Mathematical model of a telomerase transcriptional regulatory network developed by cell-based screening: analysis of inhibitor effects and telomerase expression mechanisms

Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability

Finfish and aquatic invertebrate pathology resources for now and the future

Utilization of finfish and aquatic invertebrates in biomedical research and as environmental sentinels has grown dramatically in recent decades. Likewise the aquaculture of finfish and invertebrates has expanded rapidly worldwide as populations of some aquatic food species and threatened or endangered aquatic species have plummeted due to overharvesting or habitat degradation. This increasing intensive culture and use of aquatic species has heightened the importance of maintaining a sophisticated understanding of pathology of various organ systems of these diverse species. Yet, except for selected species long cultivated in aquaculture, pathology databases and the workforce of highly trained pathologists lag behind those available for most laboratory animals and domestic mammalian and avian species. Several factors must change to maximize the use, understanding, and protection of important aquatic species: 1) improvements in databases of abnormalities across species; 2) standardization of diagnostic criteria for proliferative and nonproliferative lesions; and 3) more uniform and rigorous training in aquatic morphologic pathology

Finfish and aquatic invertebrate pathology resources for now and the future

Utilization of finfish and aquatic invertebrates in biomedical research and as environmental sentinels has grown dramatically in recent decades. Likewise the aquaculture of finfish and invertebrates has expanded rapidly worldwide as populations of some aquatic food species and threatened or endangered aquatic species have plummeted due to overharvesting or habitat degradation. This increasing intensive culture and use of aquatic species has heightened the importance of maintaining a sophisticated understanding of pathology of various organ systems of these diverse species. Yet, except for selected species long cultivated in aquaculture, pathology databases and the workforce of highly trained pathologists lag behind those available for most laboratory animals and domestic mammalian and avian species. Several factors must change to maximize the use, understanding, and protection of important aquatic species: 1) improvements in databases of abnormalities across species; 2) standardization of diagnostic criteria for proliferative and nonproliferative lesions; and 3) more uniform and rigorous training in aquatic morphologic pathology

A function-based typology for Earth’s ecosystems

As the United Nations develops a post-2020 global biodiversity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of ‘living in harmony with nature’1,2. Advancing dual imperatives to conserve biodiversity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management3. Ecosystems vary in their biota4, service provision5 and relative exposure to risks6, yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This hampers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth’s ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global biodiversity framework

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

A function-based typology for Earth's ecosystems

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: Descriptions, images and interactive maps for the typology are updated periodically at https://global-ecosystems.org/. The spatial data for this study are available at Zenodo (https://doi.org/10.5281/zenodo.3546513).As the United Nations develops a post-2020 global biodiversity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of 'living in harmony with nature'1,2. Advancing dual imperatives to conserve biodiversity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management3. Ecosystems vary in their biota4, service provision5 and relative exposure to risks6, yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This hampers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth's ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global biodiversity framework.Natural Environment Research Council (NERC

Habitat conservation in Italy: the state of the art in the light of the first European Red List of Terrestrial and Freshwater Habitats

The importance of taking into account ecosystems, plant communities and habitats for the development of biodiversity conservation strategies is increasingly acknowledged. Recently, the first ever European Red List of Habitats was produced, which provided an evaluation of the extinction risk of EUNIS-based natural and semi-natural habitats in Europe. As assessment unit, it used the habitat intended as a plant community, thus representing a landmark for the role of vegetation science in nature conservation. In the present paper, the results of the European Red List of Habitats are analyzed at the national scale with specific reference to the terrestrial and freshwater habitat types occurring in Italy. More than three-quarters of the assessed European habitat types were recognized for the Italian territory. The distribution of the threat categories reflects approximately the situation at the EU28 level. About 35% of the assessed habitat types are referred to a threat category; no critically endangered habitat is present in Italy. The most frequently used criteria are those related to a reduction in quantity. Some critical issues arising from the analyses are discussed. In particular, the presence of knowledge gaps is pointed out, with remarkable reference to the poor availability of spatial and quantitative data, severely affecting the application of the criteria adopted for the assessment. Descriptions of habitat types from Italy are reported, some of which are representative, emblematic or even exclusive to the Italian territory. The outcomes of the analysis represent the starting point for the future development of a national-scale Red List of Habitats. Results also emphasized how habitat types with a too broad definition pose a limit to a proper evaluation of the regional biogeographic variability, often very high in Italy, with local floristic and phytocoenotic peculiarities which do not find room in the adopted European typology. This is the reason why the development of national subtypes stands as a necessary step for the development of a realistic and effective assessment at the national scale

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease