Insights into the identification and evolutionary conservation of key genes in the transcriptional circuits of meiosis initiation and commitment in budding yeast

Initiation of meiosis in budding yeast does not commit the cells for meiosis. Thus, two distinct signaling cascades may differentially regulate meiosis initiation and commitment in budding yeast. To distinguish between the role of these signaling cascades, we reconstructed protein-protein interaction networks and gene regulatory networks with upregulated genes in meiosis initiation and commitment. Analyzing the integrated networks, we identified four master regulators (MRs) [Ume6p, Msn2p, Met31p, Ino2p], three transcription factors (TFs), and 279 target genes (TGs) unique for meiosis initiation, and three MRs [Ndt80p, Aro80p, Rds2p], 11 TFs, and 948 TGs unique for meiosis commitment. Functional enrichment analysis of these distinct members from the transcriptional cascades for meiosis initiation and commitment revealed that nutritional cues rewire gene expression for initiating meiosis and chromosomal recombination commits cells to meiosis. As meiotic chromosomal recombination is highly conserved in eukaryotes, we compared the evolutionary rate of unique members in the transcriptional cascade of two meiotic phases of Saccharomyces cerevisiae with members of the phylum Ascomycota, revealing that the transcriptional cascade governing chromosomal recombination during meiosis commitment has experienced greater purifying selection pressure (P value = 0.0013, 0.0382, 0.0448, 0.0369, 0.02967, 0.04937, 0.03046, 0.03357 and < 0.00001 for Ashbya gossypii, Yarrowia lipolytica, Debaryomyces hansenii, Aspergillus fumigatus, Neurospora crassa, Kluyveromyces lactis, Schizosaccharomyces pombe, Schizosaccharomyces cryophilus, and Schizosaccharomyces octosporus, respectively). This study demarcates crucial players driving meiosis initiation and commitment and demonstrates their differential rate of evolution in budding yeast.

Transcriptome profiling of the Caenorhabditis elegans intestine reveals that ELT-2 negatively and positively regulates intestinal gene expression within the context of a gene regulatory network

ELT-2 is the major transcription factor (TF) required for Caenorhabditis elegans intestinal development. ELT-2 expression initiates in embryos to promote development and then persists after hatching through the larval and adult stages. Though the sites of ELT-2 binding are characterized and the transcriptional changes that result from ELT-2 depletion are known, an intestine-specific transcriptome profile spanning developmental time has been missing. We generated this dataset by performing Fluorescence Activated Cell Sorting on intestine cells at distinct developmental stages. We analyzed this dataset in conjunction with previously conducted ELT-2 studies to evaluate the role of ELT-2 in directing the intestinal gene regulatory network through development. We found that only 33% of intestine-enriched genes in the embryo were direct targets of ELT-2 but that number increased to 75% by the L3 stage. This suggests additional TFs promote intestinal transcription especially in the embryo. Furthermore, only half of ELT-2's direct target genes were dependent on ELT-2 for their proper expression levels, and an equal proportion of those responded to elt-2 depletion with over-expression as with under-expression. That is, ELT-2 can either activate or repress direct target genes. Additionally, we observed that ELT-2 repressed its own promoter, implicating new models for its autoregulation. Together, our results illustrate that ELT-2 impacts roughly 20-50% of intestine-specific genes, that ELT-2 both positively and negatively controls its direct targets, and that the current model of the intestinal regulatory network is incomplete as the factors responsible for directing the expression of many intestinal genes remain unknown.

A variegated model of transcription factor function in the immune system

Specific combinations of transcription factors (TFs) control the gene expression programs that underlie specialized immune responses. Previous models of TF function in immunocytes had restricted each TF to a single functional categorization [e.g., lineage-defining (LDTFs) vs. signal-dependent TFs (SDTFs)] within one cell type. Synthesizing recent results, we instead propose a variegated model of immunological TF function, whereby many TFs have flexible and different roles across distinct cell states, contributing to cell phenotypic diversity. We discuss evidence in support of this variegated model, describe contextual inputs that enable TF diversification, and look to the future to imagine warranted experimental and computational tools to build quantitative and predictive models of immunocyte gene regulatory networks.

