Jialiang Huang

Dynamic Control of Enhancer Repertoires Drives Lineage and Stage-Specific Transcription during Hematopoiesis

Enhancers are the primary determinants of cell identity, but the regulatory components controlling enhancer turnover during lineage commitment remain largely unknown. Here we compare the enhancer landscape, transcriptional factor occupancy, and transcriptomic changes in human fetal and adult hematopoietic stem/progenitor cells and committed erythroid progenitors. We find that enhancers are modulated pervasively and direct lineage- and stage-specific transcription. GATA2-to-GATA1 switch is prevalent at dynamic enhancers and drives erythroid enhancer commissioning. Examination of lineage-specific enhancers identifies transcription factors and their combinatorial patterns in enhancer turnover. Importantly, by CRISPR/Cas9-mediated genomic editing, we uncover functional hierarchy of constituent enhancers within the SLC25A37 super-enhancer. Despite indistinguishable chromatin features, we reveal through genomic editing the functional diversity of several GATA switch enhancers in which enhancers with opposing functions cooperate to coordinate transcription. Thus, genome-wide enhancer profiling coupled with in situ enhancer editing provide critical insights into the functional complexity of enhancers during development.

Systematic Prediction of Pharmacodynamic Drug-Drug Interactions through Protein-Protein-Interaction Network

Identifying drug-drug interactions (DDIs) is a major challenge in drug development. Previous attempts have established formal approaches for pharmacokinetic (PK) DDIs, but there is not a feasible solution for pharmacodynamic (PD) DDIs because the endpoint is often a serious adverse event rather than a measurable change in drug concentration. Here, we developed a metric “S-score” that measures the strength of network connection between drug targets to predict PD DDIs. Utilizing known PD DDIs as golden standard positives (GSPs), we observed a significant correlation between S-score and the likelihood a PD DDI occurs. Our prediction was robust and surpassed existing methods as validated by two independent GSPs. Analysis of clinical side effect data suggested that the drugs having predicted DDIs have similar side effects. We further incorporated this clinical side effects evidence with S-score to increase the prediction specificity and sensitivity through a Bayesian probabilistic model. We have predicted 9,626 potential PD DDIs at the accuracy of 82% and the recall of 62%. Importantly, our algorithm provided opportunities for better understanding the potential molecular mechanisms or physiological effects underlying DDIs, as illustrated by the case studies.

PKA phosphorylation couples hepatic inositol-requiring enzyme 1α to glucagon signaling in glucose metabolism

The endoplasmic reticulum (ER)-resident protein kinase/endoribonuclease inositol-requiring enzyme 1 (IRE1) is activated through transautophosphorylation in response to protein folding overload in the ER lumen and maintains ER homeostasis by triggering a key branch of the unfolded protein response. Here we show that mammalian IRE1α in liver cells is also phosphorylated by a kinase other than itself in response to metabolic stimuli. Glucagon-stimulated protein kinase PKA, which in turn phosphorylated IRE1α at Ser724, a highly conserved site within the kinase activation domain. Blocking Ser724 phosphorylation impaired the ability of IRE1α to augment the up-regulation by glucagon signaling of the expression of gluconeogenic genes. Moreover, hepatic IRE1α was highly phosphorylated at Ser724 by PKA in mice with obesity, and silencing hepatic IRE1α markedly reduced hyperglycemia and glucose intolerance. Hence, these results suggest that IRE1α integrates signals from both the ER lumen and the cytoplasm in the liver and is coupled to the glucagon signaling in the regulation of glucose metabolism.

Predicting chromatin organization using histone marks.

Genome-wide mapping of three dimensional chromatin organization is an important yet technically challenging task. To aid experimental effort and to understand the determinants of long-range chromatin interactions, we have developed a computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries. Our model accurately and robustly predicts these features across datasets and cell types. Cell-type specific histone mark information is required for prediction of chromatin interaction hubs but not for TAD boundaries. Our predictions provide a useful guide for the exploration of chromatin organization.

Midlife gene expressions identify modulators of aging through dietary interventions

Dietary interventions are effective ways to extend or shorten lifespan. By examining midlife hepatic gene expressions in mice under different dietary conditions, which resulted in different lifespans and aging-related phenotypes, we were able to identify genes and pathways that modulate the aging process. We found that pathways transcriptionally correlated with diet-modulated lifespan and physiological changes were enriched for lifespan-modifying genes. Intriguingly, mitochondrial gene expression correlated with lifespan and anticorrelated with aging-related pathological changes, whereas peroxisomal gene expression showed an opposite trend. Both organelles produce reactive oxygen species, a proposed causative factor of aging. This finding implicates a contribution of peroxisome to aging. Consistent with this hypothesis, lowering the expression levels of peroxisome proliferation genes decreased the cellular peroxide levels and extended the lifespan of Drosophila melanogaster and Caenorhabditis elegans. These findings show that transcriptional changes resulting from dietary interventions can effectively reflect causal factors in aging and identify previously unknown or under-appreciated longevity pathways, such as the peroxisome pathway.

DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome

Drug–drug interactions (DDIs) may cause serious side-effects that draw great attention from both academia and industry. Since some DDIs are mediated by unexpected drug–human protein interactions, it is reasonable to analyze the chemical–protein interactome (CPI) profiles of the drugs to predict their DDIs. Here we introduce the DDI-CPI server, which can make real-time DDI predictions based only on molecular structure. When the user submits a molecule, the server will dock users molecule across 611 human proteins, generating a CPI profile that can be used as a feature vector for the pre-constructed prediction model. It can suggest potential DDIs between the users molecule and our library of 2515 drug molecules. In cross-validation and independent validation, the server achieved an AUC greater than 0.85. Additionally, by investigating the CPI profiles of predicted DDI, users can explore the PK/PD proteins that might be involved in a particular DDI. A 3D visualization of the drug-protein interaction will be provided as well. The DDI-CPI is freely accessible at http://cpi.bio-x.cn/ddi/.

Systems Biology in Aging: Linking the Old and the Young

Aging can be defined as a process of progressive decline in the physiological capacity of an organism, manifested by accumulated alteration and destabilization at the whole system level. Systems biology approaches offer a promising new perspective to examine the old problem of aging. We begin this review by introducing the concepts of systems biology, and then illustrate the application of systems biology approaches to aging research, from gene expression profiling to network analysis. We then introduce the network that can be constructed using known lifespan and aging regulators, and conclude with a look forward to the future of systems biology in aging research. In summary, systems biology is not only a young field that may help us understand aging at a higher level, but also an important platform that can link different levels of knowledge on aging, moving us closer to a more comprehensive control of systematic decline during aging.

Chronic myelogenous leukemia initiating cells require Polycomb group protein EZH2

Tyrosine kinase inhibitors (TKI) have revolutionized chronic myelogenous leukemia (CML) management. Disease eradication, however, is hampered by innate resistance of leukemia-initiating cells (LIC) to TKI-induced killing, which also provides the basis for subsequent emergence of TKI-resistant mutants. We report that EZH2, the catalytic subunit of Polycomb Repressive Complex 2 (PRC2), is overexpressed in CML LICs and required for colony formation and survival and cell-cycle progression of CML cell lines. A critical role for EZH2 is supported by genetic studies in a mouse CML model. Inactivation of Ezh2 in conventional conditional mice and through CRISPR/Cas9-mediated gene editing prevents initiation and maintenance of disease and survival of LICs, irrespective of BCR-ABL1 mutational status, and extends survival. Expression of the EZH2 homolog EZH1 is reduced in EZH2-deficient CML LICs, creating a scenario resembling complete loss of PRC2. EZH2 dependence of CML LICs raises prospects for improved therapy of TKI-resistant CML and/or eradication of disease by addition of EZH2 inhibitors. SIGNIFICANCE This work defines EZH2 as a selective vulnerability for CML cells and their LICs, regardless of BCR-ABL1 mutational status. Our findings provide an experimental rationale for improving disease eradication through judicious use of EZH2 inhibitors within the context of standard-of-care TKI therapy. Cancer Discov; 6(11); 1237-47. ©2016 AACR.See related article by Scott et al., p. 1248This article is highlighted in the In This Issue feature, p. 1197.

Transcriptome and Network Changes in Climbers at Extreme Altitudes

Extreme altitude can induce a range of cellular and systemic responses. Although it is known that hypoxia underlies the major changes and that the physiological responses include hemodynamic changes and erythropoiesis, the molecular mechanisms and signaling pathways mediating such changes are largely unknown. To obtain a more complete picture of the transcriptional regulatory landscape and networks involved in extreme altitude response, we followed four climbers on an expedition up Mount Xixiabangma (8,012 m), and collected blood samples at four stages during the climb for mRNA and miRNA expression assays. By analyzing dynamic changes of gene networks in response to extreme altitudes, we uncovered a highly modular network with 7 modules of various functions that changed in response to extreme altitudes. The erythrocyte differentiation module is the most prominently up-regulated, reflecting increased erythrocyte differentiation from hematopoietic stem cells, probably at the expense of differentiation into other cell lineages. These changes are accompanied by coordinated down-regulation of general translation. Network topology and flow analyses also uncovered regulators known to modulate hypoxia responses and erythrocyte development, as well as unknown regulators, such as the OCT4 gene, an important regulator in stem cells and assumed to only function in stem cells. We predicted computationally and validated experimentally that increased OCT4 expression at extreme altitude can directly elevate the expression of hemoglobin genes. Our approach established a new framework for analyzing the transcriptional regulatory network from a very limited number of samples.

The histone demethylase UTX regulates the lineage-specific epigenetic program of invariant natural killer T cells

Invariant natural killer T cells (iNKT cells) are innate-like lymphocytes that protect against infection, autoimmune disease and cancer. However, little is known about the epigenetic regulation of iNKT cell development. Here we found that the H3K27me3 histone demethylase UTX was an essential cell-intrinsic factor that controlled an iNKT-cell lineage-specific gene-expression program and epigenetic landscape in a demethylase-activity-dependent manner. UTX-deficient iNKT cells exhibited impaired expression of iNKT cell signature genes due to a decrease in activation-associated H3K4me3 marks and an increase in repressive H3K27me3 marks within the promoters occupied by UTX. We found that JunB regulated iNKT cell development and that the expression of genes that were targets of both JunB and the iNKT cell master transcription factor PLZF was UTX dependent. We identified iNKT cell super-enhancers and demonstrated that UTX-mediated regulation of super-enhancer accessibility was a key mechanism for commitment to the iNKT cell lineage. Our findings reveal how UTX regulates the development of iNKT cells through multiple epigenetic mechanisms.