Global Transcriptional Regulatory Network Research Articles

A Hierarchical Transcriptional Regulatory Network Required for Long-Term Thermal Stress Tolerance in an Industrial Saccharomyces cerevisiae Strain.

Yeast cells suffer from continuous and long-term thermal stress during high-temperature ethanol fermentation. Understanding the mechanism of yeast thermotolerance is important not only for studying microbial stress biology in basic research but also for developing thermotolerant strains for industrial application. Here, we compared the effects of 23 transcription factor (TF) deletions on high-temperature ethanol fermentation and cell survival after heat shock treatment and identified three core TFs, Sin3p, Srb2p and Mig1p, that are involved in regulating the response to long-term thermotolerance. Further analyses of comparative transcriptome profiling of the core TF deletions and transcription regulatory associations revealed a hierarchical transcriptional regulatory network centered on these three TFs. This global transcriptional regulatory network provided a better understanding of the regulatory mechanism behind long-term thermal stress tolerance as well as potential targets for transcriptome engineering to improve the performance of high-temperature ethanol fermentation by an industrial Saccharomyces cerevisiae strain.

Impacts of fludioxonil resistance on global gene expression in the necrotrophic fungal plant pathogen Sclerotinia sclerotiorum

BackgroundThe fungicide fludioxonil over-stimulates the fungal response to osmotic stress, leading to over-accumulation of glycerol and hyphal swelling and bursting. Fludioxonil-resistant fungal strains that are null-mutants for osmotic stress response genes are easily generated through continual sub-culturing on sub-lethal fungicide doses. Using this approach combined with RNA sequencing, we aimed to characterise the effects of mutations in osmotic stress response genes on the transcriptional profile of the important agricultural pathogen Sclerotinia sclerotiorum under standard laboratory conditions. Our objective was to understand the impact of disruption of the osmotic stress response on the global transcriptional regulatory network in an important agricultural pathogen.ResultsWe generated two fludioxonil-resistant S. sclerotiorum strains, which exhibited growth defects and hypersensitivity to osmotic stressors. Both had missense mutations in the homologue of the Neurospora crassa osmosensing two component histidine kinase gene OS1, and one had a disruptive in-frame deletion in a non-associated gene. RNA sequencing showed that both strains together differentially expressed 269 genes relative to the parent during growth in liquid broth. Of these, 185 (69%) were differentially expressed in both strains in the same direction, indicating similar effects of the different point mutations in OS1 on the transcriptome. Among these genes were numerous transmembrane transporters and secondary metabolite biosynthetic genes.ConclusionsOur study is an initial investigation into the kinds of processes regulated through the osmotic stress pathway in S. sclerotiorum. It highlights a possible link between secondary metabolism and osmotic stress signalling, which could be followed up in future studies.

Elucidation of Regulatory Modes for Five Two-Component Systems in Escherichia coli Reveals Novel Relationships.

Escherichia coli uses two-component systems (TCSs) to respond to environmental signals. TCSs affect gene expression and are parts of E. coli's global transcriptional regulatory network (TRN). Here, we identified the regulons of five TCSs in E. coli MG1655: BaeSR and CpxAR, which were stimulated by ethanol stress; KdpDE and PhoRB, induced by limiting potassium and phosphate, respectively; and ZraSR, stimulated by zinc. We analyzed RNA-seq data using independent component analysis (ICA). ChIP-exo data were used to validate condition-specific target gene binding sites. Based on these data, we do the following: (i) identify the target genes for each TCS; (ii) show how the target genes are transcribed in response to stimulus; and (iii) reveal novel relationships between TCSs, which indicate noncognate inducers for various response regulators, such as BaeR to iron starvation, CpxR to phosphate limitation, and PhoB and ZraR to cell envelope stress. Our understanding of the TRN in E. coli is thus notably expanded.IMPORTANCE E. coli is a common commensal microbe found in the human gut microenvironment; however, some strains cause diseases like diarrhea, urinary tract infections, and meningitis. E. coli's two-component systems (TCSs) modulate target gene expression, especially related to virulence, pathogenesis, and antimicrobial peptides, in response to environmental stimuli. Thus, it is of utmost importance to understand the transcriptional regulation of TCSs to infer bacterial environmental adaptation and disease pathogenicity. Utilizing a combinatorial approach integrating RNA sequencing (RNA-seq), independent component analysis, chromatin immunoprecipitation coupled with exonuclease treatment (ChIP-exo), and data mining, we suggest five different modes of TCS transcriptional regulation. Our data further highlight noncognate inducers of TCSs, which emphasizes the cross-regulatory nature of TCSs in E. coli and suggests that TCSs may have a role beyond their cognate functionalities. In summary, these results can lead to an understanding of the metabolic capabilities of bacteria and correctly predict complex phenotype under diverse conditions, especially when further incorporated with genome-scale metabolic models.

