Evolutionary Stability of Small Molecular Regulatory Networks That Exhibit Near-Perfect Adaptation.

Large-scale protein regulatory networks, such as signal transduction systems, contain small-scale modules ('motifs') that carry out specific dynamical functions. Systematic characterization of the properties of small network motifs is therefore of great interest to molecular systems biologists. We simulate a generic model of three-node motifs in search of near-perfect adaptation, the property that a system responds transiently to a change in an environmental signal and then returns near-perfectly to its pre-signal state (even in the continued presence of the signal). Using an evolutionary algorithm, we search the parameter space of these generic motifs for network topologies that score well on a pre-defined measure of near-perfect adaptation. We find many high-scoring parameter sets across a variety of three-node topologies. Of all possibilities, the highest scoring topologies contain incoherent feed-forward loops (IFFLs), and these topologies are evolutionarily stable in the sense that, under 'macro-mutations' that alter the topology of a network, the IFFL motif is consistently maintained. Topologies that rely on negative feedback loops with buffering (NFLBs) are also high-scoring; however, they are not evolutionarily stable in the sense that, under macro-mutations, they tend to evolve an IFFL motif and may-or may not-lose the NFLB motif.

DNA hypomethylating agents increase activation and cytolytic activity of CD8+ T cells.

We demonstrate that DNA hypomethylating agent (HMA) treatment can directly modulate the anti-tumor response and effector function of CD8+ T cells. In vivo HMA treatment promotes CD8+ T cell tumor infiltration and suppresses tumor growth via CD8+ T cell-dependent activity. Ex vivo, HMAs enhance primary human CD8+ T cell activation markers, effector cytokine production, and anti-tumor cytolytic activity. Epigenomic and transcriptomic profiling shows that HMAs vastly regulate T cell activation-related transcriptional networks, culminating with over-activation of NFATc1 short isoforms. Mechanistically, demethylation of an intragenic CpG island immediately downstream to the 3' UTR of the short isoform was associated with antisense transcription and alternative polyadenylation of NFATc1 short isoforms. High-dimensional single-cell mass cytometry analyses reveal a selective effect of HMAs on a subset of human CD8+ T cell subpopulations, increasing both the number and abundance of a granzyme Bhigh, perforinhigh effector subpopulation. Overall, our findings support the use of HMAs as a therapeutic strategy to boost anti-tumor immune response.

Nucleolar RNA polymerase II drives ribosome biogenesis.

Proteins are manufactured by ribosomes-macromolecular complexes of protein and RNA molecules that are assembled within major nuclear compartments called nucleoli1,2. Existing models suggest that RNA polymerases I and III (Pol I and Pol III) are the only enzymes that directly mediate the expression of the ribosomal RNA (rRNA) components of ribosomes. Here we show, however, that RNA polymerase II (Pol II) inside human nucleoli operates near genes encoding rRNAs to drive their expression. Pol II, assisted by the neurodegeneration-associated enzyme senataxin, generates a shield comprising triplex nucleic acid structures known as R-loops at intergenic spacers flanking nucleolar rRNA genes. The shield prevents Pol I from producing sense intergenic noncoding RNAs (sincRNAs) that can disrupt nucleolar organization and rRNA expression. These disruptive sincRNAs can be unleashed by Pol II inhibition, senataxin loss, Ewing sarcoma or locus-associated R-loop repression through an experimental system involving the proteins RNaseH1, eGFP and dCas9 (which we refer to as 'red laser'). We reveal a nucleolar Pol-II-dependent mechanism that drives ribosome biogenesis, identify disease-associated disruption of nucleoli by noncoding RNAs, and establish locus-targeted R-loop modulation. Our findings revise theories of labour division between the major RNA polymerases, and identify nucleolar Pol II as a major factor in protein synthesis and nuclear organization, with potential implications for health and disease.

Sensitive tumour detection and classification using plasma cell-free DNA methylomes.

The use of liquid biopsies for cancer detection and management is rapidly gaining prominence1. Current methods for the detection of circulating tumour DNA involve sequencing somatic mutations using cell-free DNA, but the sensitivity of these methods may be low among patients with early-stage cancer given the limited number of recurrent mutations2-5. By contrast, large-scale epigenetic alterations-which are tissue- and cancer-type specific-are not similarly constrained6 and therefore potentially have greater ability to detect and classify cancers in patients with early-stage disease. Here we develop a sensitive, immunoprecipitation-based protocol to analyse the methylome of small quantities of circulating cell-free DNA, and demonstrate the ability to detect large-scale DNA methylation changes that are enriched for tumour-specific patterns. We also demonstrate robust performance in cancer detection and classification across an extensive collection of plasma samples from several tumour types. This work sets the stage to establish biomarkers for the minimally invasive detection, interception and classification of early-stage cancers based on plasma cell-free DNA methylation patterns.

