Multistage and transmission-blocking targeted antimalarials discovered from the open-source MMV Pandemic Response Box

Chemical matter is needed to target the divergent biology associated with the different life cycle stages of Plasmodium. Here, we report the parallel de novo screening of the Medicines for Malaria Venture (MMV) Pandemic Response Box against Plasmodium asexual and liver stage parasites, stage IV/V gametocytes, gametes, oocysts and as endectocides. Unique chemotypes were identified with both multistage activity or stage-specific activity, including structurally diverse gametocyte-targeted compounds with potent transmission-blocking activity, such as the JmjC inhibitor ML324 and the antitubercular clinical candidate SQ109. Mechanistic investigations prove that ML324 prevents histone demethylation, resulting in aberrant gene expression and death in gametocytes. Moreover, the selection of parasites resistant to SQ109 implicates the druggable V-type H+-ATPase for the reduced sensitivity. Our data therefore provides an expansive dataset of compounds that could be redirected for antimalarial development and also point towards proteins that can be targeted in multiple parasite life cycle stages.Supplementary Data 1: Data of the supra-hexagonal plot in Figure 2ASupplementary Data 2: Complete dataset of all MMV PRB compounds’ activity on Plasmodium life cycle stagesSupplementary Data 3: Full SMFA dataset to support Figure 5CSupplementary Data 4: Transcriptome analysis of MMV1580488 (ML324) treated parasites to support Figure 6C.The Medicines for Malaria Venture and South African Technology Innovation Agency (TIA). This project was in part supported by the South African Medical Research Council with funds received from the South African Department of Science and Innovation, in partnership with the Medicines for Malaria Venture; and the DST/NRF South African Research Chairs Initiative Grant; and CSIR Parliamentary Grant funding as well as the Bill and Melinda Gates Foundation and the Australian NHMRC (APP1072217).http://www.nature.com/ncommshj2021BiochemistryGeneticsMicrobiology and Plant PathologyUP Centre for Sustainable Malaria Control (UP CSMC

Dynamical seasonal ocean forecasts to aid salmon farm management in a climate hotspot

AbstractMarine aquaculture businesses are subject to a range of environmental conditions that can impact on day to day operations, the health of the farmed species, and overall production. An understanding of future environmental conditions can assist marine resource users plan their activities, minimise risks due to adverse conditions, and maximise opportunities. Short-term farm management is assisted by weather forecasts, but longer term planning may be hampered by an absence of useful climate information at relevant spatial and temporal scales. Here we use dynamical seasonal forecasts to predict water temperatures for south-east Tasmanian Atlantic salmon farm sites several months into the future. High summer temperatures pose a significant risk to production systems of these farms. Based on twenty years of historical validation, the model shows useful skill (i.e., predictive ability) for all months of the year at lead-times of 0–1months. Model skill is highest when forecasting for winter months, and lowest for December and January predictions. The poorer performance in summer may be due to increased variability due to the convergence of several ocean currents offshore from the salmon farming region. Accuracy of probabilistic forecasts exceeds 80% for all months at lead-time 0months for the upper tercile (warmest 33% of values) and exceeds 50% at a lead-time of 3months. This analysis shows that useful information on future ocean conditions up to several months into the future can be provided for the salmon aquaculture industry in this region. Similar forecasting techniques can be applied to other marine industries such as wild fisheries and pond aquaculture in other regions. This future knowledge will enhance environment-related decision making of marine managers and increase industry resilience to climate variability

ISBN:

seasonal prediction website

Subseasonal prediction of the 2020 Great Barrier Reef and Coral Sea marine heatwave

