RESUMEN
Cytokines mediate cell-cell communication in the immune system and represent important therapeutic targets1-3. A myriad of studies have highlighted their central role in immune function4-13, yet we lack a global view of the cellular responses of each immune cell type to each cytokine. To address this gap, we created the Immune Dictionary, a compendium of single-cell transcriptomic profiles of more than 17 immune cell types in response to each of 86 cytokines (>1,400 cytokine-cell type combinations) in mouse lymph nodes in vivo. A cytokine-centric view of the dictionary revealed that most cytokines induce highly cell-type-specific responses. For example, the inflammatory cytokine interleukin-1ß induces distinct gene programmes in almost every cell type. A cell-type-centric view of the dictionary identified more than 66 cytokine-driven cellular polarization states across immune cell types, including previously uncharacterized states such as an interleukin-18-induced polyfunctional natural killer cell state. Based on this dictionary, we developed companion software, Immune Response Enrichment Analysis, for assessing cytokine activities and immune cell polarization from gene expression data, and applied it to reveal cytokine networks in tumours following immune checkpoint blockade therapy. Our dictionary generates new hypotheses for cytokine functions, illuminates pleiotropic effects of cytokines, expands our knowledge of activation states of each immune cell type, and provides a framework to deduce the roles of specific cytokines and cell-cell communication networks in any immune response.
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Citocinas , Inmunidad , Análisis de la Célula Individual , Animales , Ratones , Comunicación Celular/efectos de los fármacos , Citocinas/inmunología , Perfilación de la Expresión Génica , Regulación de la Expresión Génica , Inhibidores de Puntos de Control Inmunológico/farmacología , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Inmunidad/efectos de los fármacos , Interleucina-18/inmunología , Interleucina-1beta/inmunología , Células Asesinas Naturales/inmunología , Ganglios Linfáticos/citología , Ganglios Linfáticos/inmunología , Neoplasias/inmunología , Neoplasias/terapia , Transducción de Señal/efectos de los fármacos , Programas InformáticosRESUMEN
Heat-Shock Factor 1 (HSF1), master regulator of the heat-shock response, facilitates malignant transformation, cancer cell survival, and proliferation in model systems. The common assumption is that these effects are mediated through regulation of heat-shock protein (HSP) expression. However, the transcriptional network that HSF1 coordinates directly in malignancy and its relationship to the heat-shock response have never been defined. By comparing cells with high and low malignant potential alongside their nontransformed counterparts, we identify an HSF1-regulated transcriptional program specific to highly malignant cells and distinct from heat shock. Cancer-specific genes in this program support oncogenic processes: cell-cycle regulation, signaling, metabolism, adhesion and translation. HSP genes are integral to this program, however, many are uniquely regulated in malignancy. This HSF1 cancer program is active in breast, colon and lung tumors isolated directly from human patients and is strongly associated with metastasis and death. Thus, HSF1 rewires the transcriptome in tumorigenesis, with prognostic and therapeutic implications.
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Proteínas de Unión al ADN/metabolismo , Neoplasias/metabolismo , Factores de Transcripción/metabolismo , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/patología , Línea Celular Tumoral , Células Cultivadas , Proteínas de Unión al ADN/análisis , Proteínas de Unión al ADN/genética , Femenino , Regulación Neoplásica de la Expresión Génica , Redes Reguladoras de Genes , Genoma Humano , Factores de Transcripción del Choque Térmico , Humanos , Neoplasias/patología , Factores de Transcripción/análisis , Factores de Transcripción/genéticaRESUMEN
INTRODUCTION/AIMS: Amyotrophic lateral sclerosis (ALS), a motor neuron disease, remains a clinical diagnosis with an average time from onset of symptoms to diagnosis of about 1 year. Herein we examine the possibility that interactions with an internet search engine can identify people with ALS. METHODS: We identified 285 anonymous Bing users whose queries indicated that they had been diagnosed with ALS and matched them to: (1) 3276 control users; and (2) 1814 users whose searches indicated they had ALS disease mimics. We tested whether the ALS group could be distinguished from controls and disease mimics based on search engine query data. Finally, we conducted a prospective validation from participants who provided access to their Bing search data. RESULTS: The model distinguished between the ALS group and controls with an area under the curve (AUC) of 0.81. Model scores for the ALS group differed from the disease mimics group (rank sum test, p < .05 with Bonferroni correction). Mild cognitive impairment could not be distinguished from ALS (p > .05). In the prospective analysis, the model reached an AUC of 0.74. DISCUSSION: Our results suggest that interactions with search engines should be further studied to understand the potential to act as a tool to assist in screening for ALS and to reduce diagnostic delay.