Gene Regulatory Network Characterization of Gastric Cancer's Histological Subtypes: Distinctive Biological and Clinically Relevant Master Regulators

Gastric cancer (GC) molecular heterogeneity represents a major determinant for clinical outcomes, and although new molecular classifications have been introduced, they are not easy to translate from bench to bedside. We explored the data from GC public databases by performing differential gene expression analysis (DEGs) and gene network reconstruction to identify master regulators (MRs), as well as a gene set analysis (GSA) to reveal their biological features. Moreover, we evaluated the association of MRs with clinicopathological parameters. According to the GSA, the Diffuse group was characterized by an epithelial-mesenchymal transition (EMT) and inflammatory response, while the Intestinal group was associated with a cell cycle and drug resistance pathways. In particular, the regulons of Diffuse MRs, such as Vgll3 and Ciita, overlapped with the EMT and interferon-gamma response, while the regulons Top2a and Foxm1 were shared with the cell cycle pathways in the Intestinal group. We also found a strict association between MR activity and several clinicopathological features, such as survival. Our approach led to the identification of genes and pathways differentially regulated in the Intestinal and Diffuse GC histotypes, highlighting biologically interesting MRs and subnetworks associated with clinical features and prognosis, suggesting putative actionable candidates.

Orchestrated Biosynthesis of the Secondary Metabolite Cocktails Enables the Producing Fungus to Combat Diverse Bacteria

Fungal secondary metabolites with antibiotic activities can promote fungal adaptation to diverse environments. Besides the global regulator, individual biosynthetic gene clusters (BGCs) usually contain a pathway-specific transcription factor for the tight regulation of fungal secondary metabolism. Here, we report the chemical biology mediated by a supercluster containing three BGCs in the entomopathogenic fungus Metarhiziumrobertsii. These clusters are jointly controlled by an embedded transcription factor that orchestrates the collective production of four classes of chemicals: ustilaginoidin, indigotide, pseurotin, and hydroxyl-ovalicin. The ustilaginoidin BGC is implicated as a late-acquired cluster in Metarhizium to produce both the bis-naphtho-γ-pyrones and the monomeric naphtho-γ-pyrone glycosides (i.e., indigotides). We found that the biosynthesis of indigotides additionally requires the functions of paired methylglucosylation genes located outside the supercluster. The pseurotin/ovalicin BGCs are blended and mesosyntenically conserved to the intertwined pseurotin/fumagillin BGCs of Aspergillus fumigatus. However, the former have lost a few genes, including a polyketide synthase gene responsible for the production of a pentaene chain used for assembly with ovalicin to form fumagillin, as observed in A. fumigatus. The collective production of chemical cocktails by this supercluster was dispensable for fungal virulence against insects and could enable the fungus to combat different bacteria better than the metabolite(s) produced by an individual BGC could. Thus, our results unveil a novel strategy employed by fungi to manage chemical ecology against diverse bacteria.

scInTime: A Computational Method Leveraging Single-Cell Trajectory and Gene Regulatory Networks to Identify Master Regulators of Cellular Differentiation

Trajectory inference (TI) or pseudotime analysis has dramatically extended the analytical framework of single-cell RNA-seq data, allowing regulatory genes contributing to cell differentiation and those involved in various dynamic cellular processes to be identified. However, most TI analysis procedures deal with individual genes independently while overlooking the regulatory relations between genes. Integrating information from gene regulatory networks (GRNs) at different pseudotime points may lead to more interpretable TI results. To this end, we introduce scInTime—an unsupervised machine learning framework coupling inferred trajectory with single-cell GRNs (scGRNs) to identify master regulatory genes. We validated the performance of our method by analyzing multiple scRNA-seq data sets. In each of the cases, top-ranking genes predicted by scInTime supported their functional relevance with corresponding signaling pathways, in line with the results of available functional studies. Overall results demonstrated that scInTime is a powerful tool to exploit pseudotime-series scGRNs, allowing for a clear interpretation of TI results toward more significant biological insights.

Analyzing master regulators and scRNA-seq of COVID-19 patients reveals an underlying anti-SARS-CoV-2 mechanism of ZNF proteins

Studies have demonstrated that both mortality and severe illness rates exist significant difference in different gender COVID-19 patients, but the reasons are still very mysterious to date. Here, we firstly find that the survival outcome of female patients is better to male patients through analyzing the 3044 COVID-19 cases. Secondly, we identify many important master regulators [e.g. STAT1/STAT2 and zinc finger (ZNF) proteins], in particular female patients can express more ZNF proteins and stronger transcriptional activities than male patients in response to SARS-CoV-2 infection. Thirdly, we discover that ZNF protein activity is significantly negative correlation with the SARS-CoV-2 load of COVID-19 patients, and ZNF proteins as transcription factors can also activate their target genes to participate in anti-SARS-CoV-2 infection. Fourthly, we demonstrate that ZNF protein activity is positive correlation with the abundance of multiple immune cells of COVID-19 patients, implying that the highly ZNF protein activity might promote the abundance and the antiviral activity of multiple immune cells to effectively suppress SARS-CoV-2 infection. Taken together, our study proposes an underlying anti-SARS-COV-2 role of ZNF proteins, and differences in the amount and activity of ZNF proteins might be responsible for the distinct prognosis of different gender COVID-19 patients.

Predicting FOXM1-Mediated Gene Regulation through the Analysis of Genome-Wide FOXM1 Binding Sites in MCF-7, K562, SK-N-SH, GM12878 and ECC-1 Cell Lines

Forkhead box protein M1 (FOXM1) is a key transcription factor (TF) that regulates a common set of genes related to the cell cycle in various cell types. However, the mechanism by which FOXM1 controls the common gene set in different cellular contexts is unclear. In this study, a comprehensive meta-analysis of genome-wide FOXM1 binding sites in ECC-1, GM12878, K562, MCF-7, and SK-N-SH cell lines was conducted to predict FOXM1-driven gene regulation. Consistent with previous studies, different TF binding motifs were identified at FOXM1 binding sites, while the NFY binding motif was found at 81% of common FOXM1 binding sites in promoters of cell cycle-related genes. The results indicated that FOXM1 might control the gene set through interaction with the NFY proteins, while cell type-specific genes were predicted to be regulated by enhancers with FOXM1 and cell type-specific TFs. We also found that the high expression level of FOXM1 was significantly associated with poor prognosis in nine types of cancer. Overall, these results suggest that FOXM1 is predicted to function as a master regulator of the cell cycle through the interaction of NFY-family proteins, and therefore the inhibition of FOXM1 could be an attractive strategy for cancer therapy.

Network study of nasal transcriptome profiles reveals master regulator genes of asthma

BACKGROUND

Nasal transcriptomics can provide an accessible window into asthma pathobiology.

OBJECTIVE

Our goal was to move beyond gene signatures of asthma to identify master regulator genes that causally regulate genes associated with asthma phenotypes.

METHODS

We recruited 156 children with severe persistent asthma and controls for nasal transcriptome profiling and applied network-based and probabilistic causal methods to identify severe asthma genes and their master regulators. We then took the same approach in an independent cohort of 190 adults with mild/moderate asthma and controls to identify mild/moderate asthma genes and their master regulators. Comparative analysis of the master regulator genes followed by validation testing in independent children with severe asthma (n = 21) and mild/moderate asthma (n = 154) was then performed.

RESULTS

Nasal gene signatures for severe persistent asthma and for mild/moderate persistent asthma were identified; both were found to be enriched in coexpression network modules for ciliary function and inflammatory response. By applying probabilistic causal methods to these gene signatures and validation testing in independent cohorts, we identified (1) a master regulator gene common to asthma across severity and ages (FOXJ1); (2) master regulator genes of severe persistent asthma in children (LRRC23, TMEM231, CAPS, PTPRC, and FYB); and (3) master regulator genes of mild/moderate persistent asthma in children and adults (C1orf38 and FMNL1). The identified master regulators were statistically inferred to causally regulate the expression of downstream genes that modulate ciliary function and inflammatory response to influence asthma.

CONCLUSION

The identified master regulator genes of asthma provide a novel path forward to further uncovering asthma mechanisms and therapy.

Identification of miRNA Master Regulators in Breast Cancer

Breast cancer is the neoplasm with the highest number of deaths in women. Although the molecular mechanisms associated with the development of this tumor have been widely described, metastatic disease has a high mortality rate. In recent years, several studies show that microRNAs or miRNAs regulate complex processes in different biological systems including cancer. In the present work, we describe a group of 61 miRNAs consistently over-expressed in breast cancer (BC) samples that regulate the breast cancer transcriptome. By means of data mining from TCGA, miRNA and mRNA sequencing data corresponding to 1091 BC patients and 110 normal adjacent tissues were downloaded and a miRNA-mRNA network was inferred. Calculations of their oncogenic activity demonstrated that they were involved in the regulation of classical cancer pathways such as cell cycle, PI3K-AKT, DNA repair, and k-Ras signaling. Using univariate and multivariate analysis, we found that five of these miRNAs could be used as biomarkers for the prognosis of overall survival. Furthermore, we confirmed the over-expression of two of them in 56 locally advanced BC samples obtained from the histopathological archive of the National Cancer Institute of Mexico, showing concordance with our previous bioinformatic analysis.

Identification of a Master Regulator of Differentiation in Toxoplasma

Toxoplasma gondii chronically infects a quarter of the world's population, and its recrudescence can cause life-threatening disease in immunocompromised individuals and recurrent ocular lesions in the immunocompetent. Acute-stage tachyzoites differentiate into chronic-stage bradyzoites, which form intracellular cysts resistant to immune clearance and existing therapies. The molecular basis of this differentiation is unknown, despite being efficiently triggered by stresses in culture. Through Cas9-mediated screening and single-cell profiling, we identify a Myb-like transcription factor (BFD1) necessary for differentiation in cell culture and in mice. BFD1 accumulates during stress and its synthetic expression is sufficient to drive differentiation. Consistent with its function as a transcription factor, BFD1 binds the promoters of many stage-specific genes and represents a counterpoint to the ApiAP2 factors that dominate our current view of parasite gene regulation. BFD1 provides a genetic switch to study and control Toxoplasma differentiation and will inform prevention and treatment of chronic infections.

A Transcriptional Network Promotes Anthocyanin Biosynthesis in Tomato Flesh

Dietary anthocyanins are important health-promoting antioxidants that make a major contribution to the quality of fruits. It is intriguing that most tomato cultivars do not produce anthocyanins in fruit. However, the purple tomato variety Indigo Rose, which has the dominant Aft locus combined with the recessive atv locus from wild tomato species, exhibits light-dependent anthocyanin accumulation in the fruit skin. Here, we report that Aft encodes a functional anthocyanin activator named SlAN2-like, while atv encodes a nonfunctional version of the anthocyanin repressor SlMYBATV. The expression of SlAN2-like is responsive to light, and the functional SlAN2-like can activate the expression of both anthocyanin biosynthetic genes and their regulatory genes, suggesting that SlAN2-like acts as a master regulator in the activation of anthocyanin biosynthesis. We further showed that cultivated tomatoes contain nonfunctional alleles of SlAN2-like and therefore fail to produce anthocyanins. Consistently, expression of a functional SlAN2-like gene driven by the fruit-specific promoter in a tomato cultivar led to the activation of the entire anthocyanin biosynthesis pathway and high-level accumulation of anthocyanins in both the peel and flesh. Taken together, our study exemplifies that efficient engineering of complex metabolic pathways could be achieved through tissue-specific expression of master transcriptional regulators.

Discovering master regulators in hepatocellular carcinoma: one novel MR, SEC14L2 inhibits cancer cells

Identification of master regulator (MR) genes offers a relatively rapid and efficient way to characterize disease-specific molecular programs. Since strong consensus regarding commonly altered MRs in hepatocellular carcinoma (HCC) is lacking, we generated a compendium of HCC datasets from 21 studies and identified a comprehensive signature consisting of 483 genes commonly deregulated in HCC. We then used reverse engineering of transcriptional networks to identify the MRs that underpin the development and progression of HCC. After cross-validation in different HCC datasets, systematic assessment using patient-derived data confirmed prognostic predictive capacities for most HCC MRs and their corresponding regulons. Our HCC signature covered well-established liver cancer hallmarks, and network analyses revealed coordinated interaction between several MRs. One novel MR, SEC14L2, exerted an anti-proliferative effect in HCC cells and strongly suppressed tumor growth in a mouse model. This study advances our knowledge of transcriptional MRs potentially involved in HCC development and progression that may be targeted by specific interventions.

TP63-Mediated Enhancer Reprogramming Drives the Squamous Subtype of Pancreatic Ductal Adenocarcinoma

The aberrant expression of squamous lineage markers in pancreatic ductal adenocarcinoma (PDA) has been correlated with poor clinical outcomes. However, the functional role of this putative transdifferentiation event in PDA pathogenesis remains unclear. Here, we show that expression of the transcription factor TP63 (∆Np63) is sufficient to install and sustain the enhancer landscape and transcriptional signature of the squamous lineage in human PDA cells. We also demonstrate that TP63-driven enhancer reprogramming promotes aggressive tumor phenotypes, including enhanced cell motility and invasion, and an accelerated growth of primary PDA tumors and metastases in vivo. This process ultimately leads to a powerful addiction of squamous PDA cells to continuous TP63 expression. Our study demonstrates the functional significance of squamous transdifferentiation in PDA and reveals TP63-based reprogramming as an experimental tool for investigating mechanisms and vulnerabilities linked to this aberrant cell fate transition.

Somerville et al. report that the transcription factor TP63 is a master regulator of squamous-subtype pancreatic cancer as it reprograms the enhancer landscape to drive squamous transdifferentiation, promoting invasion, migration, in vivo tumor growth, and poor prognosis.