Interferon-complement loop in transplant-associated thrombotic microangiopathy

AbstractTransplant-associated thrombotic microangiopathy (TA-TMA) is an important cause of morbidity and mortality after hematopoietic stem cell transplantation (HSCT). The complement inhibitor eculizumab improves TA-TMA, but not all patients respond to therapy, prompting a search for additional targetable pathways of endothelial injury. TA-TMA is relatively common after HSCT and can serve as a model to study mechanisms of tissue injury in other thrombotic microangiopathies. In this work, we performed transcriptome analyses of peripheral blood mononuclear cells collected before HSCT, at onset of TA-TMA, and after resolution of TA-TMA in children with and without TA-TMA after HSCT. We observed significant upregulation of the classical, alternative, and lectin complement pathways during active TA-TMA. Essentially all upregulated genes and pathways returned to baseline expression levels at resolution of TA-TMA after eculizumab therapy, supporting the clinical practice of discontinuing complement blockade after resolution of TA-TMA. Further analysis of the global transcriptional regulatory network showed a notable interferon signature associated with TA-TMA with increased STAT1 and STAT2 signaling that resolved after complement blockade. In summary, we observed activation of multiple complement pathways in TA-TMA, in contrast to atypical hemolytic uremic syndrome (aHUS), where complement activation occurs largely via the alternative pathway. Our data also suggest a key relationship between increased interferon signaling, complement activation, and TA-TMA. We propose a model of an “interferon-complement loop” that can perpetuate endothelial injury and thrombotic microangiopathy. These findings open opportunities to study novel complement blockers and combined anti-complement and anti-interferon therapies in patients with TA-TMA and other microangiopathies like aHUS and lupus-associated TMAs.

Low-Phosphate Chromatin Dynamics Predict a Cell Wall Remodeling Network in Rice Shoots.

Phosphorus (P) is an essential plant macronutrient vital to fundamental metabolic processes. Plant-available P is low in most soils, making it a frequent limiter of growth. Declining P reserves for fertilizer production exacerbates this agricultural challenge. Plants modulate complex responses to fluctuating P levels via global transcriptional regulatory networks. Although chromatin structure plays a substantial role in controlling gene expression, the chromatin dynamics involved in regulating P homeostasis have not been determined. Here we define distinct chromatin states across the rice (Oryza sativa) genome by integrating multiple chromatin marks, including the H2A.Z histone variant, H3K4me3 modification, and nucleosome positioning. In response to P starvation, 40% of all protein-coding genes exhibit a transition from one chromatin state to another at their transcription start site. Several of these transitions are enriched in subsets of genes differentially expressed under P deficiency. The most prominent subset supports the presence of a coordinated signaling network that targets cell wall structure and is regulated in part via a decrease of H3K4me3 at transcription start sites. The P starvation-induced chromatin dynamics and correlated genes identified here will aid in enhancing P use efficiency in crop plants, benefitting global agriculture.

Reconstruction of a Global Transcriptional Regulatory Network for Control of Lipid Metabolism in Yeast by Using Chromatin Immunoprecipitation with Lambda Exonuclease Digestion.