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Esclerosis Amiotrófica Lateral , Disfunción Cognitiva , Enfermedad de la Neurona Motora , Humanos , Esclerosis Amiotrófica Lateral/diagnóstico , Motor de Búsqueda , Diagnóstico TardíoRESUMEN
INTRODUCTION/AIMS: Genetics is an important risk factor for amyotrophic lateral sclerosis (ALS), a neurodegenerative disease affecting motor neurons. Recent findings demonstrate that in addition to specific genetic mutations, structural variants caused by genetic instability can also play a causative role in ALS. Genomic instability can lead to deletions, duplications, insertions, inversions, and translocations in the genome, and these changes can sometimes lead to fusion of distinct genes into a single transcript. Gene fusion events have been studied extensively in cancer; however, they have not been thoroughly investigated in ALS. The aim of this study was to determine whether gene fusions are present in ALS. METHODS: Gene fusions were identified using STAR Fusion v1.10.0 software in bulk RNA-Seq data from human postmortem samples from publicly available data sets from Target ALS and the New York Genome Center ALS Consortium. RESULTS: We report the presence of gene fusion events in several brain regions as well as in spinal cord samples in ALS. Although most gene fusions were intra-chromosomal events between neighboring genes and present in both ALS and control samples, there was a significantly greater number of unique gene fusions in ALS compared to controls. Lastly, we identified specific gene fusions with a significant burden in ALS, that were absent from both control samples and known cancer gene fusion databases. DISCUSSION: Collectively, our findings reveal an enrichment of gene fusions in ALS and suggest that these events may be an additional genetic cause linked to ALS pathogenesis.
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Esclerosis Amiotrófica Lateral , Enfermedades Neurodegenerativas , Humanos , Esclerosis Amiotrófica Lateral/genética , Esclerosis Amiotrófica Lateral/patología , Neuronas Motoras/patología , Fusión GénicaRESUMEN
We have previously established induced pluripotent stem cell (iPSC) models of Huntington's disease (HD), demonstrating CAG-repeat-expansion-dependent cell biological changes and toxicity. However, the current differentiation protocols are cumbersome and time consuming, making preparation of large quantities of cells for biochemical or screening assays difficult. Here, we report the generation of immortalized striatal precursor neurons (ISPNs) with normal (33) and expanded (180) CAG repeats from HD iPSCs, differentiated to a phenotype resembling medium spiny neurons (MSN), as a proof of principle for a more tractable patient-derived cell model. For immortalization, we used co-expression of the enzymatic component of telomerase hTERT and conditional expression of c-Myc. ISPNs can be propagated as stable adherent cell lines, and rapidly differentiated into highly homogeneous MSN-like cultures within 2 weeks, as demonstrated by immunocytochemical criteria. Differentiated ISPNs recapitulate major HD-related phenotypes of the parental iPSC model, including brain-derived neurotrophic factor (BDNF)-withdrawal-induced cell death that can be rescued by small molecules previously validated in the parental iPSC model. Proteome and RNA-seq analyses demonstrate separation of HD versus control samples by principal component analysis. We identified several networks, pathways, and upstream regulators, also found altered in HD iPSCs, other HD models, and HD patient samples. HD ISPN lines may be useful for studying HD-related cellular pathogenesis, and for use as a platform for HD target identification and screening experimental therapeutics. The described approach for generation of ISPNs from differentiated patient-derived iPSCs could be applied to a larger allelic series of HD cell lines, and to comparable modeling of other genetic disorders.
