanding. Accordingly, we created a comprehensive map of cancer protein systems integrating both new and published multi-omic interaction data at multiple scales of analysis. We then developed a unified statistical model that pinpoints 395 specific systems under mutational selection across 13 cancer types. This map, called NeST (Nested Systems in Tumors), incorporates canonical processes and notable discoveries, including a PIK3CA-actomyosin complex that inhibits phosphatidylinositol 3-kinase signaling and recurrent mutations in collagen complexes that promote tumor proliferation. These systems can be used as clinical biomarkers and implicate a total of 548 genes in cancer evolution and progression. This work shows how disparate tumor mutations converge on protein assemblies at different scales.
Asunto(s)
Proteínas de Neoplasias/genética , Proteínas de Neoplasias/metabolismo , Neoplasias/genética , Neoplasias/metabolismo , Mapas de Interacción de Proteínas/genética , Genes Relacionados con las Neoplasias , Humanos , Mutación , Mapeo de Interacción de Proteínas/métodosRESUMEN
Genetic screens in Saccharomyces cerevisiae have allowed for the identification of many genes as sensors or effectors of DNA damage, typically by comparing the fitness of genetic mutants in the presence or absence of DNA-damaging treatments. However, these static screens overlook the dynamic nature of DNA damage response pathways, missing time-dependent or transient effects. Here, we examine gene dependencies in the dynamic response to ultraviolet radiation-induced DNA damage by integrating ultra-high-density arrays of 6144 diploid gene deletion mutants with high-frequency time-lapse imaging. We identify 494 ultraviolet radiation response genes which, in addition to recovering molecular pathways and protein complexes previously annotated to DNA damage repair, include components of the CCR4-NOT complex, tRNA wobble modification, autophagy, and, most unexpectedly, 153 nuclear-encoded mitochondrial genes. Notably, mitochondria-deficient strains present time-dependent insensitivity to ultraviolet radiation, posing impaired mitochondrial function as a protective factor in the ultraviolet radiation response.
Asunto(s)
Proteínas de Saccharomyces cerevisiae , Rayos Ultravioleta , Daño del ADN , Reparación del ADN , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/metabolismoRESUMEN
All mammals progress through similar physiological stages throughout life, from early development to puberty, aging, and death. Yet, the extent to which this conserved physiology reflects underlying genomic events is unclear. Here, we map the common methylation changes experienced by mammalian genomes as they age, focusing on comparison of humans with dogs, an emerging model of aging. Using oligo-capture sequencing, we characterize methylomes of 104 Labrador retrievers spanning a 16-year age range, achieving >150× coverage within mammalian syntenic blocks. Comparison with human methylomes reveals a nonlinear relationship that translates dog-to-human years and aligns the timing of major physiological milestones between the two species, with extension to mice. Conserved changes center on developmental gene networks, which are sufficient to translate age and the effects of anti-aging interventions across multiple mammals. These results establish methylation not only as a diagnostic age readout but also as a cross-species translator of physiological aging milestones.
Asunto(s)
Envejecimiento/genética , Metilación de ADN/genética , Animales , Perros , HumanosRESUMEN
Systematic measurements of genetic interactions have been used to classify gene functions and to categorize genes into protein complexes, functional pathways and biological processes. This protocol describes how to perform a high-throughput genetic interaction screen in S. cerevisiae using a variant of epistatic miniarray profiles (E-MAP) in which the fitnesses of 6144 colonies are measured simultaneously. We also describe the computational methods to analyze the resulting data.
Asunto(s)
Epistasis Genética/genética , Genoma Fúngico/genética , Saccharomyces cerevisiae/genéticaRESUMEN
Human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) represents a distinct classification of cancer with worse expected outcomes. Of the 11 genes recurrently mutated in HNSCC, we identify a singular and substantial survival advantage for mutations in the gene encoding Nuclear Set Domain Containing Protein 1 (NSD1), a histone methyltransferase altered in approximately 10% of patients. This effect, a 55% decrease in risk of death in NSD1-mutated versus non-mutated patients, can be validated in an independent cohort. NSD1 alterations are strongly associated with widespread genome hypomethylation in the same tumors, to a degree not observed for any other mutated gene. To address whether NSD1 plays a causal role in these associations, we use CRISPR-Cas9 to disrupt NSD1 in HNSCC cell lines and find that this leads to substantial CpG hypomethylation and sensitivity to cisplatin, a standard chemotherapy in head and neck cancer, with a 40% to 50% decrease in the IC50 value. Such results are reinforced by a survey of 1,001 cancer cell lines, in which loss-of-function NSD1 mutations have an average 23% decrease in cisplatin IC50 value compared with cell lines with wild-type NSD1Significance: This study identifies a favorable subtype of HPV-negative HNSCC linked to NSD1 mutation, hypomethylation, and cisplatin sensitivity. Mol Cancer Ther; 17(7); 1585-94. ©2018 AACR.
Asunto(s)
Carcinoma de Células Escamosas/tratamiento farmacológico , Metilación de ADN/genética , Neoplasias de Cabeza y Cuello/tratamiento farmacológico , Péptidos y Proteínas de Señalización Intracelular/genética , Proteínas Nucleares/genética , Sistemas CRISPR-Cas/genética , Carcinoma de Células Escamosas/genética , Carcinoma de Células Escamosas/patología , Línea Celular Tumoral , Cisplatino/farmacología , Islas de CpG/efectos de los fármacos , Metilación de ADN/efectos de los fármacos , Resistencia a Antineoplásicos/genética , Femenino , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Neoplasias de Cabeza y Cuello/genética , Neoplasias de Cabeza y Cuello/patología , Histona Metiltransferasas , N-Metiltransferasa de Histona-Lisina , Humanos , Masculino , Mutación/efectos de los fármacos , PapillomaviridaeRESUMEN
Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These 'somatic eQTLs' (expression quantitative trait loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines and that increasing DAAM1 expression leads to invasive cell migration. Collectively, the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer.
Asunto(s)
Genes Relacionados con las Neoplasias , Mutación , Neoplasias/genética , Proteínas Adaptadoras Transductoras de Señales/genética , Isomerasas Aldosa-Cetosa/genética , Línea Celular Tumoral , Regulación Neoplásica de la Expresión Génica , Redes Reguladoras de Genes , Humanos , Proteínas de Microfilamentos , Proteínas de Unión al GTP Monoméricas/genética , Invasividad Neoplásica/genética , Neoplasias/metabolismo , Sitios de Carácter Cuantitativo , ARN Mensajero/genética , ARN Mensajero/metabolismo , ARN Neoplásico/genética , ARN Neoplásico/metabolismo , ARN no Traducido/genética , ARN no Traducido/metabolismo , Secuenciación Completa del Genoma , Proteínas de Unión al GTP rhoRESUMEN
We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies.
Asunto(s)
Mapeo Cromosómico/métodos , Repeticiones Palindrómicas Cortas Agrupadas y Regularmente Espaciadas/genética , Técnicas Químicas Combinatorias , Epistasis Genética/genética , Proteínas de Neoplasias/genética , Células A549 , Línea Celular Tumoral , Células HeLa , Secuenciación de Nucleótidos de Alto Rendimiento , HumanosRESUMEN
We have developed a general progressive procedure, Active Interaction Mapping, to guide assembly of the hierarchy of functions encoding any biological system. Using this process, we assemble an ontology of functions comprising autophagy, a central recycling process implicated in numerous diseases. A first-generation model, built from existing gene networks in Saccharomyces, captures most known autophagy components in broad relation to vesicle transport, cell cycle, and stress response. Systematic analysis identifies synthetic-lethal interactions as most informative for further experiments; consequently, we saturate the model with 156,364 such measurements across autophagy-activating conditions. These targeted interactions provide more information about autophagy than all previous datasets, producing a second-generation ontology of 220 functions. Approximately half are previously unknown; we confirm roles for Gyp1 at the phagophore-assembly site, Atg24 in cargo engulfment, Atg26 in cytoplasm-to-vacuole targeting, and Ssd1, Did4, and others in selective and non-selective autophagy. The procedure and autophagy hierarchy are at http://atgo.ucsd.edu/.