To build transcription regulatory networks, transcription factor binding must be analyzed in cells grown under different conditions because their responses and targets differ depending on environmental conditions. We performed whole-genome analysis of the DNA binding of five Saccharomyces cerevisiae transcription factors involved in lipid metabolism, Ino2, Ino4, Hap1, Oaf1, and Pip2, in response to four different environmental conditions in chemostat cultures, which allowed us to keep the specific growth rate constant. Chromatin immunoprecipitation with lambda exonuclease digestion (ChIP-exo) enabled the detection of binding events at a high resolution. We discovered a large number of unidentified targets and thus expanded functions for each transcription factor (e.g., glutamate biosynthesis as a target of Oaf1 and Pip2). Moreover, condition-dependent binding of transcription factors in response to cell metabolic state (e.g., differential binding of Ino2 between fermentative and respiratory metabolic conditions) was clearly suggested. Combining the new binding data with previously published data from transcription factor deletion studies revealed the high complexity of the transcriptional regulatory network for lipid metabolism in yeast, which involves the combinatorial and complementary regulation by multiple transcription factors. We anticipate that our work will provide insights into transcription factor binding dynamics that will prove useful for the understanding of transcription regulatory networks. IMPORTANCE Transcription factors play a crucial role in the regulation of gene expression and adaptation to different environments. To better understand the underlying roles of these adaptations, we performed experiments that give us high-resolution binding of transcription factors to their targets. We investigated five transcription factors involved in lipid metabolism in yeast, and we discovered multiple novel targets and condition-specific responses that allow us to draw a better regulatory map of the lipid metabolism.

Modulation of Global Transcriptional Regulatory Networks as a Strategy for Increasing Kanamycin Resistance of the Translational Elongation Factor-G Mutants in Escherichia coli.

Evolve and resequence experiments have provided us a tool to understand bacterial adaptation to antibiotics. In our previous work, we used short-term evolution to isolate mutants resistant to the ribosome targeting antibiotic kanamycin, and reported that Escherichia coli develops low cost resistance to kanamycin via different point mutations in the translation Elongation Factor-G (EF-G). Furthermore, we had shown that the resistance of EF-G mutants could be increased by second site mutations in the genes rpoD/cpxA/topA/cyaA. Mutations in three of these genes had been discovered in earlier screens for aminoglycoside resistance. In this work, we expand our understanding of these second site mutations, the goal being to understand how these mutations affect the activities of the mutated gene products to confer resistance. We show that the mutation in cpxA most likely results in an active Cpx stress response. Further evolution of an EF-G mutant in a higher concentration of kanamycin than what was used in our previous experiments identified the cpxA locus as a primary target for a significant increase in resistance. The mutation in cyaA results in a loss of catalytic activity and probably results in resistance via altered CRP function. Despite a reduction in cAMP levels, the CyaAN600Y mutant has a transcriptome indicative of increased CRP activity, pointing to an unknown role for CyaA and / or cAMP in gene expression. From the transcriptomes of double and single mutants, we describe the epistasis between the mutation in EF-G and these second site mutations. We show that the large scale transcriptomic changes in the topoisomerase I (FusAA608E-TopAS180L) mutant likely result from increased negative supercoiling in the cell. Finally, genes with known roles in aminoglycoside resistance were present among the misregulated genes in the mutants.

Integrated analysis reveals candidate genes and transcription factors in lung adenocarcinoma.

Lung adenocarcinoma is the most common type of non‑small cell lung cancer in Asia. Therefore, it is important to improve understanding of the underlying transcriptional regulatory mechanisms involved. The present study aimed to identify potential candidate genes and transcription factors (TFs) associated with the disease. Four gene expression profiles were downloaded from the Gene Expression Omnibus database, which included 141 lung adenocarcinoma patients and 191healthy controls. The differentially expressed genes (DEGs) were screened out and functional annotation was performed. In addition, TFs were identified and a global transcriptional regulatory network was constructed. Integrated analysis gave rise to a total of 1,238 DEGs in lung adenocarcinoma when compared with healthy tissues, including 970 upregulated and 268 downregulated DEGs. The six overexpressed outlier genes of ceruloplasmin, heparan sulfate 6‑O‑sulfotransferase 2, transmembrane protease serine4, anillin actin binding protein, cellular retinoic acid binding protein 2 and cystatin SN may serve important roles in the development of lung adenocarcinoma. In addition, the downregulation of carbonic anhydrase 4 and S100 calcium binding protein A12 may render these effective diagnostic biomarkers. The results of the transcriptional regulatory network demonstrated that the hub nodes were sex determining region Y‑box10, Spi‑B transcription factor and nuclear receptor subfamily 4 group A member 2. The four TFs, forkhead box D1, E74‑like ETS transcription factor 5, homeobox A5 and kruppel‑like factor 5, may warrant future investigations into their function in disease development. In conclusion, the present study provided for further studies a list of candidate genes and TFs for the detection and treatment of lung adenocarcinoma.

Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities.

Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the Escherichia coli TRN-probably the best characterized TRN-several questions remain. Here, we address three questions: (i) How complete is our knowledge of the E. coli TRN; (ii) how well can we predict gene expression using this TRN; and (iii) how robust is our understanding of the TRN? First, we reconstructed a high-confidence TRN (hiTRN) consisting of 147 transcription factors (TFs) regulating 1,538 transcription units (TUs) encoding 1,764 genes. The 3,797 high-confidence regulatory interactions were collected from published, validated chromatin immunoprecipitation (ChIP) data and RegulonDB. For 21 different TF knockouts, up to 63% of the differentially expressed genes in the hiTRN were traced to the knocked-out TF through regulatory cascades. Second, we trained supervised machine learning algorithms to predict the expression of 1,364 TUs given TF activities using 441 samples. The algorithms accurately predicted condition-specific expression for 86% (1,174 of 1,364) of the TUs, while 193 TUs (14%) were predicted better than random TRNs. Third, we identified 10 regulatory modules whose definitions were robust against changes to the TRN or expression compendium. Using surrogate variable analysis, we also identified three unmodeled factors that systematically influenced gene expression. Our computational workflow comprehensively characterizes the predictive capabilities and systems-level functions of an organism's TRN from disparate data types.

Identification of transcription factors (TFs) and targets involved in the cholangiocarcinoma (CCA) by integrated analysis.

The present study was designed to investigate the upstream transcription factors (TFs) and the signature genes in cholangiocarcinoma (CCA), providing better clues on the regulatory mechanisms and therapeutic applications. Gene expression data sets of CCA were searched in the Gene Expression Omnibus database for integrated analysis. Functional annotation of differently expressed genes (DEGs) was then conducted and the TFs were identified. Moreover, a global transcriptional regulatory network of TFs-targets was constructed. Integrated analysis of five eligible Gene Expression Omnibus data sets led to a set of 993 DEGs and 48 TFs in CCA. The constructed TFs-targets regulatory network consisted of 697 TF-target interactions between 41 TFs and 436 DEGs. The top 10 TFs covering the most downstream DEGs were NFATC2, SOX10, ARID3A, ZNF263, NR4A2, GATA3, EGR1, PLAG1, STAT3 and FOSL1, which may have important roles in the tumorigenesis of CCA. Supporting the fact that defects of cell-cycle surveillance mechanism were closely related to various cancers, we found that cell cycle was the most significantly enriched pathway. KCNN2 and ADCY6 were involved in the bile secretion. Thus, their aberrant expression may be closely related to the pathogenesis of CCA. Particularly, we found that upregulation of EZH2 in CCA is a powerful potential marker for CCA.

Zeb2 Regulates Cell Fate at the Exit from Epiblast State in Mouse Embryonic Stem Cells.

In human embryonic stem cells (ESCs) the transcription factor Zeb2 regulates neuroectoderm versus mesendoderm formation, but it is unclear how Zeb2 affects the global transcriptional regulatory network in these cell‐fate decisions. We generated Zeb2 knockout (KO) mouse ESCs, subjected them as embryoid bodies (EBs) to neural and general differentiation and carried out temporal RNA‐sequencing (RNA‐seq) and reduced representation bisulfite sequencing (RRBS) analysis in neural differentiation. This shows that Zeb2 acts preferentially as a transcriptional repressor associated with developmental progression and that Zeb2 KO ESCs can exit from their naïve state. However, most cells in these EBs stall in an early epiblast‐like state and are impaired in both neural and mesendodermal differentiation. Genes involved in pluripotency, epithelial‐to‐mesenchymal transition (EMT), and DNA‐(de)methylation, including Tet1, are deregulated in the absence of Zeb2. The observed elevated Tet1 levels in the mutant cells and the knowledge of previously mapped Tet1‐binding sites correlate with loss‐of‐methylation in neural‐stimulating conditions, however, after the cells initially acquired the correct DNA‐methyl marks. Interestingly, cells from such Zeb2 KO EBs maintain the ability to re‐adapt to 2i + LIF conditions even after prolonged differentiation, while knockdown of Tet1 partially rescues their impaired differentiation. Hence, in addition to its role in EMT, Zeb2 is critical in ESCs for exit from the epiblast state, and links the pluripotency network and DNA‐methylation with irreversible commitment to differentiation. Stem Cells 2017;35:611–625