Mammary molecular portraits reveal lineage-specific features and progenitor cell vulnerabilities.

The mammary epithelium depends on specific lineages and their stem and progenitor function to accommodate hormone-triggered physiological demands in the adult female. Perturbations of these lineages underpin breast cancer risk, yet our understanding of normal mammary cell composition is incomplete. Here, we build a multimodal resource for the adult gland through comprehensive profiling of primary cell epigenomes, transcriptomes, and proteomes. We define systems-level relationships between chromatin-DNA-RNA-protein states, identify lineage-specific DNA methylation of transcription factor binding sites, and pinpoint proteins underlying progesterone responsiveness. Comparative proteomics of estrogen and progesterone receptor-positive and -negative cell populations, extensive target validation, and drug testing lead to discovery of stem and progenitor cell vulnerabilities. Top epigenetic drugs exert cytostatic effects; prevent adult mammary cell expansion, clonogenicity, and mammopoiesis; and deplete stem cell frequency. Select drugs also abrogate human breast progenitor cell activity in normal and high-risk patient samples. This integrative computational and functional study provides fundamental insight into mammary lineage and stem cell biology.

O-Acetylation of Peptidoglycan Limits Helper T Cell Priming and Permits Staphylococcus aureus Reinfection.

Humans do not usually develop effective immunity to Staphylococcus aureus reinfection. Using a murine model that mimics human infection, we show that lack of protective immunity to S. aureus systemic reinfection is associated with robust interleukin-10 (IL-10) production and impaired protective Th17 responses. In dendritic cell co-culture assays, priming with S. aureus promotes robust T cell proliferation, but limits Th cells polarization and production of IL-1ß and other cytokines important for Th1 and Th17 differentiation. We show that O-acetylation of peptidoglycan, a mechanism utilized by S. aureus to block bacterial cell wall breakdown, limits the induction of pro-inflammatory signals required for optimal Th17 polarization. IL-10 deficiency in mice restores protective immunity to S. aureus infection, and adjuvancy with a staphylococcal peptidoglycan O-acetyltransferase mutant reduces IL-10, increases IL-1ß, and promotes development of IL-17-dependent, Th cell-transferable protective immunity. Overall, our study suggests a mechanism whereby S. aureus modulates cytokines critical for induction of protective Th17 immunity.

Pre-neoplastic epigenetic disruption of transcriptional enhancers in chronic inflammation.

Chronic periodontitis (CP) is a chronic inflammatory disease independently associated with higher incidence of oral cavity squamous cell carcinoma (OSCC). However, the molecular mechanism responsible for this increased incidence is unknown. Here we profiled the DNA methylome of CP patients and healthy controls and compared to a large set of OSCC samples from TCGA. We observed a significant overlap between the altered DNA methylation patterns in CP and in OSCC, suggesting an emergence of a pre-neoplastic epigenome in CP. Remarkably, the hypermethylated CpGs in CP were significantly enriched for enhancer elements. This aberrant enhancer methylation is functional and able to disrupt enhancer activity by preventing the binding of chromatin looping factors. This study provides new insights on the molecular mechanisms linking chronic inflammation and tumor predisposition, highlighting the role of epigenetic disruption of transcriptional enhancers.

DNA-Demethylating Agents Target Colorectal Cancer Cells by Inducing Viral Mimicry by Endogenous Transcripts.

DNA-demethylating agents have shown clinical anti-tumor efficacy via an unknown mechanism of action. Using a combination of experimental and bioinformatics analyses in colorectal cancer cells, we demonstrate that low-dose 5-AZA-CdR targets colorectal cancer-initiating cells (CICs) by inducing viral mimicry. This is associated with induction of dsRNAs derived at least in part from endogenous retroviral elements, activation of the MDA5/MAVS RNA recognition pathway, and downstream activation of IRF7. Indeed, disruption of virus recognition pathways, by individually knocking down MDA5, MAVS, or IRF7, inhibits the ability of 5-AZA-CdR to target colorectal CICs and significantly decreases 5-AZA-CdR long-term growth effects. Moreover, transfection of dsRNA into CICs can mimic the effects of 5-AZA-CdR. Together, our results represent a major shift in understanding the anti-tumor mechanisms of DNA-demethylating agents and highlight the MDA5/MAVS/IRF7 pathway as a potentially druggable target against CICs.

Symmetrical Dose-Dependent DNA-Methylation Profiles in Children with Deletion or Duplication of 7q11.23.