Asunto(s)
Autofagia/genética , Redes Reguladoras de Genes , Genómica/métodos , Proteínas de Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/genética , Biología de Sistemas/métodos , Proteínas Relacionadas con la Autofagia/genética , Proteínas Relacionadas con la Autofagia/metabolismo , Bases de Datos Genéticas , Complejos de Clasificación Endosomal Requeridos para el Transporte/genética , Complejos de Clasificación Endosomal Requeridos para el Transporte/metabolismo , Proteínas Activadoras de GTPasa/genética , Proteínas Activadoras de GTPasa/metabolismo , Regulación Fúngica de la Expresión Génica , Glucosiltransferasas/genética , Glucosiltransferasas/metabolismo , Humanos , Modelos Genéticos , Pichia/genética , Pichia/metabolismo , Mapas de Interacción de Proteínas , Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/metabolismo , Integración de SistemasRESUMEN
An emerging therapeutic strategy for cancer is to induce selective lethality in a tumor by exploiting interactions between its driving mutations and specific drug targets. Here we use a multi-species approach to develop a resource of synthetic lethal interactions relevant to cancer therapy. First, we screen in yeast â¼169,000 potential interactions among orthologs of human tumor suppressor genes (TSG) and genes encoding drug targets across multiple genotoxic environments. Guided by the strongest signal, we evaluate thousands of TSG-drug combinations in HeLa cells, resulting in networks of conserved synthetic lethal interactions. Analysis of these networks reveals that interaction stability across environments and shared gene function increase the likelihood of observing an interaction in human cancer cells. Using these rules, we prioritize â¼10(5) human TSG-drug combinations for future follow-up. We validate interactions based on cell and/or patient survival, including topoisomerases with RAD17 and checkpoint kinases with BLM.
Asunto(s)
Antineoplásicos/uso terapéutico , Biomarcadores de Tumor/genética , Redes Reguladoras de Genes/efectos de los fármacos , Genes Supresores de Tumor , Mutación , Medicina de Precisión/métodos , Mapas de Interacción de Proteínas/efectos de los fármacos , Saccharomyces cerevisiae/efectos de los fármacos , Neoplasias del Cuello Uterino/tratamiento farmacológico , Proteínas de Ciclo Celular/genética , Proteínas de Ciclo Celular/metabolismo , Proliferación Celular/efectos de los fármacos , Supervivencia Celular/efectos de los fármacos , Relación Dosis-Respuesta a Droga , Femenino , Regulación Fúngica de la Expresión Génica/efectos de los fármacos , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Predisposición Genética a la Enfermedad , Células HeLa , Humanos , Estimación de Kaplan-Meier , Terapia Molecular Dirigida , Fenotipo , Interferencia de ARN , RecQ Helicasas/genética , RecQ Helicasas/metabolismo , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/metabolismo , Transducción de Señal/efectos de los fármacos , Mutaciones Letales Sintéticas , Factores de Tiempo , Transfección , Neoplasias del Cuello Uterino/genética , Neoplasias del Cuello Uterino/metabolismo , Neoplasias del Cuello Uterino/mortalidadRESUMEN
HIV-infected individuals are living longer on antiretroviral therapy, but many patients display signs that in some ways resemble premature aging. To investigate and quantify the impact of chronic HIV infection on aging, we report a global analysis of the whole-blood DNA methylomes of 137 HIV+ individuals under sustained therapy along with 44 matched HIV- individuals. First, we develop and validate epigenetic models of aging that are independent of blood cell composition. Using these models, we find that both chronic and recent HIV infection lead to an average aging advancement of 4.9 years, increasing expected mortality risk by 19%. In addition, sustained infection results in global deregulation of the methylome across >80,000 CpGs and specific hypomethylation of the region encoding the human leukocyte antigen locus (HLA). We find that decreased HLA methylation is predictive of lower CD4 / CD8 T cell ratio, linking molecular aging, epigenetic regulation, and disease progression.
Asunto(s)
Envejecimiento/genética , Metilación de ADN , Epigénesis Genética , Infecciones por VIH/genética , Antígenos HLA/genética , Envejecimiento/inmunología , Fármacos Anti-VIH/uso terapéutico , Relación CD4-CD8 , Estudios de Casos y Controles , Enfermedad Crónica , Islas de CpG , Progresión de la Enfermedad , Perfilación de la Expresión Génica , Estudio de Asociación del Genoma Completo , Genotipo , Infecciones por VIH/diagnóstico , Infecciones por VIH/tratamiento farmacológico , Infecciones por VIH/inmunología , Infecciones por VIH/mortalidad , Antígenos HLA/inmunología , Humanos , Modelos Genéticos , Fenotipo , Factores de Riesgo , Factores de Tiempo , Resultado del TratamientoRESUMEN
Accurately translating genotype to phenotype requires accounting for the functional impact of genetic variation at many biological scales. Here we present a strategy for genotype-phenotype reasoning based on existing knowledge of cellular subsystems. These subsystems and their hierarchical organization are defined by the Gene Ontology or a complementary ontology inferred directly from previously published datasets. Guided by the ontology's hierarchical structure, we organize genotype data into an "ontotype," that is, a hierarchy of perturbations representing the effects of genetic variation at multiple cellular scales. The ontotype is then interpreted using logical rules generated by machine learning to predict phenotype. This approach substantially outperforms previous, non-hierarchical methods for translating yeast genotype to cell growth phenotype, and it accurately predicts the growth outcomes of two new screens of 2,503 double gene knockouts impacting DNA repair or nuclear lumen. Ontotypes also generalize to larger knockout combinations, setting the stage for interpreting the complex genetics of disease.