Master Regulators of Signaling Pathways: An Application to the Analysis of Gene Regulation in Breast Cancer

Analysis of gene regulatory networks allows the identification of master transcriptional factors that control specific groups of genes. In this work, we inferred a gene regulatory network from a large dataset of breast cancer samples to identify the master transcriptional factors that control the genes within signal transduction pathways. The focus in a particular subset of relevant genes constitutes an extension of the original Master Regulator Inference Algorithm (MARINa) analysis. This modified version of MARINa utilizes a restricted molecular signature containing genes from the 25 human pathways in KEGG's signal transduction category. Our breast cancer RNAseq expression dataset consists of 881 samples comprising tumors and normal mammary gland tissue. The top 10 master transcriptional factors found to regulate signal transduction pathways in breast cancer we identified are: TSHZ2, HOXA2, MEIS2, HOXA3, HAND2, HOXA5, TBX18, PEG3, GLI2, and CLOCK. The functional enrichment of the regulons of these master transcriptional factors showed an important proportion of processes related to morphogenesis. Our results suggest that, as part of the aberrant regulation of signaling pathways in breast cancer, pathways similar to the regulation of cell differentiation, cardiovascular system development, and vasculature development may be dysregulated and co-opted in favor of tumor development through the action of these transcription factors.

Integrated transcriptomics reveals master regulators of lung adenocarcinoma and novel repositioning of drug candidates

BACKGROUND

Lung adenocarcinoma is the major cause of cancer-related deaths in the world. Given this, the importance of research on its pathophysiology and therapy remains a key health issue. To assist in this endeavor, recent oncology studies are adopting Systems Biology approaches and bioinformatics to analyze and understand omics data, bringing new insights about this disease and its treatment.

METHODS

We used reverse engineering of transcriptomic data to reconstruct nontumorous lung reference networks, focusing on transcription factors (TFs) and their inferred target genes, referred as regulatory units or regulons. Afterwards, we used 13 case-control studies to identify TFs acting as master regulators of the disease and their regulatory units. Furthermore, the inferred activation patterns of regulons were used to evaluate patient survival and search drug candidates for repositioning.

RESULTS

The regulatory units under the influence of ATOH8, DACH1, EPAS1, ETV5, FOXA2, FOXM1, HOXA4, SMAD6, and UHRF1 transcription factors were consistently associated with the pathological phenotype, suggesting that they may be master regulators of lung adenocarcinoma. We also observed that the inferred activity of FOXA2, FOXM1, and UHRF1 was significantly associated with risk of death in patients. Finally, we obtained deptropine, promazine, valproic acid, azacyclonol, methotrexate, and ChemBridge ID compound 5109870 as potential candidates to revert the molecular profile leading to decreased survival.

CONCLUSION

Using an integrated transcriptomics approach, we identified master regulator candidates involved with the development and prognostic of lung adenocarcinoma, as well as potential drugs for repurposing.

Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers

Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes—modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility.

Identifying a missing lineage driver in a subset of lung neuroendocrine tumors

Tumor heterogeneity of a primary histologic cancer type has major implications for cancer research and therapeutics. An important and understudied aspect of this heterogeneity is the role of transcription factors that serve as "lineage oncogenes" in a tumor type. A demonstration that different subgroups have distinct dependencies on lineage-specific transcription factors is highlighted in a relatively homogenous cancer type: the pulmonary neuroendocrine cancer small cell lung carcinoma (SCLC). Identification of these factors is providing new insights into the origin of the heterogeneity and subtype-specific vulnerabilities in SCLC and provides a template for studying heterogeneity in other cancer types.

POU2F3 is a master regulator of a tuft cell-like variant of small cell lung cancer

Small cell lung cancer (SCLC) is widely considered to be a tumor of pulmonary neuroendocrine cells; however, a variant form of this disease has been described that lacks neuroendocrine features. Here, we applied domain-focused CRISPR screening to human cancer cell lines to identify the transcription factor (TF) POU2F3 (POU class 2 homeobox 3; also known as SKN-1a/OCT-11) as a powerful dependency in a subset of SCLC lines. An analysis of human SCLC specimens revealed that POU2F3 is expressed exclusively in variant SCLC tumors that lack expression of neuroendocrine markers and instead express markers of a chemosensory lineage known as tuft cells. Using chromatin- and RNA-profiling experiments, we provide evidence that POU2F3 is a master regulator of tuft cell identity in a variant form of SCLC. Moreover, we show that most SCLC tumors can be classified into one of three lineages based on the expression of POU2F3, ASCL1, or NEUROD1. Our CRISPR screens exposed other unique dependencies in POU2F3-expressing SCLC lines, including the lineage TFs SOX9 and ASCL2 and the receptor tyrosine kinase IGF1R (insulin-like growth factor 1 receptor). These data reveal POU2F3 as a cell identity determinant and a dependency in a tuft cell-like variant of SCLC, which may reflect a previously unrecognized cell of origin or a trans-differentiation event in this disease.

