TMEM87a/Elkin1, a component of a novel mechanoelectrical transduction pathway, modulates melanoma adhesion and migration

Mechanoelectrical transduction is a cellular signalling pathway where physical stimuli are converted into electro-chemical signals by mechanically activated ion channels. We describe here the presence of mechanically activated currents in melanoma cells that are dependent on TMEM87a, which we have renamed Elkin1. Heterologous expression of this protein in PIEZO1-deficient cells, that exhibit no baseline mechanosensitivity, is sufficient to reconstitute mechanically activated currents. Melanoma cells lacking functional Elkin1 exhibit defective mechanoelectrical transduction, decreased motility and increased dissociation from organotypic spheroids. By analysing cell adhesion properties, we demonstrate that Elkin1 deletion is associated with increased cell-substrate adhesion and decreased homotypic cell-cell adhesion strength. We therefore conclude that Elkin1 supports a PIEZO1-independent mechanoelectrical transduction pathway and modulates cellular adhesions and regulates melanoma cell migration and cell-cell interactions

A standardisation framework for bio‐logging data to advance ecological research and conservation

Bio‐logging data obtained by tagging animals are key to addressing global conservation challenges. However, the many thousands of existing bio‐logging datasets are not easily discoverable, universally comparable, nor readily accessible through existing repositories and across platforms, slowing down ecological research and effective management. A set of universal standards is needed to ensure discoverability, interoperability and effective translation of bio‐logging data into research and management recommendations. We propose a standardisation framework adhering to existing data principles (FAIR: Findable, Accessible, Interoperable and Reusable; and TRUST: Transparency, Responsibility, User focus, Sustainability and Technology) and involving the use of simple templates to create a data flow from manufacturers and researchers to compliant repositories, where automated procedures should be in place to prepare data availability into four standardised levels: (a) decoded raw data, (b) curated data, (c) interpolated data and (d) gridded data. Our framework allows for integration of simple tabular arrays (e.g. csv files) and creation of sharable and interoperable network Common Data Form (netCDF) files containing all the needed information for accuracy‐of‐use, rightful attribution (ensuring data providers keep ownership through the entire process) and data preservation security. We show the standardisation benefits for all stakeholders involved, and illustrate the application of our framework by focusing on marine animals and by providing examples of the workflow across all data levels, including filled templates and code to process data between levels, as well as templates to prepare netCDF files ready for sharing. Adoption of our framework will facilitate collection of Essential Ocean Variables (EOVs) in support of the Global Ocean Observing System (GOOS) and inter‐governmental assessments (e.g. the World Ocean Assessment), and will provide a starting point for broader efforts to establish interoperable bio‐logging data formats across all fields in animal ecology

Long-term monitoring of tropical bats for anthropogenic impact assessment : gauging the statistical power to detect population change

Bats are ecologically important mammals in tropical ecosystems; however, their populations face numerous environmental threats related to climate change, habitat loss, fragmentation, hunting, and emerging diseases. Thus, there is a pressing need to develop and implement large-scale networks to monitor trends in bat populations over extended time periods. Using data from a range of Neotropical and Paleotropical bat assemblages, we assessed the ability for long-term monitoring programs to reliably detect temporal trends in species abundance. We explored the magnitude of within-site temporal variation in abundance and evaluated the statistical power of a suite of different sampling designs for several different bat species and ensembles. Despite pronounced temporal variation in abundance of most tropical bat species, power simulations suggest that long-term monitoring programs (⩾20 years) can detect population trends of 5% per year or more with adequate statistical power (⩾0.9). However, shorter monitoring programs (⩽10 years) have insufficient power for trend detection. Overall, our analyses demonstrate that a monitoring program extending over 20 years with four surveys conducted biennially on five plots per monitoring site would have the potential for detecting a 5% annual change in abundance for a suite of bat species from different ensembles. The likelihood of reaching adequate statistical power was sensitive to initial species abundance and the magnitude of count variation, stressing that only the most abundant species in an assemblage and those with generally low variation in abundance should be considered for detailed population monitoring

A standardisation framework for bio-logging data to advance ecological research and conservation

Funding: AMMS was funded by a 2020 Pew Fellowship in Marine Conservation, ARC DE170100841, and also supported by AIMS. CR was the recipient of a Radcliffe Fellowship at the Radcliffe Institute for Advanced Study, Harvard University.Bio-logging data obtained by tagging animals is key to addressing global conservation challenges. However, the many thousands of existing bio-logging datasets are not easily discoverable, universally comparable, nor readily accessible through existing repositories and across platforms. This slows down ecological research and effective management. A set of universal standards is needed to ensure discoverability, interoperability, and effective translation of bio-logging data into research and management recommendations. We propose a standardisation framework adhering to existing data principles (FAIR: Findable, Accessible, Interoperable, and Reusable; and TRUST: Transparency, Responsibility, User focus, Sustainability and Technology) and involving the use of simple templates to create a data flow from manufacturers and researchers to compliant repositories, where automated procedures should be in place to prepare data availability into four standardised levels: (i) decoded raw data, (ii) curated data, (iii) interpolated data, and (iv) gridded data. Our framework allows for integration of simple tabular arrays (e.g., csv files) and creation of sharable and interoperable network Common Data Form (netCDF) files containing all the needed information for accuracy-of-use, rightful attribution (ensuring data providers keep ownership through the entire process), and data preservation security. We show the standardisation benefits for all stakeholders involved, and illustrate the application of our framework by focusing on marine animals and by providing examples of the workflow across all data levels, providing data examples, including filled templates and code to process data between levels, as well as templates to prepare netCDF files ready for sharing. Adoption of our framework will facilitate collection of Essential Ocean Variables (EOVs) in support of the Global Ocean Observing System (GOOS) and inter-governmental assessments (e.g., the World Ocean Assessment), and will provide a starting point for broader efforts to establish interoperable bio-logging data formats across all fields in animal ecology.Publisher PDFPeer reviewe

Circulating microRNAs in sera correlate with soluble biomarkers of immune activation but do not predict mortality in ART treated individuals with HIV-1 infection: A case control study

10.1371/journal.pone.0139981PLoS ONE1010e013998