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Enfermedad de Huntington , Células Madre Pluripotentes Inducidas , Diferenciación Celular/genética , Línea Celular , Humanos , Enfermedad de Huntington/genética , Enfermedad de Huntington/metabolismo , Enfermedad de Huntington/terapia , Células Madre Pluripotentes Inducidas/metabolismo , Neuronas/metabolismoRESUMEN
MOTIVATION: Advances in bioimaging now permit in situ proteomic characterization of cell-cell interactions in complex tissues, with important applications across a spectrum of biological problems from development to disease. These methods depend on selection of antibodies targeting proteins that are expressed specifically in particular cell types. Candidate marker proteins are often identified from single-cell transcriptomic data, with variable rates of success, in part due to divergence between expression levels of proteins and the genes that encode them. In principle, marker identification could be improved by using existing databases of immunohistochemistry for thousands of antibodies in human tissue, such as the Human Protein Atlas. However, these data lack detailed annotations of the types of cells in each image. RESULTS: We develop a method to predict cell type specificity of protein markers from unlabeled images. We train a convolutional neural network with a self-supervised objective to generate embeddings of the images. Using non-linear dimensionality reduction, we observe that the model clusters images according to cell types and anatomical regions for which the stained proteins are specific. We then use estimates of cell type specificity derived from an independent single-cell transcriptomics dataset to train an image classifier, without requiring any human labelling of images. Our scheme demonstrates superior classification of known proteomic markers in kidney compared to selection via single-cell transcriptomics. AVAILABILITY AND IMPLEMENTATION: Code and trained model are available at www.github.com/murphy17/HPA-SimCLR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Anticuerpos , Proteómica , Comunicación Celular , Bases de Datos Factuales , Humanos , Aprendizaje Automático SupervisadoRESUMEN
Transcriptional and epigenetic alterations occur early in Huntington's disease (HD), and treatment with epigenetic modulators is beneficial in several HD animal models. The drug JQ1, which inhibits histone acetyl-lysine reader bromodomains, has shown promise for multiple cancers and neurodegenerative disease. We tested whether JQ1 could improve behavioral phenotypes in the R6/2 mouse model of HD and modulate HD-associated changes in transcription and epigenomics. R6/2 and non-transgenic (NT) mice were treated with JQ1 daily from 5 to 11 weeks of age and behavioral phenotypes evaluated over this period. Following the trial, cortex and striatum were isolated and subjected to mRNA-seq and ChIP-seq for the histone marks H3K4me3 and H3K27ac. Initially, JQ1 enhanced motor performance in NT mice. In R6/2 mice, however, JQ1 had no effect on rotarod or grip strength but exacerbated weight loss and worsened performance on the pole test. JQ1-induced gene expression changes in NT mice were distinct from those in R6/2 and primarily involved protein translation and bioenergetics pathways. Dysregulation of HD-related pathways in striatum was exacerbated by JQ1 in R6/2 mice, but not in NTs, and JQ1 caused a corresponding increase in the formation of a mutant huntingtin protein-dependent high molecular weight species associated with pathogenesis. This study suggests that drugs predicted to be beneficial based on their mode of action and effects in wild-type or in other neurodegenerative disease models may have an altered impact in the HD context. These observations have important implications in the development of epigenetic modulators as therapies for HD.
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Azepinas/farmacología , Corteza Cerebral/efectos de los fármacos , Corteza Cerebral/metabolismo , Cuerpo Estriado/efectos de los fármacos , Cuerpo Estriado/metabolismo , Proteína Huntingtina/metabolismo , Enfermedad de Huntington/metabolismo , Triazoles/farmacología , Acetilación , Animales , Escala de Evaluación de la Conducta , Síntomas Conductuales/tratamiento farmacológico , Corteza Cerebral/patología , Secuenciación de Inmunoprecipitación de Cromatina , Cuerpo Estriado/patología , Modelos Animales de Enfermedad , Metabolismo Energético/efectos de los fármacos , Epigénesis Genética/efectos de los fármacos , Regulación de la Expresión Génica/efectos de los fármacos , Regulación de la Expresión Génica/genética , Ontología de Genes , Histonas/metabolismo , Proteína Huntingtina/genética , Enfermedad de Huntington/tratamiento farmacológico , Enfermedad de Huntington/genética , Enfermedad de Huntington/patología , Masculino , Ratones , Ratones Transgénicos , Actividad Motora/efectos de los fármacos , Biosíntesis de Proteínas/efectos de los fármacos , RNA-Seq , Transducción de Señal/efectos de los fármacos , Transducción de Señal/genéticaRESUMEN
Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.