Iron Starvation Conditions Upregulate Ehrlichia ruminantium Type IV Secretion System, tr1 Transcription Factor and map1 Genes Family through the Master Regulatory Protein ErxR

Ehrlichia ruminantium is an obligatory intracellular bacterium that causes heartwater, a fatal disease in ruminants. Due to its intracellular nature, E. ruminantium requires a set of specific virulence factors, such as the type IV secretion system (T4SS), and outer membrane proteins (Map proteins) in order to avoid and subvert the host's immune response. Several studies have been conducted to understand the regulation of the T4SS or outer membrane proteins, in Ehrlichia, but no integrated approach has been used to understand the regulation of Ehrlichia pathogenicity determinants in response to environmental cues. Iron is known to be a key nutrient for bacterial growth both in the environment and within hosts. In this study, we experimentally demonstrated the regulation of virB, map1, and tr1 genes by the newly identified master regulator ErxR (for Ehrlichia ruminantium expression regulator). We also analyzed the effect of iron depletion on the expression of erxR gene, tr1 transcription factor, T4SS and map1 genes clusters in E. ruminantium. We show that exposure of E. ruminantium to iron starvation induces erxR and subsequently tr1, virB, and map1 genes. Our results reveal tight co-regulation of T4SS and map1 genes via the ErxR regulatory protein at the transcriptional level, and, for the first time link map genes to the virulence function sensu stricto, thereby advancing our understanding of Ehrlichia's infection process. These results suggest that Ehrlichia is able to sense changes in iron concentrations in the environment and to regulate the expression of virulence factors accordingly.

Neuromedin U alters bioenergetics and expands the cancer stem cell phenotype in HER2-positive breast cancer

Neuromedin U (NmU) is a neuropeptide belonging to the neuromedin family. Recently, we reported a significant association between NmU and breast cancer, particularly correlating with increased aggressiveness, resistance to HER2-targeted therapies and overall significantly poorer outcome for patients, although the mechanism through which it exerts this effect remained unexplained. Investigating this, here we found that ectopic over-expression of NmU in HER2-positive breast cancer cells induced aberrant metabolism, with increased glycolysis, likely due to enhanced pyruvate dehydrogenase kinase activity. Similar results were observed in HER2-targeted drug-resistant cell variants, which we had previously shown to display increased levels of NmU. Overexpression of NmU also resulted in upregulation of epithelial-mesenchymal transition markers and increased IL-6 secretion which, together with aberrant metabolism, have all been associated with the cancer stem cell (CSC) phenotype. Flow cytometry experiments confirmed that NmU-overexpressing and HER2-targeted drug-resistant cells showed an increased proportion of cells with CSC phenotype (CD44⁺ /CD24^- ). Taken together, our results report a new mechanism of action for NmU in HER2-overexpressing breast cancer that enhances resistance to HER2-targeted drugs through conferring CSC characteristics and expansion of the CSC phenotype.

NFIX as a Master Regulator for Lung Cancer Progression

About 40% of lung cancer cases globally are diagnosed at the advanced stage. Lung cancer has a high mortality and overall survival in stage I disease is only 70%. This study was aimed at finding a candidate of transcription regulator that initiates the mechanism for metastasis by integrating computational and functional studies. The genes involved in lung cancer were retrieved using in silico software. 10 kb promoter sequences upstream were scanned for the master regulator. Transient transfection of shRNA NFIXs were conducted against A549 and NCI-H1299 cell lines. qRT-PCR and functional assays for cell proliferation, migration and invasion were carried out to validate the involvement of NFIX in metastasis. Genome-wide gene expression microarray using a HumanHT-12v4.0 Expression BeadChip Kit was performed to identify differentially expressed genes and construct a new regulatory network. The in silico analysis identified NFIX as a master regulator and is strongly associated with 17 genes involved in the migration and invasion pathways including IL6ST, TIMP1 and ITGB1. Silencing of NFIX showed reduced expression of IL6ST, TIMP1 and ITGB1 as well as the cellular proliferation, migration and invasion processes. The data was integrated with the in silico analyses to find the differentially expressed genes. Microarray analysis showed that 18 genes were expressed differentially in both cell lines after statistical analyses integration between t-test, LIMMA and ANOVA with Benjamini-Hochberg adjustment at p-value < 0.05. A transcriptional regulatory network was created using all 18 genes, the existing regulated genes including the new genes PTCH1, NFAT5 and GGCX that were found highly associated with NFIX, the master regulator of metastasis. This study suggests that NFIX is a promising target for therapeutic intervention that is expected to inhibit metastatic recurrence and improve survival rate.