Epigenetic dysfunction has been implicated in a growing list of disorders that include cancer, neurodevelopmental disorders, and neurodegeneration. Williams syndrome (WS) and 7q11.23 duplication syndrome (Dup7) are rare neurodevelopmental disorders with broad phenotypic spectra caused by deletion and duplication, respectively, of a 1.5-Mb region that includes several genes with a role in epigenetic regulation. We have identified striking differences in DNA methylation across the genome between blood cells from children with WS or Dup7 and blood cells from typically developing (TD) children. Notably, regions that were differentially methylated in both WS and Dup7 displayed a significant and symmetrical gene-dose-dependent effect, such that WS typically showed increased and Dup7 showed decreased DNA methylation. Differentially methylated genes were significantly enriched with genes in pathways involved in neurodevelopment, autism spectrum disorder (ASD) candidate genes, and imprinted genes. Using alignment with ENCODE data, we also found the differentially methylated regions to be enriched with CCCTC-binding factor (CTCF) binding sites. These findings suggest that gene(s) within 7q11.23 alter DNA methylation at specific sites across the genome and result in dose-dependent DNA-methylation profiles in WS and Dup7. Given the extent of DNA-methylation changes and the potential impact on CTCF binding and chromatin regulation, epigenetic mechanisms most likely contribute to the complex neurological phenotypes of WS and Dup7. Our findings highlight the importance of DNA methylation in the pathogenesis of WS and Dup7 and provide molecular mechanisms that are potentially shared by WS, Dup7, and ASD.

Aberrant DNA methylation reprogramming during induced pluripotent stem cell generation is dependent on the choice of reprogramming factors.

The conversion of somatic cells into pluripotent stem cells via overexpression of reprogramming factors involves epigenetic remodeling. DNA methylation at a significant proportion of CpG sites in induced pluripotent stem cells (iPSCs) differs from that of embryonic stem cells (ESCs). Whether different sets of reprogramming factors influence the type and extent of aberrant DNA methylation in iPSCs differently remains unknown. In order to help resolve this critical question, we generated human iPSCs from a common fibroblast cell source using either the Yamanaka factors (OCT4, SOX2, KLF4 and cMYC) or the Thomson factors (OCT4, SOX2, NANOG and LIN28), and determined their genome-wide DNA methylation profiles. In addition to shared DNA methylation aberrations present in all our iPSCs, we identified Yamanaka-iPSC (Y-iPSC)-specific and Thomson-iPSC (T-iPSC)-specific recurrent aberrations. Strikingly, not only were the genomic locations of the aberrations different but also their types: reprogramming with Yamanaka factors mainly resulted in failure to demethylate CpGs, whereas reprogramming with Thomson factors mainly resulted in failure to methylate CpGs. Differences in the level of transcripts encoding DNMT3b and TET3 between Y-iPSCs and T-iPSCs may contribute partially to the distinct types of aberrations. Finally, de novo aberrantly methylated genes in Y-iPSCs were enriched for NANOG targets that are also aberrantly methylated in some cancers. Our study thus reveals that the choice of reprogramming factors influences the amount, location, and class of DNA methylation aberrations in iPSCs. These findings may provide clues into how to produce human iPSCs with fewer DNA methylation abnormalities.

A hybrid model of mammalian cell cycle regulation.

The timing of DNA synthesis, mitosis and cell division is regulated by a complex network of biochemical reactions that control the activities of a family of cyclin-dependent kinases. The temporal dynamics of this reaction network is typically modeled by nonlinear differential equations describing the rates of the component reactions. This approach provides exquisite details about molecular regulatory processes but is hampered by the need to estimate realistic values for the many kinetic constants that determine the reaction rates. It is difficult to estimate these kinetic constants from available experimental data. To avoid this problem, modelers often resort to 'qualitative' modeling strategies, such as Boolean switching networks, but these models describe only the coarsest features of cell cycle regulation. In this paper we describe a hybrid approach that combines the best features of continuous differential equations and discrete Boolean networks. Cyclin abundances are tracked by piecewise linear differential equations for cyclin synthesis and degradation. Cyclin synthesis is regulated by transcription factors whose activities are represented by discrete variables (0 or 1) and likewise for the activities of the ubiquitin-ligating enzyme complexes that govern cyclin degradation. The discrete variables change according to a predetermined sequence, with the times between transitions determined in part by cyclin accumulation and degradation and as well by exponentially distributed random variables. The model is evaluated in terms of flow cytometry measurements of cyclin proteins in asynchronous populations of human cell lines. The few kinetic constants in the model are easily estimated from the experimental data. Using this hybrid approach, modelers can quickly create quantitatively accurate, computational models of protein regulatory networks in cells.