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Metaboloma , Metabolómica , Metabolómica/métodos , Proteómica , Flujo de TrabajoRESUMEN
Huntington's disease (HD) is a chronic neurodegenerative disorder characterized by a late clinical onset despite ubiquitous expression of the mutant Huntingtin gene (HTT) from birth. Transcriptional dysregulation is a pivotal feature of HD. Yet, the genes that are altered in the prodromal period and their regulators, which present opportunities for therapeutic intervention, remain to be elucidated. Using transcriptional and chromatin profiling, we found aberrant transcription and changes in histone H3K27acetylation in the striatum of R6/1 mice during the presymptomatic disease stages. Integrating these data, we identified the Elk-1 transcription factor as a candidate regulator of prodromal changes in HD. Exogenous expression of Elk-1 exerted beneficial effects in a primary striatal cell culture model of HD, and adeno-associated virus-mediated Elk-1 overexpression alleviated transcriptional dysregulation in R6/1 mice. Collectively, our work demonstrates that aberrant gene expression precedes overt disease onset in HD, identifies the Elk-1 transcription factor as a key regulator linked to early epigenetic and transcriptional changes in HD, and presents evidence for Elk-1 as a target for alleviating molecular pathology in HD.
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Epigenómica , Enfermedad de Huntington/genética , Proteína Elk-1 con Dominio ets/genética , Proteína Elk-1 con Dominio ets/metabolismo , Animales , Cuerpo Estriado/metabolismo , Dependovirus , Modelos Animales de Enfermedad , Histonas/metabolismo , Proteína Huntingtina/genética , Enfermedad de Huntington/tratamiento farmacológico , Ratones , Ratones Transgénicos , Neuronas/metabolismo , Proteínas Nucleares/metabolismoRESUMEN
Polycomb repressive complexes (PRCs) play key roles in developmental epigenetic regulation. Yet the mechanisms that target PRCs to specific loci in mammalian cells remain incompletely understood. In this study we show that Bmi1, a core component of Polycomb Repressive Complex 1 (PRC1), binds directly to the Runx1/CBFß transcription factor complex. Genome-wide studies in megakaryocytic cells demonstrate significant chromatin occupancy overlap between the PRC1 core component Ring1b and Runx1/CBFß and functional regulation of a considerable fraction of commonly bound genes. Bmi1/Ring1b and Runx1/CBFß deficiencies generate partial phenocopies of one another in vivo. We also show that Ring1b occupies key Runx1 binding sites in primary murine thymocytes and that this occurs via PRC2-independent mechanisms. Genetic depletion of Runx1 results in reduced Ring1b binding at these sites in vivo. These findings provide evidence for site-specific PRC1 chromatin recruitment by core binding transcription factors in mammalian cells.
