Morgan, E. | Search bioRxiv

bioRxiv2018

High-risk human papillomaviruses down-regulate expression of the Ste20 family kinase MST1 to inhibit the Hippo pathway and promote transformation

Human papillomaviruses (HPV) are a major cause of malignancy worldwide They are the aetiological agent of almost all cervical cancers and an increasing number of head and neck carcinomas. Deregulation of the Hippo pathway component YAP1 has recently been demonstrated to play a role in HPV-mediated cervical cancer, but whether other components of this pathway are implicated in the pathogenesis of this disease remains poorly understood.\n\nThe expression level and activation status of critical Hippo pathway components were analysed across multiple cytology samples from patients with cervical disease, as well as HPV positive (HPV+) and HPV negative (HPV-) cervical cancer cell lines using real time qPCR, western blot and immunohistochemistry. In parallel, we assessed the effects of MST1 and MST2 overexpression upon cervical cancer cell proliferation, migration and invasion. Finally, we interrogated the consequences of interrupted MST1 and MST2 function using a targeted small molecule inhibitor in tandem with kinase inactive MST mutants. Our analysis found that expression of the Ste20 kinase MST1 was decreased within both HPV+ primary patient samples and cervical cancer cell lines. This effect was mediated by the virus-coded oncoproteins E6 and E7, which impair MST1 transcription. Reintroduction of MST1, or its paralogue MST2, into HPV positive cervical cancer cells re-activated the Hippo pathway, leading to a reduction in cell proliferation, migration and invasion. Finally, using a small molecule inhibitor of MST1/2 or kinase inactive mutants of either protein, we demonstrated that this effect required the kinase function of MST1/2. Our results reveal that HPV down regulates MST1 expression to inactivate the Hippo pathway and so drive cells towards transformation.

microbiology↗

bioRxiv2018

A mechanistic hydro-epidemiological model of liver fluke risk

The majority of existing models for predicting disease risk in response to climate change are empirical. These models exploit correlations between historical data, rather than explicitly describing relationships between cause and response variables. Therefore, they are unsuitable for capturing impacts beyond historically observed variability and cannot be employed to assess interventions. In this study, we integrate environmental and epidemiological processes into a new mechanistic model, taking the widespread parasitic disease of fasciolosis as an example. The model simulates environmental suitability for disease transmission, explicitly linking the parasite life-cycle to key weather-water-environment conditions. First, using epidemiological data, we show that the model can reproduce observed infection levels in time and space over two case studies in the UK. Second, to overcome data limitations, we propose a calibration approach based on Monte Carlo sampling and expert opinion, which allows constraint of the model in a process-based way, including a quantification of uncertainty. Finally, comparison with information from the literature and a widely-used empirical risk index shows that the simulated disease dynamics agree with what has been traditionally observed, and that the new model gives better insight into the time-space patterns of infection, which will be valuable for decision support.

epidemiology↗