Identification of upstream transcription factors (TFs) for expression signature genes in breast cancer

Breast cancer is a common malignancy among women with a rising incidence. Our intention was to detect transcription factors (TFs) for deeper understanding of the underlying mechanisms of breast cancer. Integrated analysis of gene expression datasets of breast cancer was performed. Then, functional annotation of differentially expressed genes (DEGs) was conducted, including Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, TFs were identified and a global transcriptional regulatory network was constructed. Seven publically available GEO datasets were obtained, and a set of 1196 DEGs were identified (460 up-regulated and 736 down-regulated). Functional annotation results showed that cell cycle was the most significantly enriched pathway, which was consistent with the fact that cell cycle is closely related to various tumors. Fifty-three differentially expressed TFs were identified, and the regulatory networks consisted of 817 TF-target interactions between 46 TFs and 602 DEGs in the context of breast cancer. Top 10 TFs covering the most downstream DEGs were SOX10, NFATC2, ZNF354C, ARID3A, BRCA1, FOXO3, GATA3, ZEB1, HOXA5 and EGR1. The transcriptional regulatory networks could enable a better understanding of regulatory mechanisms of breast cancer pathology and provide an opportunity for the development of potential therapy.

Integrative Analysis of Microarray Data to Reveal Regulation Patterns in the Pathogenesis of Hepatocellular Carcinoma.

Background/AimsThe integration of multiple profiling data and the construction of a transcriptional regulatory network may provide additional insights into the molecular mechanisms of hepatocellular carcinoma (HCC). The present study was conducted to investigate the deregulation of genes and the transcriptional regulatory network in HCC.MethodsAn integrated analysis of HCC gene expression datasets was performed in Gene Expression Omnibus. Functional annotation of the differentially expression genes (DEGs) was conducted. Furthermore, transcription factors (TFs) were identified, and a global transcriptional regulatory network was constructed.ResultsAn integrated analysis of eight eligible gene expression profiles of HCC led to 1,835 DEGs. Consistent with the fact that the cell cycle is closely related to various tumors, the functional annotation revealed that genes involved in the cell cycle were significantly enriched. A transcriptional regulatory network was constructed using the 62 TFs, which consisted of 872 TF-target interactions between 56 TFs and 672 DEGs in the context of HCC. The top 10 TFs covering the most downstream DEGs were ZNF354C, NFATC2, ARID3A, BRCA1, ZNF263, FOXD1, GATA3, FOXO3, FOXL1, and NR4A2. This network will appeal to future investigators focusing on the development of HCC.ConclusionsThe transcriptional regulatory network can provide additional information that is valuable in understanding the underlying molecular mechanism in hepatic tumorigenesis.

Identification of upstream regulators for synovial expression signature genes in osteoarthritis

ObjectivesThe detection of transcription factors (TFs) for OA signature genes provides better clues to the underlying regulatory mechanisms and therapeutic applications. MethodsWe searched GEO database for synovial expression profiling from different OA microarray studies to perform a systematic analysis. Functional annotation of DEGs was conducted, including gene ontology (GO) enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. Based on motif databases and the results from integrated analysis of current gene expression data, a global transcriptional regulatory network was constructed, and the upstream TFs were identified for OA signature genes. ResultsSix GEO datasets were obtained. Totally, 805 genes across the studies were consistently differentially expressed in OA (469 up-regulated and 336 down-regulated genes) with FDR⿤0.01. Supporting an involvement of ECM in the development of OA, we showed that ECM-receptor interaction was the most significant pathway in our KEGG analysis (P=5.92E-12). Sixty-one differentially expressed TFs were identified with FDR⿤0.05. The constructed OA-specific regulatory networks consisted of 648 TF-target interactions between 51 TFs and 429 DEGs in the context of OA. The top 10 TFs covering the most downstream DEGs were identified as crucial TFs involved in the development of OA, including ARID3A, NFIC, ZNF354C, NR4A2, BRCA1, EHF, FOXL1, FOXC1, EGR1, and HOXA5. ConclusionThis integrated analysis has identified the OA signature, providing clues to pathogenesis of OA at the molecular level, which may be also used as diagnostic markers for OA. Some crucial upstream regulators, such as NR4A2, EHF, and EGR1 may be considered as potential new therapeutic targets for OA.