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Cromatina/metabolismo , Subunidad alfa 2 del Factor de Unión al Sitio Principal/metabolismo , Subunidad beta del Factor de Unión al Sitio Principal/metabolismo , Proteínas Represoras/metabolismo , Animales , Línea Celular , Cromatografía de Afinidad , Análisis por Conglomerados , Subunidad alfa 2 del Factor de Unión al Sitio Principal/genética , Subunidad beta del Factor de Unión al Sitio Principal/genética , Perfilación de la Expresión Génica , Regulación de la Expresión Génica , Técnicas de Silenciamiento del Gen , Células Madre Hematopoyéticas/fisiología , Megacariocitos/metabolismo , Ratones , Ratones Endogámicos C57BL , Ratones Noqueados , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismo , Complejo Represivo Polycomb 1 , Proteínas del Grupo Polycomb , Unión Proteica , Multimerización de Proteína , Proteínas Proto-Oncogénicas/genética , Proteínas Proto-Oncogénicas/metabolismo , Proteínas Represoras/genética , Proteínas Represoras/aislamiento & purificación , Linfocitos T/metabolismo , Timocitos/metabolismo , Ubiquitina-Proteína Ligasas/genética , Ubiquitina-Proteína Ligasas/metabolismo , Pez Cebra/embriología , Pez Cebra/genéticaRESUMEN
Uncovering the molecular context of dysregulated metabolites is crucial to understand pathogenic pathways. However, their system-level analysis has been limited owing to challenges in global metabolite identification. Most metabolite features detected by untargeted metabolomics carried out by liquid-chromatography-mass spectrometry cannot be uniquely identified without additional, time-consuming experiments. We report a network-based approach, prize-collecting Steiner forest algorithm for integrative analysis of untargeted metabolomics (PIUMet), that infers molecular pathways and components via integrative analysis of metabolite features, without requiring their identification. We demonstrated PIUMet by analyzing changes in metabolism of sphingolipids, fatty acids and steroids in a Huntington's disease model. Additionally, PIUMet enabled us to elucidate putative identities of altered metabolite features in diseased cells, and infer experimentally undetected, disease-associated metabolites and dysregulated proteins. Finally, we established PIUMet's ability for integrative analysis of untargeted metabolomics data with proteomics data, demonstrating that this approach elicits disease-associated metabolites and proteins that cannot be inferred by individual analysis of these data.
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Algoritmos , Enfermedad de Huntington/metabolismo , Redes y Vías Metabólicas , Metabolómica/métodos , Redes Neurales de la Computación , Bases de Datos de Proteínas , Ácidos Grasos/metabolismo , Humanos , Aprendizaje Automático , Metabolómica/instrumentación , Esfingolípidos/metabolismo , Esteroides/metabolismoRESUMEN
Myeloproliferative neoplasms (MPNs) driver mutations are usually found in JAK2, MPL, and CALR genes; however, 10%-15% of cases are triple negative (TN). A previous study showed lower rate of JAK2 V617F in primary myelofibrosis patients exposed to low doses of ionizing radiation (IR) from Chernobyl accident. To examine distinct driver mutations, we enrolled 281 Ukrainian IR-exposed and unexposed MPN patients. Genomic DNA was obtained from peripheral blood leukocytes. JAK2 V617F, MPL W515, types 1- and 2-like CALR mutations were identified by Sanger Sequencing and real time polymerase chain reaction. Chromosomal alterations were assessed by oligo-SNP microarray platform. Additional genetic variants were identified by whole exome and targeted sequencing. Statistical significance was evaluated by Fisher's exact test and Wilcoxon's rank sum test (R, version 3.4.2). IR-exposed MPN patients exhibited a different genetic profile vs unexposed: lower rate of JAK2 V617F (58.4% vs 75.4%, P = .0077), higher rate of type 1-like CALR mutation (12.2% vs 3.1%, P = .0056), higher rate of TN cases (27.8% vs 16.2%, P = .0366), higher rate of potentially pathogenic sequence variants (mean numbers: 4.8 vs 3.1, P = .0242). Furthermore, we identified several potential drivers specific to IR-exposed TN MPN patients: ATM p.S1691R with copy-neutral loss of heterozygosity at 11q; EZH2 p.D659G at 7q and SUZ12 p.V71 M at 17q with copy number loss. Thus, IR-exposed MPN patients represent a group with distinct genomic characteristics worthy of further study.