Interferon-γ is a master checkpoint regulator of cytokine-induced differentiation

Cytokines are protein mediators that are known to be involved in many biological processes, including cell growth, survival, inflammation, and development. To study their regulation, we generated a library of 209 different cytokines. This was used in a combinatorial format to study the effects of cytokines on each other, with particular reference to the control of differentiation. This study showed that IFN-γ is a master checkpoint regulator for many cytokines. It operates via an autocrine mechanism to elevate STAT1 and induce internalization of gp130, a common component of many heterodimeric cytokine receptors. This targeting of a receptor subunit that is common to all members of an otherwise diverse family solves the problem of how a master regulator can control so many diverse receptors. When one adds an autocrine mechanism, fine control at the level of individual cells is achieved.

Large-Scale trans-eQTLs Affect Hundreds of Transcripts and Mediate Patterns of Transcriptional Co-regulation

Efforts to decipher the causal relationships between differences in gene regulation and corresponding differences in phenotype have been stymied by several basic technical challenges. Although detecting local, cis-eQTLs is now routine, trans-eQTLs, which are distant from the genes of origin, are far more difficult to find because millions of SNPs must currently be compared to thousands of transcripts. Here, we demonstrate an alternative approach: we looked for SNPs associated with the expression of many genes simultaneously and found that hundreds of trans-eQTLs each affect hundreds of transcripts in lymphoblastoid cell lines across three African populations. These trans-eQTLs target the same genes across the three populations and show the same direction of effect. We discovered that target transcripts of a high-confidence set of trans-eQTLs encode proteins that interact more frequently than expected by chance, are bound by the same transcription factors, and are enriched for pathway annotations indicative of roles in basic cell homeostasis. We thus demonstrate that our approach can uncover trans-acting transcriptional control circuits that affect co-regulated groups of genes: a key to understanding how cellular pathways and processes are orchestrated.

Crystal structure of the DNA binding domain of the transcription factor T-bet suggests simultaneous recognition of distant genome sites

The transcription factor T-bet (Tbox protein expressed in T cells) is one of the master regulators of both the innate and adaptive immune responses. It plays a central role in T-cell lineage commitment, where it controls the T_H1 response, and in gene regulation in plasma B-cells and dendritic cells. T-bet is a member of the Tbox family of transcription factors; however, T-bet coordinately regulates the expression of many more genes than other Tbox proteins. A central unresolved question is how T-bet is able to simultaneously recognize distant Tbox binding sites, which may be located thousands of base pairs away. We have determined the crystal structure of the Tbox DNA binding domain (DBD) of T-bet in complex with a palindromic DNA. The structure shows a quaternary structure in which the T-bet dimer has its DNA binding regions splayed far apart, making it impossible for a single dimer to bind both sites of the DNA palindrome. In contrast to most other Tbox proteins, a single T-bet DBD dimer binds simultaneously to identical half-sites on two independent DNA. A fluorescence-based assay confirms that T-bet dimers are able to bring two independent DNA molecules into close juxtaposition. Furthermore, chromosome conformation capture assays confirm that T-bet functions in the direct formation of chromatin loops in vitro and in vivo. The data are consistent with a looping/synapsing model for transcriptional regulation by T-bet in which a single dimer of the transcription factor can recognize and coalesce distinct genetic elements, either a promoter plus a distant regulatory element, or promoters on two different genes.

Elucidation and Pharmacological Targeting of Novel Molecular Drivers of Follicular Lymphoma Progression

Follicular lymphoma, the most common indolent subtype of non-Hodgkin lymphoma, is associated with a relatively long overall survival rate ranging from 6 to 10 years from the time of diagnosis. However, in 20% to 60% of follicular lymphoma patients, transformation to aggressive diffuse large B-cell lymphoma (DLBCL) reduces median survival to only 1.2 years. The specific functional and genetic determinants of follicular lymphoma transformation remain elusive, and genomic alterations underlying disease advancement have only been identified for a subset of cases. Therefore, to identify candidate drivers of follicular lymphoma transformation, we performed systematic analysis of a B-cell-specific regulatory model exhibiting follicular lymphoma transformation signatures using the Master Regulator Inference algorithm (MARINa). This analysis revealed FOXM1, TFDP1, ATF5, HMGA1, and NFYB to be candidate master regulators (MR) contributing to disease progression. Accordingly, validation was achieved through synthetic lethality assays in which RNAi-mediated silencing of MRs individually or in combination reduced the viability of (14;18)-positive DLBCL (t-DLBCL) cells. Furthermore, specific combinations of small-molecule compounds targeting synergistic MR pairs induced loss of viability in t-DLBCL cells. Collectively, our findings indicate that MR analysis is a valuable method for identifying bona fide contributors to follicular lymphoma transformation and may therefore guide the selection of compounds to be used in combinatorial treatment strategies.