RESUMEN
Chemical inhibitors of the checkpoint kinases have shown promise in the treatment of cancer, yet their clinical utility may be limited by a lack of molecular biomarkers to identify specific patients most likely to respond to therapy. To this end, we screened 112 known tumor suppressor genes for synthetic lethal interactions with inhibitors of the CHEK1 and CHEK2 checkpoint kinases. We identified eight interactions, including the Replication Factor C (RFC)-related protein RAD17. Clonogenic assays in RAD17 knockdown cell lines identified a substantial shift in sensitivity to checkpoint kinase inhibition (3.5-fold) as compared to RAD17 wild-type. Additional evidence for this interaction was found in a large-scale functional shRNA screen of over 100 genotyped cancer cell lines, in which CHEK1/2 mutant cell lines were unexpectedly sensitive to RAD17 knockdown. This interaction was widely conserved, as we found that RAD17 interacts strongly with checkpoint kinases in the budding yeast Saccharomyces cerevisiae. In the setting of RAD17 knockdown, CHEK1/2 inhibition was found to be synergistic with inhibition of WEE1, another pharmacologically relevant checkpoint kinase. Accumulation of the DNA damage marker γH2AX following chemical inhibition or transient knockdown of CHEK1, CHEK2 or WEE1 was magnified by knockdown of RAD17. Taken together, our data suggest that CHEK1 or WEE1 inhibitors are likely to have greater clinical efficacy in tumors with RAD17 loss-of-function.
Asunto(s)
Antineoplásicos/farmacología , Proteínas de Ciclo Celular/metabolismo , Proteínas de Unión al ADN/metabolismo , Neoplasias/tratamiento farmacológico , Proteínas Nucleares/metabolismo , Proteínas de Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/fisiología , Saccharomyces cerevisiae/patogenicidad , Tiofenos/farmacología , Urea/análogos & derivados , Biomarcadores Farmacológicos/metabolismo , Ciclo Celular/efectos de los fármacos , Ciclo Celular/genética , Proteínas de Ciclo Celular/genética , Quinasa 1 Reguladora del Ciclo Celular (Checkpoint 1) , Quinasa de Punto de Control 2/genética , Quinasa de Punto de Control 2/metabolismo , Daño del ADN/efectos de los fármacos , Daño del ADN/genética , Proteínas de Unión al ADN/genética , Descubrimiento de Drogas , Células HeLa , Humanos , Terapia Molecular Dirigida , Mutación/genética , Neoplasias/diagnóstico , Proteínas Nucleares/genética , Proteínas Quinasas/genética , Proteínas Quinasas/metabolismo , Proteínas Tirosina Quinasas/genética , Proteínas Tirosina Quinasas/metabolismo , ARN Interferente Pequeño/genética , Proteínas de Saccharomyces cerevisiae/genética , Urea/farmacologíaRESUMEN
Efficient repair of UV-induced DNA damage requires the precise coordination of nucleotide excision repair (NER) with numerous other biological processes. To map this crosstalk, we generated a differential genetic interaction map centered on quantitative growth measurements of >45,000 double mutants before and after different doses of UV radiation. Integration of genetic data with physical interaction networks identified a global map of 89 UV-induced functional interactions among 62 protein complexes, including a number of links between the RSC complex and several NER factors. We show that RSC is recruited to both silenced and transcribed loci following UV damage where it facilitates efficient repair by promoting nucleosome remodeling. Finally, a comparison of the response to high versus low levels of UV shows that the degree of genetic rewiring correlates with dose of UV and reveals a network of dose-specific interactions. This study makes available a large resource of UV-induced interactions, and it illustrates a methodology for identifying dose-dependent interactions based on quantitative shifts in genetic networks.