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Accidente Nuclear de Chernóbil , Trastornos Mieloproliferativos/etiología , Neoplasias Inducidas por Radiación/etiología , Contaminantes Radiactivos/efectos adversos , Adulto , Anciano , Calreticulina/genética , Aberraciones Cromosómicas , ADN/genética , Femenino , Dosificación de Gen , Humanos , Janus Quinasa 2/genética , Pérdida de Heterocigocidad , Masculino , Persona de Mediana Edad , Mutación Missense , Trastornos Mieloproliferativos/epidemiología , Trastornos Mieloproliferativos/genética , Neoplasias Inducidas por Radiación/epidemiología , Neoplasias Inducidas por Radiación/genética , Receptores de Trombopoyetina/genética , Ucrania/epidemiología , Secuenciación del Exoma , Adulto JovenRESUMEN
The orchestrated action of genes controls complex biological phenotypes, yet the systematic discovery of gene and drug combinations that modulate these phenotypes in human cells is labor intensive and challenging to scale. Here, we created a platform for the massively parallel screening of barcoded combinatorial gene perturbations in human cells and translated these hits into effective drug combinations. This technology leverages the simplicity of the CRISPR-Cas9 system for multiplexed targeting of specific genomic loci and the versatility of combinatorial genetics en masse (CombiGEM) to rapidly assemble barcoded combinatorial genetic libraries that can be tracked with high-throughput sequencing. We applied CombiGEM-CRISPR to create a library of 23,409 barcoded dual guide-RNA (gRNA) combinations and then perform a high-throughput pooled screen to identify gene pairs that inhibited ovarian cancer cell growth when they were targeted. We validated the growth-inhibiting effects of specific gene sets, including epigenetic regulators KDM4C/BRD4 and KDM6B/BRD4, via individual assays with CRISPR-Cas-based knockouts and RNA-interference-based knockdowns. We also tested small-molecule drug pairs directed against our pairwise hits and showed that they exerted synergistic antiproliferative effects against ovarian cancer cells. We envision that the CombiGEM-CRISPR platform will be applicable to a broad range of biological settings and will accelerate the systematic identification of genetic combinations and their translation into novel drug combinations that modulate complex human disease phenotypes.
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Repeticiones Palindrómicas Cortas Agrupadas y Regularmente Espaciadas , Código de Barras del ADN Taxonómico , HumanosRESUMEN
With the recent technological developments a vast amount of high-throughput data has been profiled to understand the mechanism of complex diseases. The current bioinformatics challenge is to interpret the data and underlying biology, where efficient algorithms for analyzing heterogeneous high-throughput data using biological networks are becoming increasingly valuable. In this paper, we propose a software package based on the Prize-collecting Steiner Forest graph optimization approach. The PCSF package performs fast and user-friendly network analysis of high-throughput data by mapping the data onto a biological networks such as protein-protein interaction, gene-gene interaction or any other correlation or coexpression based networks. Using the interaction networks as a template, it determines high-confidence subnetworks relevant to the data, which potentially leads to predictions of functional units. It also interactively visualizes the resulting subnetwork with functional enrichment analysis.
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Biología Computacional/métodos , Bases de Datos Factuales , Ensayos Analíticos de Alto Rendimiento/métodos , Programas InformáticosRESUMEN
High-throughput, 'omic' methods provide sensitive measures of biological responses to perturbations. However, inherent biases in high-throughput assays make it difficult to interpret experiments in which more than one type of data is collected. In this work, we introduce Omics Integrator, a software package that takes a variety of 'omic' data as input and identifies putative underlying molecular pathways. The approach applies advanced network optimization algorithms to a network of thousands of molecular interactions to find high-confidence, interpretable subnetworks that best explain the data. These subnetworks connect changes observed in gene expression, protein abundance or other global assays to proteins that may not have been measured in the screens due to inherent bias or noise in measurement. This approach reveals unannotated molecular pathways that would not be detectable by searching pathway databases. Omics Integrator also provides an elegant framework to incorporate not only positive data, but also negative evidence. Incorporating negative evidence allows Omics Integrator to avoid unexpressed genes and avoid being biased toward highly-studied hub proteins, except when they are strongly implicated by the data. The software is comprised of two individual tools, Garnet and Forest, that can be run together or independently to allow a user to perform advanced integration of multiple types of high-throughput data as well as create condition-specific subnetworks of protein interactions that best connect the observed changes in various datasets. It is available at http://fraenkel.mit.edu/omicsintegrator and on GitHub at https://github.com/fraenkel-lab/OmicsIntegrator.