Screening Driving Transcription Factors in the Processing of Gastric Cancer.

Background. Construction of the transcriptional regulatory network can provide additional clues on the regulatory mechanisms and therapeutic applications in gastric cancer. Methods. Gene expression profiles of gastric cancer were downloaded from GEO database for integrated analysis. All of DEGs were analyzed by GO enrichment and KEGG pathway enrichment. Transcription factors were further identified and then a global transcriptional regulatory network was constructed. Results. By integrated analysis of the six eligible datasets (340 cases and 43 controls), a bunch of 2327 DEGs were identified, including 2100 upregulated and 227 downregulated DEGs. Functional enrichment analysis of DEGs showed that digestion was a significantly enriched GO term for biological process. Moreover, there were two important enriched KEGG pathways: cell cycle and homologous recombination. Furthermore, a total of 70 differentially expressed TFs were identified and the transcriptional regulatory network was constructed, which consisted of 566 TF-target interactions. The top ten TFs regulating most downstream target genes were BRCA1, ARID3A, EHF, SOX10, ZNF263, FOXL1, FEV, GATA3, FOXC1, and FOXD1. Most of them were involved in the carcinogenesis of gastric cancer. Conclusion. The transcriptional regulatory network can help researchers to further clarify the underlying regulatory mechanisms of gastric cancer tumorigenesis.

An experimentally supported model of the Bacillus subtilis global transcriptional regulatory network.

Organisms from all domains of life use gene regulation networks to control cell growth, identity, function, and responses to environmental challenges. Although accurate global regulatory models would provide critical evolutionary and functional insights, they remain incomplete, even for the best studied organisms. Efforts to build comprehensive networks are confounded by challenges including network scale, degree of connectivity, complexity of organism-environment interactions, and difficulty of estimating the activity of regulatory factors. Taking advantage of the large number of known regulatory interactions in Bacillus subtilis and two transcriptomics datasets (including one with 38 separate experiments collected specifically for this study), we use a new combination of network component analysis and model selection to simultaneously estimate transcription factor activities and learn a substantially expanded transcriptional regulatory network for this bacterium. In total, we predict 2,258 novel regulatory interactions and recall 74% of the previously known interactions. We obtained experimental support for 391 (out of 635 evaluated) novel regulatory edges (62% accuracy), thus significantly increasing our understanding of various cell processes, such as spore formation.

The histone H3 lysine-27 demethylase Jmjd3 plays a critical role in specific regulation of Th17 cell differentiation.

Interleukin (IL) 17-producing T helper (Th17) cells play critical roles in the clearance of extracellular bacteria and fungi as well as the pathogenesis of various autoimmune diseases, such as multiple sclerosis, psoriasis, and ulcerative colitis. Although a global transcriptional regulatory network of Th17 cell differentiation has been mapped recently, the participation of epigenetic modifications in the differentiation process has yet to be elucidated. We demonstrated here that histone H3 lysine-27 (H3K27) demethylation, predominantly mediated by the H3K27 demethylase Jmjd3, crucially regulated Th17 cell differentiation. Activation of naïve CD4(+) T cells immediately induced high expression of Jmjd3. Genetic depletion of Jmjd3 in CD4(+) T cells specifically impaired Th17 cell differentiation both in vitro and in vivo. Ectopic expression of Jmjd3 largely rescued the impaired differentiation of Th17 cells in vitro in Jmjd3-deficient CD4(+) T cells. Importantly, Jmjd3-deficient mice were resistant to the induction of experimental autoimmune encephalomyelitis (EAE). Furthermore, inhibition of the H3K27 demethylase activity with the specific inhibitor GSK-J4 dramatically suppressed Th17 cell differentiation in vitro. At the molecular level, Jmjd3 directly bound to and reduced the level of H3K27 trimethylation (me3) at the genomic sites of Rorc, which encodes the master Th17 transcription factor Rorγt, and Th17 cytokine genes such as Il17, Il17f, and Il22. Therefore, our studies established a critical role of Jmjd3-mediated H3K27 demethylation in Th17 cell differentiation and suggest that Jmjd3 can be a novel therapeutic target for suppressing autoimmune responses.