Asunto(s)
Ensamble y Desensamble de Cromatina , Reparación del ADN , Redes Reguladoras de Genes/efectos de la radiación , Saccharomyces cerevisiae/genética , Rayos Ultravioleta , Relación Dosis-Respuesta en la Radiación , Genoma Fúngico , Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/efectos de la radiación , Proteínas de Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/metabolismoRESUMEN
Classic "position-effect" experiments repositioned genes near telomeres to demonstrate that the epigenetic landscape can dramatically alter gene expression. Here, we show that systematic gene knockout collections provide an exceptional resource for interrogating position effects, not only near telomeres but at every genetic locus. Because a single reporter gene replaces each deleted gene, interrogating this reporter provides a sensitive probe into different chromatin environments while controlling for genetic context. Using this approach, we find that, whereas systematic replacement of yeast genes with the kanMX marker does not perturb the chromatin landscape, chromatin differences associated with gene position account for 35% of kanMX activity. We observe distinct chromatin influences, including a Set2/Rpd3-mediated antagonistic interaction between histone H3 lysine 36 trimethylation and the Rap1 transcriptional activation site in kanMX. This interaction explains why some yeast genes have been resistant to deletion and allows successful generation of these deletion strains through the use of a modified transformation procedure. These findings demonstrate that chromatin regulation is not governed by a uniform "histone code" but by specific interactions between chromatin and genetic factors.
Asunto(s)
Efectos de la Posición Cromosómica/genética , Epigénesis Genética , Orden Génico/genética , Saccharomyces cerevisiae/genética , Acetilación , Cromatina/metabolismo , Cromosomas Fúngicos/genética , Diploidia , Eliminación de Gen , Regulación Fúngica de la Expresión Génica , Técnicas de Inactivación de Genes , Biblioteca de Genes , Genes Fúngicos/genética , Marcadores Genéticos , Heterocigoto , Histonas/metabolismo , Lisina/metabolismo , Metilación , Mutagénesis Insercional/genética , Regiones Promotoras Genéticas/genética , Unión Proteica/genética , Procesamiento Proteico-Postraduccional/genética , Proteínas de Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/metabolismo , Transducción de Señal/genéticaRESUMEN
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.
Asunto(s)
Daño del ADN , Reparación del ADN/genética , Epistasis Genética , Redes Reguladoras de Genes , Proteínas de Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Cromatina/metabolismo , ADN de Hongos/genética , Genes Fúngicos , Histonas/genética , Histonas/metabolismo , Metilmetanosulfonato/farmacología , Proteínas Quinasas Activadas por Mitógenos/genética , Proteínas Quinasas Activadas por Mitógenos/metabolismo , Mutágenos/farmacología , Mutación , Fosfoproteínas Fosfatasas/genética , Fosfoproteínas Fosfatasas/metabolismo , Mapeo de Interacción de Proteínas , Proteínas Serina-Treonina Quinasas/genética , Proteínas Serina-Treonina Quinasas/metabolismo , Proteínas de Saccharomyces cerevisiae/genética , Transducción de Señal , Factores de Transcripción/genética , Factores de Transcripción/metabolismoRESUMEN
Transcriptional networks have been shown to evolve very rapidly, prompting questions as to how such changes arise and are tolerated. Recent comparisons of transcriptional networks across species have implicated variations in the cis-acting DNA sequences near genes as the main cause of divergence. What is less clear is how these changes interact with trans-acting changes occurring elsewhere in the genetic circuit. Here, we report the discovery of a system of compensatory trans and cis mutations in the yeast AP-1 transcriptional network that allows for conserved transcriptional regulation despite continued genetic change. We pinpoint a single species, the fungal pathogen Candida glabrata, in which a trans mutation has occurred very recently in a single AP-1 family member, distinguishing it from its Saccharomyces ortholog. Comparison of chromatin immunoprecipitation profiles between Candida and Saccharomyces shows that, despite their different DNA-binding domains, the AP-1 orthologs regulate a conserved block of genes. This conservation is enabled by concomitant changes in the cis-regulatory motifs upstream of each gene. Thus, both trans and cis mutations have perturbed the yeast AP-1 regulatory system in such a way as to compensate for one another. This demonstrates an example of "coevolution" between a DNA-binding transcription factor and its cis-regulatory site, reminiscent of the coevolution of protein binding partners.