Genomic signatures of population decline in the malaria mosquito Anopheles gambiae

Population genomic features such as nucleotide diversity and linkage disequilibrium are expected to be strongly shaped by changes in population size, and might therefore be useful for monitoring the success of a control campaign. In the Kilifi district of Kenya, there has been a marked decline in the abundance of the malaria vector Anopheles gambiae subsequent to the rollout of insecticide-treated bed nets. To investigate whether this decline left a detectable population genomic signature, simulations were performed to compare the effect of population crashes on nucleotide diversity, Tajima's D, and linkage disequilibrium (as measured by the population recombination parameter ρ). Linkage disequilibrium and ρ were estimated for An. gambiae from Kilifi, and compared them to values for Anopheles arabiensis and Anopheles merus at the same location, and for An. gambiae in a location 200 km from Kilifi. In the first simulations ρ changed more rapidly after a population crash than the other statistics, and therefore is a more sensitive indicator of recent population decline. In the empirical data, linkage disequilibrium extends 100-1000 times further, and ρ is 100-1000 times smaller, for the Kilifi population of An. gambiae than for any of the other populations. There were also significant runs of homozygosity in many of the individual An. gambiae mosquitoes from Kilifi. These results support the hypothesis that the recent decline in An. gambiae was driven by the rollout of bed nets. Measuring population genomic parameters in a small sample of individuals before, during and after vector or pest control may be a valuable method of tracking the effectiveness of interventions

Synthesizing multi-sensor, multi-satellite, multi-decadal datasets for global volcano monitoring

Owing to practical limitations less than half of Earth's 1400 subaerial volcanoes have no ground monitoring and few are monitored consistently. Earth-observing satellite missions provide global and frequent measurements of volcanic activity that are closing these gaps in coverage. We compare databases of global, satellite-detections of ground deformation (1992–2016), SO₂ emissions (1978–2016), and thermal features (2000–2016) that together include 306 volcanoes. Each database has limitations in terms of spatial and temporal resolution but each technique contributed 45–86 unique detections of activity that were not detected by other techniques. Integration of these three databases shows that satellites detected ~10² volcanic activities per year before the year 2000 and ~103 activities per year after the year 2000. We find that most of the 54 erupting volcanoes without satellite-detections are associated with low volcano explosivity index eruptions and note that many of these eruptions (71%, 97/135) occurred in the earliest decades of remote sensing (pre-2000) when detection thresholds were high. From 1978 to 2016 we conduct a preliminary analysis of the timing between the onset of satellite-detections of deformation (N = 154 episodes, N = 71 volcanoes), thermal features (N = 16,544 episodes, N = 99 volcanoes), and SO₂ emissions (N = 1495 episodes, N = 116 volcanoes) to eruption start dates. We analyze these data in two ways: first, including all satellite-detected volcanic activities associated with an eruption; and second, by considering only the first satellite-detected activity related to eruption. In both scenarios, we find that deformation is dominantly pre-eruptive (47% and 57%) whereas available databases of thermal features and SO₂ emissions utilizing mainly low-resolution sensors are dominantly co-eruptive (88% and 76% for thermal features, 97% and 96% for SO₂ emissions)

Gastrin-induced miR-222 promotes gastric tumor development by suppressing p27kip1

Background and aims Elevated circulating concentrations of the hormone gastrin contribute to the development of gastric adenocarcinoma and types-1 and 2 gastric neuroendocrine tumors (NETs). MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate proteins which in turn influence various biological processes. We hypothesised that gastrin induces the expression of specific gastric miRNAs within CCK2 receptor (CCK2R) expressing cells and that these mediate functionally important actions of gastrin.Results Gastrin increased miR-222 expression in AGSGR cells, with maximum changes observed at 10 nM G17 for 24 h. Signalling occurred via CCK2R and the PKC and PI3K pathways. miR-222 expression was increased in the serum and gastric corpus mucosa of hypergastrinemic INS-GAS mice and hypergastrinemic patients with autoimmune atrophic gastritis and type 1 gastric NETs; it decreased in patients following treatment with the CCK2R antagonist netazepide (YF476). Gastrin-induced miR-222 overexpression resulted in reduced expression and cytoplasmic mislocalisation of p27kip1, which in turn caused actin remodelling and increased migration in AGSGR cells. Materials and methods miRNA PCR arrays were used to identify changes in miRNA expression following G17 treatment of human gastric adenocarcinoma cells stably transfected with CCK2R (AGSGR). miR-222 was further investigated using primer assays and samples from hypergastrinemic mice and humans. Chemically synthesised mimics and inhibitors were used to assess cellular phenotypical changes associated with miR-222 dysregulation.Conclusions These data indicate a novel mechanism contributing to gastrin-associated gastric tumor development. miR-222 may also be a promising biomarker for monitoring gastrin induced premalignant changes in the stomach

Microevolution of Helicobacter pylori during prolonged infection of single hosts and within families