[ Super-enhancers. Are they regulators of regulatory genes of development and cancer?]

Enhancers make up a huge class of genome regulatory elements that play an important role in the formation and maintenance of specific patterns of gene transcriptional activity in all types of cells. In recent years, high-throughput methods for the genome-wide epigenetic analysis of chromatin have made it possible to identify structural and functional features of enhancers and their role in the spatial and functional organization of the genome and in the formation and maintenance of cell identity, as well as in the pathogenesis of certain diseases. Special attention has been focused on genome regions called super-enhancers, or stretch enhancers, which consist of clusters of elements with properties of classic enhancers. This review considers current data on specific properties of super-enhancers and their role in the formation of interconnected autoregulatory circuits with positive feedback that regulates the most important genes, the activity of which underlies the formation and maintenance of specialized cellular functions.

A Gene Regulatory Program in Human Breast Cancer

Molecular heterogeneity in human breast cancer has challenged diagnosis, prognosis, and clinical treatment. It is well known that molecular subtypes of breast tumors are associated with significant differences in prognosis and survival. Assuming that the differences are attributed to subtype-specific pathways, we then suspect that there might be gene regulatory mechanisms that modulate the behavior of the pathways and their interactions. In this study, we proposed an integrated methodology, including machine learning and information theory, to explore the mechanisms. Using existing data from three large cohorts of human breast cancer populations, we have identified an ensemble of 16 master regulator genes (or MR16) that can discriminate breast tumor samples into four major subtypes. Evidence from gene expression across the three cohorts has consistently indicated that the MR16 can be divided into two groups that demonstrate subtype-specific gene expression patterns. For example, group 1 MRs, including ESR1, FOXA1, and GATA3, are overexpressed in luminal A and luminal B subtypes, but lowly expressed in HER2-enriched and basal-like subtypes. In contrast, group 2 MRs, including FOXM1, EZH2, MYBL2, and ZNF695, display an opposite pattern. Furthermore, evidence from mutual information modeling has congruently indicated that the two groups of MRs either up- or down-regulate cancer driver-related genes in opposite directions. Furthermore, integration of somatic mutations with pathway changes leads to identification of canonical genomic alternations in a subtype-specific fashion. Taken together, these studies have implicated a gene regulatory program for breast tumor progression.

A systems approach to drug discovery in Alzheimer's disease

In the articles included in this volume, one feels a strong frustration among the writers with the slow course of therapeutics development for Alzheimer's disease and with the clinical failure of targeted therapeutic agents despite substantial progress in our understanding of the biology and biochemistry of the disease.

Helper T-cell identity and evolution of differential transcriptomes and epigenomes

CD4(+) T cells are critical for the elimination of an immense array of microbial pathogens. Among the ways they accomplish this task is to generate progeny with specialized, characteristic patterns of gene expression. From this perspective, helper cells can be viewed as pluripotent precursors that adopt distinct cell fates. Although there are aspects of helper cell differentiation that can be modeled as a classic cell fate commitment, CD4(+) T cells also maintain considerable flexibility in their transcriptional program. This makes sense in terms of host defense, but raises the question of how these remarkable cells balance both these requirements, a high degree of specific gene expression and the capacity for plasticity. In this review, we discuss recent advances in our understanding of CD4(+) T-cell specification, focusing on how genomic perspectives have influenced our views of these processes. The relative contributions of sensors of the cytokine milieu, especially the signal transducer and activator of transcription family transcription factors, 'master regulators', and other transcription factors are considered as they relate to the helper cell transcriptome and epigenome.

Target hub proteins serve as master regulators of development in yeast

To understand the organization of the transcriptional networks that govern cell differentiation, we have investigated the transcriptional circuitry controlling pseudohyphal development in Saccharomyces cerevisiae. The binding targets of Ste12, Tec1, Sok2, Phd1, Mga1, and Flo8 were globally mapped across the yeast genome. The factors and their targets form a complex binding network, containing patterns characteristic of autoregulation, feedback and feed-forward loops, and cross-talk. Combinatorial binding to intergenic regions was commonly observed, which allowed for the identification of a novel binding association between Mga1 and Flo8, in which Mga1 requires Flo8 for binding to promoter regions. Further analysis of the network showed that the promoters of MGA1 and PHD1 were bound by all of the factors used in this study, identifying them as key target hubs. Overexpression of either of these two proteins specifically induced pseudohyphal growth under noninducing conditions, highlighting them as master regulators of the system. Our results indicate that target hubs can serve as master regulators whose activity is sufficient for the induction of complex developmental responses and therefore represent important regulatory nodes in biological networks.