The 2020 marine heatwave (MHW) in the Great Barrier Reef (GBR) and Coral Sea led to mass coral bleaching. Sea surface temperature anomalies reached +1.7 °C for the whole of the GBR and Coral Sea and exceeded +2 °C across broad regions (referenced to 1990–2012). The MHW reached Category 2 (Strong) and warm anomalies peaked between mid-February and mid-March 2020. The MHW’s peak intensity aligned with regions of reduced cloud cover and weak wind speeds. We used a MHW framework to assess the ability of an operational coupled ocean-atmosphere prediction system (Australian Community Climate and Earth System Simulator Seasonal version 1) to capture the MHW’s severity, duration, and spatial extent. For initial week predictions, the predicted MHW severity generally agreed with the magnitude and spatial extent of the observed severity for that week. The model ensemble mean did not capture the MHW’s development phase at lead times beyond the first week. The model underestimated the MHW’s spatial extent, which reached up to 95% of the study area with at least Moderate severity and up to 43% with at least Strong severity. However, most forecast ensemble members correctly predicted the period of Strong severity in the first week of the model forecast. The model correctly predicted MHW conditions to persist from mid-February to mid-March but did not capture the end of the MHW. The inability to predict the end of the event and other periods of less skilful prediction were related to subseasonal variability owing to weather systems, including the passage of tropical cyclones not simulated in the model. On subseasonal time scale, evaluating daily to weekly forecasts of ocean temperature extremes is an important step toward implementing methods for developing operational forecast extremes products for use in early warning systems

Climate change and carbon threats to coral reefs: national meteorological and ocean services as sentinels

[Extract] The preservation of coral reefs under a changing climate requires a coordinated approach that integrates observational, experimental, and modeling efforts with practical management and sound government policy. Coral reefs are among the most species-rich habitats in the world, but also among the most vulnerable to our current high-emission path. Observations of the climate system have shown an increase in global average surface temperature during the twentieth century, with an increased rate of warming since 1950

A Framework for Combining Seasonal Forecasts and Climate Projections to Aid Risk Management for Fisheries and Aquaculture

A changing climate, in particular a warming ocean, is likely to impact marine industries in a variety of ways. For example, aquaculture businesses may not be able to maintain production in their current location into the future, or area-restricted fisheries may need to follow the fish as they change distribution. Preparation for these potential climate impacts can be improved with information about the future. Such information can support a risk-based management strategy for industries exposed to both short-term environmental variability and long-term change. In southern Australia, adverse climate impacts on valuable seafood industries have occurred, and they are now seeking advice about future environmental conditions. We introduce a decision tree to explain the potential use of long-term climate projections and seasonal forecasts by these industries. Climate projections provide insight into the likely time in the future when current locations will no longer be suitable for growing or catching particular species. Until this time, seasonal forecasting is beneficial in helping industries plan ahead to reduce impacts in poor years and maximize opportunities in good years. Use of seasonal forecasting can extend the period of time in which industries can cope in a location as environmental suitability declines due to climate change. While a range of short-term forecasting approaches exist, including persistence and climatological forecasts, only dynamic model forecasts provide a viable option for managing environmental risk for marine industries in regions where climate change is reducing environmental suitability and creating novel conditions

Improved capabilities of global ocean reanalyses for analysing sea level variability near the Atlantic and Gulf of Mexico Coastal U.S.

Realistic representation of monthly sea level anomalies in coastal regions has been a challenge for global ocean reanalyses. This is especially the case in coastal regions where sea levels are influenced by western boundary currents such as near the U.S. Atlantic Coast and the Gulf of Mexico. For these regions, most ocean reanalyses compare poorly to observations. Problems in reanalyses include errors in data assimilation and horizontal resolutions that are too coarse to simulate energetic currents like the Gulf Stream and Loop Current System. However, model capabilities are advancing with improved data assimilation and higher resolution. Here, we show that some current-generation ocean reanalyses produce monthly sea level anomalies with improved skill when compared to satellite altimetry observations of sea surface heights. Using tide gauge observations for coastal verification, we find the highest skill associated with the GLORYS12 and HYCOM ocean reanalyses. Both systems assimilate altimetry observations and have eddy-resolving horizontal resolutions (1/12°). We found less skill in three other ocean reanalyses (ACCESS-S2, ORAS5, and ORAP6) with coarser, though still eddy-permitting, resolutions (1/4°). The operational reanalysis from ECMWF (ORAS5) and their pilot reanalysis (ORAP6) provide an interesting comparison because the latter assimilates altimetry globally and with more weight, as well as assimilating ocean observations over continental shelves. We find these attributes associated with improved skill near many tide gauges. We also assessed an older reanalysis (CFSR), which has the lowest skill likely due to its lower resolution (1/2°) and lack of altimetry assimilation. ACCESS-S2 likewise does not assimilate altimetry, although its skill is much better than CFSR and only somewhat lower than ORAS5. Since coastal flooding is influenced by sea level anomalies, the recent development of skilful ocean reanalyses on monthly timescales may be useful for better understanding the physical processes associated with flood risks