Identifying candidate drivers of alcohol dependence-induced excessive drinking by assembly and interrogation of brain-specific regulatory networks.

BackgroundA systems biology approach based on the assembly and interrogation of gene regulatory networks, or interactomes, was used to study neuroadaptation processes associated with the transition to alcohol dependence at the molecular level.ResultsUsing a rat model of dependent and non-dependent alcohol self-administration, we reverse engineered a global transcriptional regulatory network during protracted abstinence, a period when relapse rates are highest. We then interrogated the network to identify master regulator genes that mechanistically regulate brain region-specific signatures associated with dependent and non-dependent alcohol self-administration. Among these, the gene coding for the glucocorticoid receptor was independently identified as a master regulator in multiple brain regions, including the medial prefrontal cortex, nucleus accumbens, central nucleus of the amygdala, and ventral tegmental area, consistent with the view that brain reward and stress systems are dysregulated during protracted abstinence. Administration of the glucocorticoid antagonist mifepristone in either the nucleus accumbens or ventral tegmental area selectively decreased dependent, excessive, alcohol self-administration in rats but had no effect on non-dependent, moderate, alcohol self-administration.ConclusionsOur study suggests that assembly and analysis of regulatory networks is an effective strategy for the identification of key regulators of long-term neuroplastic changes within specific brain regions that play a functional role in alcohol dependence. More specifically, our results support a key role for regulatory networks downstream of the glucocorticoid receptor in excessive alcohol drinking during protracted alcohol abstinence.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0593-5) contains supplementary material, which is available to authorized users.

Enterococcus faecalis reconfigures its transcriptional regulatory network activation at different copper levels

A global transcriptional regulatory network was generated in the pathogenic bacterium Enterococcus faecalis in order to understand how this organism can activate and coordinate its expression at different copper concentrations. The topological evaluation of the network showed common patterns described in other organisms. Integrating microarray experiments allowed the identification of two sub-networks activated at low (0.05 mM CuSO4) and high (0.5 mM CuSO4) concentrations of copper. The analysis indicates the presence of specific functionally activated modules induced by copper levels, highlighting the regulons LysR and ArgR as global regulators and CopY, Fur and LexA as local regulators. Taking advantage of the fact that E. faecalis presented a homeostatic module, we produced an in vivo intervention by removing this system from the cell without affecting the connectivity of the global transcriptional network. This strategy led us to find that this bacterium can reconfigure its gene expression to maintain cellular homeostasis, activating new modules principally related to glucose metabolism and transcriptional processes. Finally, these results position E. faecalis as the most complete and controllable systemic model organism for copper homeostasis available to date.

Identification of upstream regulators for prognostic expression signature genes in colorectal cancer

BackgroundGene expression signatures have been commonly used as diagnostic and prognostic markers for cancer subtyping. However, expression signatures frequently include many passengers, which are not directly related to cancer progression. Their upstream regulators such as transcription factors (TFs) may take a more critical role as drivers or master regulators to provide better clues on the underlying regulatory mechanisms and therapeutic applications.ResultsIn order to identify prognostic master regulators, we took the known 85 prognostic signature genes for colorectal cancer and inferred their upstream TFs. To this end, a global transcriptional regulatory network was constructed with total >200,000 TF-target links using the ARACNE algorithm. We selected the top 10 TFs as candidate master regulators to show the highest coverage of the signature genes among the total 846 TF-target sub-networks or regulons. The selected TFs showed a comparable or slightly better prognostic performance than the original 85 signature genes in spite of greatly reduced number of marker genes from 85 to 10. Notably, these TFs were selected solely from inferred regulatory links using gene expression profiles and included many TFs regulating tumorigenic processes such as proliferation, metastasis, and differentiation.ConclusionsOur network approach leads to the identification of the upstream transcription factors for prognostic signature genes to provide leads to their regulatory mechanisms. We demonstrate that our approach could identify upstream biomarkers for a given set of signature genes with markedly smaller size and comparable performances. The utility of our method may be expandable to other types of signatures such as diagnosis and drug response.