Transcriptional Repressive H3K9 and H3K27 Methylations Contribute to DNMT1-Mediated DNA Methylation Recovery

DNA methylation and histone modifications are two major epigenetic events regulating gene expression and chromatin structure, and their alterations are linked to human carcinogenesis. DNA methylation plays an important role in tumor suppressor gene inactivation, and can be revised by DNA methylation inhibitors. The reversible nature of DNA methylation forms the basis of epigenetic cancer therapy. However, it has been reported that DNA re-methylation and gene re-silencing could occur after removal of demethylation treatment and this may significantly hamper the therapeutic value of DNA methylation inhibitors. In this study we have provided detailed evidence demonstrating that mammalian cells possess a bona fide DNA methylation recovery system. We have also shown that DNA methylation recovery was mediated by the major human DNA methyltransferase, DNMT1. In addition, we found that H3K9-tri-methylation and H3K27-tri-methylation were closely associated with this DNA methylation recovery. These persistent transcriptional repressive histone modifications may have a crucial role in regulating DNMT1-mediated DNA methylation recovery. Our findings may have important implications towards a better understanding of epigenetic regulation and future development of epigenetic therapeutic intervention

Key questions for modelling COVID-19 exit strategies

This is the final version. Available on open access from the Royal Society via the DOI in this recordCombinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.Alan Turing InstituteEPSR

Key questions for modelling COVID-19 exit strategies

This is the final version. Available on open access from the Royal Society via the DOI in this recordCombinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.Alan Turing InstituteEPSR

The anticancer effects of chaetocin are independent of programmed cell death and hypoxia, and are associated with inhibition of endothelial cell proliferation

BACKGROUND: We previously reported that chaetocin has potent and selective anti-myeloma activity attributable to reactive oxygen species (ROS) induction imposed by inhibition of the redox enzyme thioredoxin reductase; we now detail its effects in solid tumours. METHODS: Cellular assays, transcriptional profiling and the NCI60 screen were used to assess the effects of chaetocin in solid tumour and endothelial cells. RESULTS: NCI-60 screening demonstrated chaetocin to even more potently inhibit proliferation in solid tumour than in haematological cell lines; transcriptional profiling revealed a signature consistent with induction of inflammatory response and cell death pathways. Chaetocin induced ROS, oxidative damage to cellular proteins and apoptosis, with 2–10 n IC(50)s (24 h exposures) in all tested solid tumour cell lines. The pan-caspase inhibitor zVAD-fmk did not block chaetocin-induced cell death despite inhibiting mitochondrial membrane depolarisation and apoptosis. Further, Molt-4 rho(0) cells lacking metabolically functional mitochondria were readily killed by chaetocin; in addition chaetocin-induced cytotoxicity was unaffected by autophagy inhibitors or hypoxia and consequent HIF-1α upregulation. Moreover, chaetocin inhibited SKOV3 ovarian cancer xenografts producing less vascular tumours, and inhibited human umbilical vein endothelial cell proliferation. CONCLUSION: Chaetocin has intriguing and wide-ranging in vitro and in vivo anticancer effects, and is an attractive candidate for further preclinical and clinical development

Evidence for complex contagion models of social contagion from observational data

Social influence can lead to behavioural 'fads' that are briefly popular and quickly die out. Various models have been proposed for these phenomena, but empirical evidence of their accuracy as real-world predictive tools has so far been absent. Here we find that a 'complex contagion' model accurately describes the spread of behaviours driven by online sharing. We found that standard, 'simple', contagion often fails to capture both the rapid spread and the long tails of popularity seen in real fads, where our complex contagion model succeeds. Complex contagion also has predictive power: it successfully predicted the peak time and duration of the ALS Icebucket Challenge. The fast spread and longer duration of fads driven by complex contagion has important implications for activities such as publicity campaigns and charity drives