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Bases de Datos Genéticas/estadística & datos numéricos , Redes Reguladoras de Genes , Secuenciación de Nucleótidos de Alto Rendimiento/estadística & datos numéricos , Programas Informáticos , Algoritmos , Biología Computacional , Epigénesis Genética , Perfilación de la Expresión Génica/estadística & datos numéricos , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/metabolismo , Mapas de Interacción de Proteínas/genética , Factores de Transcripción/metabolismoRESUMEN
The transcription factor GATA-1 is required for terminal erythroid maturation and functions as an activator or repressor depending on gene context. Yet its in vivo site selectivity and ability to distinguish between activated versus repressed genes remain incompletely understood. In this study, we performed GATA-1 ChIP-seq in erythroid cells and compared it to GATA-1-induced gene expression changes. Bound and differentially expressed genes contain a greater number of GATA-binding motifs, a higher frequency of palindromic GATA sites, and closer occupancy to the transcriptional start site versus nondifferentially expressed genes. Moreover, we show that the transcription factor Zbtb7a occupies GATA-1-bound regions of some direct GATA-1 target genes, that the presence of SCL/TAL1 helps distinguish transcriptional activation versus repression, and that polycomb repressive complex 2 (PRC2) is involved in epigenetic silencing of a subset of GATA-1-repressed genes. These data provide insights into GATA-1-mediated gene regulation in vivo.
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Cromatina/metabolismo , Factor de Transcripción GATA1/metabolismo , Genoma/genética , Proteínas Represoras/metabolismo , Activación Transcripcional/genética , Animales , Secuencia de Bases , Sitios de Unión , Biotina/metabolismo , Biotinilación , Línea Celular Tumoral , Inmunoprecipitación de Cromatina , Biología Computacional , Perfilación de la Expresión Génica , Regulación Leucémica de la Expresión Génica , Silenciador del Gen , Ratones , Modelos Genéticos , Datos de Secuencia Molecular , Proteínas del Grupo Polycomb , Unión Proteica , Secuencias Reguladoras de Ácidos Nucleicos/genética , Análisis de Secuencia de ADN , Estreptavidina/metabolismoRESUMEN
MOTIVATION: High-throughput datasets such as genetic screens, mRNA expression assays and global phospho-proteomic experiments are often difficult to interpret due to inherent noise in each experimental system. Computational tools have improved interpretation of these datasets by enabling the identification of biological processes and pathways that are most likely to explain the measured results. These tools are primarily designed to analyse data from a single experiment (e.g. drug treatment versus control), creating a need for computational algorithms that can handle heterogeneous datasets across multiple experimental conditions at once. SUMMARY: We introduce SAMNetWeb, a web-based tool that enables functional enrichment analysis and visualization of high-throughput datasets. SAMNetWeb can analyse two distinct data types (e.g. mRNA expression and global proteomics) simultaneously across multiple experimental systems to identify pathways activated in these experiments and then visualize the pathways in a single interaction network. Through the use of a multi-commodity flow based algorithm that requires each experiment 'share' underlying protein interactions, SAMNetWeb can identify distinct and common pathways across experiments. AVAILABILITY AND IMPLEMENTATION: SAMNetWeb is freely available at http://fraenkel.mit.edu/samnetweb.
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Algoritmos , Redes Reguladoras de Genes , Genómica/métodos , Proteómica/métodos , Transducción de Señal , Programas Informáticos , Biología de Sistemas/métodos , Biomarcadores de Tumor/análisis , Neoplasias de la Mama/genética , Interpretación Estadística de Datos , Femenino , Perfilación de la Expresión Génica , Humanos , Internet , Neoplasias Pulmonares/genética , ARN Mensajero/genética , Células Tumorales CultivadasRESUMEN
While Polycomb group protein Bmi1 is important for stem cell maintenance, its role in lineage commitment is largely unknown. We have identified Bmi1 as a novel regulator of erythroid development. Bmi1 is highly expressed in mouse erythroid progenitor cells and its deficiency impairs erythroid differentiation. BMI1 is also important for human erythroid development. Furthermore, we discovered that loss of Bmi1 in erythroid progenitor cells results in decreased transcription of multiple ribosomal protein genes and impaired ribosome biogenesis. Bmi1 deficiency stabilizes p53 protein, leading to upregulation of p21 expression and subsequent G0/G1 cell cycle arrest. Genetic inhibition of p53 activity rescues the erythroid defects seen in the Bmi1 null mice, demonstrating that a p53-dependent mechanism underlies the pathophysiology of the anemia. Mechanistically, Bmi1 is associated with multiple ribosomal protein genes and may positively regulate their expression in erythroid progenitor cells. Thus, Bmi1 promotes erythroid development, at least in part through regulating ribosome biogenesis. Ribosomopathies are human disorders of ribosome dysfunction, including Diamond-Blackfan anemia (DBA) and 5q- syndrome, in which genetic abnormalities cause impaired ribosome biogenesis, resulting in specific clinical phenotypes. We observed that BMI1 expression in human hematopoietic stem and progenitor cells from patients with DBA is correlated with the expression of some ribosomal protein genes, suggesting that BMI1 deficiency may play a pathological role in DBA and other ribosomopathies.
Asunto(s)
Células Eritroides/citología , Células Eritroides/metabolismo , Complejo Represivo Polycomb 1/metabolismo , Proteínas Proto-Oncogénicas/metabolismo , Ribosomas/metabolismo , Animales , Diferenciación Celular/fisiología , Eritropoyesis/fisiología , Expresión Génica , Humanos , Ratones , Ratones Endogámicos C57BL , Complejo Represivo Polycomb 1/genética , Proteínas Proto-Oncogénicas/genética , Proteínas Ribosómicas/biosíntesis , Proteínas Ribosómicas/genética , Proteínas Ribosómicas/metabolismo , Ribosomas/genéticaRESUMEN
The earliest stages of Huntington disease are marked by changes in gene expression that are caused in an indirect and poorly understood manner by polyglutamine expansions in the huntingtin (HTT) protein. To explore the hypothesis that DNA methylation may be altered in cells expressing mutated HTT, we use reduced representation bisulfite sequencing (RRBS) to map sites of DNA methylation in cells carrying either wild-type or mutant HTT. We find that a large fraction of the genes that change in expression in the presence of mutant huntingtin demonstrate significant changes in DNA methylation. Regions with low CpG content, which have previously been shown to undergo methylation changes in response to neuronal activity, are disproportionately affected. On the basis of the sequence of regions that change in methylation, we identify AP-1 and SOX2 as transcriptional regulators associated with DNA methylation changes, and we confirm these hypotheses using genome-wide chromatin immunoprecipitation sequencing (ChIP-Seq). Our findings suggest new mechanisms for the effects of polyglutamine-expanded HTT. These results also raise important questions about the potential effects of changes in DNA methylation on neurogenesis and cognitive decline in patients with Huntington disease.
Asunto(s)
Metilación de ADN , Proteínas Mutantes/genética , Proteínas del Tejido Nervioso/genética , Proteínas Nucleares/genética , Animales , Línea Celular , Inmunoprecipitación de Cromatina , Islas de CpG , Modelos Animales de Enfermedad , Expresión Génica , Humanos , Proteína Huntingtina , Enfermedad de Huntington/genética , Enfermedad de Huntington/metabolismo , Ratones , Factores de Transcripción SOXB1/metabolismo , Factor de Transcripción AP-1/metabolismoRESUMEN
SOX2 is a master regulator of both pluripotent embryonic stem cells (ESCs) and multipotent neural progenitor cells (NPCs); however, we currently lack a detailed understanding of how SOX2 controls these distinct stem cell populations. Here we show by genome-wide analysis that, while SOX2 bound to a distinct set of gene promoters in ESCs and NPCs, the majority of regions coincided with unique distal enhancer elements, important cis-acting regulators of tissue-specific gene expression programs. Notably, SOX2 bound the same consensus DNA motif in both cell types, suggesting that additional factors contribute to target specificity. We found that, similar to its association with OCT4 (Pou5f1) in ESCs, the related POU family member BRN2 (Pou3f2) co-occupied a large set of putative distal enhancers with SOX2 in NPCs. Forced expression of BRN2 in ESCs led to functional recruitment of SOX2 to a subset of NPC-specific targets and to precocious differentiation toward a neural-like state. Further analysis of the bound sequences revealed differences in the distances of SOX and POU peaks in the two cell types and identified motifs for additional transcription factors. Together, these data suggest that SOX2 controls a larger network of genes than previously anticipated through binding of distal enhancers and that transitions in POU partner factors may control tissue-specific transcriptional programs. Our findings have important implications for understanding lineage specification and somatic cell reprogramming, where SOX2, OCT4, and BRN2 have been shown to be key factors.