Our understanding of basic evolutionary processes in bacteria is still very limited. For example, multiple recent dating estimates are based on a universal inter-species molecular clock rate, but that rate was calibrated using estimates of geological dates that are no longer accepted. We therefore estimated the short-term rates of mutation and recombination in Helicobacter pylori by sequencing an average of 39,300 bp in 78 gene fragments from 97 isolates. These isolates included 34 pairs of sequential samples, which were sampled at intervals of 0.25 to 10.2 years. They also included single isolates from 29 individuals (average age: 45 years) from 10 families. The accumulation of sequence diversity increased with time of separation in a clock-like manner in the sequential isolates. We used Approximate Bayesian Computation to estimate the rates of mutation, recombination, mean length of recombination tracts, and average diversity in those tracts. The estimates indicate that the short-term mutation rate is 1.4×10−6 (serial isolates) to 4.5×10−6 (family isolates) per nucleotide per year and that three times as many substitutions are introduced by recombination as by mutation. The long-term mutation rate over millennia is 5–17-fold lower, partly due to the removal of non-synonymous mutations due to purifying selection. Comparisons with the recent literature show that short-term mutation rates vary dramatically in different bacterial species and can span a range of several orders of magnitude

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

A mammalian functional-genetic approach to characterizing cancer therapeutics

Supplementary information is available online at http://www.nature.com/naturechemicalbiology/. Reprints and permissions information is available online at http://npg.nature.com/reprintsandpermissions/.Identifying mechanisms of drug action remains a fundamental impediment to the development and effective use of chemotherapeutics. Here we describe an RNA interference (RNAi)–based strategy to characterize small-molecule function in mammalian cells. By examining the response of cells expressing short hairpin RNAs (shRNAs) to a diverse selection of chemotherapeutics, we could generate a functional shRNA signature that was able to accurately group drugs into established biochemical modes of action. This, in turn, provided a diversely sampled reference set for high-resolution prediction of mechanisms of action for poorly characterized small molecules. We could further reduce the predictive shRNA target set to as few as eight genes and, by using a newly derived probability-based nearest-neighbors approach, could extend the predictive power of this shRNA set to characterize additional drug categories. Thus, a focused shRNA phenotypic signature can provide a highly sensitive and tractable approach for characterizing new anticancer drugs.National Institute of Mental Health (U.S.) (grant RO1 CA128803-03)American Association for Cancer ResearchMassachusetts Institute of Technology. Dept. of BiologyNational Cancer Institute (U.S.). Integrative Cancer Biology Program (grant 1-U54-CA112967

Prospective validation of the 4C prognostic models for adults hospitalised with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol

Purpose: To prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19. // Methods: Prospective observational cohort study of adults (age ≥18 years) with confirmed or highly suspected COVID-19 recruited into the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study in 306 hospitals across England, Scotland and Wales. Patients were recruited between 27 August 2020 and 17 February 2021, with at least 4 weeks follow-up before final data extraction. The main outcome measures were discrimination and calibration of models for in-hospital deterioration (defined as any requirement of ventilatory support or critical care, or death) and mortality, incorporating predefined subgroups. // Results: 76 588 participants were included, of whom 27 352 (37.4%) deteriorated and 12 581 (17.4%) died. Both the 4C Mortality (0.78 (0.77 to 0.78)) and 4C Deterioration scores (pooled C-statistic 0.76 (95% CI 0.75 to 0.77)) demonstrated consistent discrimination across all nine National Health Service regions, with similar performance metrics to the original validation cohorts. Calibration remained stable (4C Mortality: pooled slope 1.09, pooled calibration-in-the-large 0.12; 4C Deterioration: 1.00, –0.04), with no need for temporal recalibration during the second UK pandemic wave of hospital admissions. // Conclusion: Both 4C risk stratification models demonstrate consistent performance to predict clinical deterioration and mortality in a large prospective second wave validation cohort of UK patients. Despite recent advances in the treatment and management of adults hospitalised with COVID-19, both scores can continue to inform clinical decision making

Genome sequencing of the extinct Eurasian wild aurochs, Bos primigenius, illuminates the phylogeography and evolution of cattle

Background Domestication of the now-extinct wild aurochs, Bos primigenius, gave rise to the two major domestic extant cattle taxa, B. taurus and B. indicus. While previous genetic studies have shed some light on the evolutionary relationships between European aurochs and modern cattle, important questions remain unanswered, including the phylogenetic status of aurochs, whether gene flow from aurochs into early domestic populations occurred, and which genomic regions were subject to selection processes during and after domestication. Here, we address these questions using whole-genome sequencing data generated from an approximately 6,750-year-old British aurochs bone and genome sequence data from 81 additional cattle plus genome-wide single nucleotide polymorphism data from a diverse panel of 1,225 modern animals. Results Phylogenomic analyses place the aurochs as a distinct outgroup to the domestic B. taurus lineage, supporting the predominant Near Eastern origin of European cattle. Conversely, traditional British and Irish breeds share more genetic variants with this aurochs specimen than other European populations, supporting localized gene flow from aurochs into the ancestors of modern British and Irish cattle, perhaps through purposeful restocking by early herders in Britain. Finally, the functions of genes showing evidence for positive selection in B. taurus are enriched for neurobiology, growth, metabolism and immunobiology, suggesting that these biological processes have been important in the domestication of cattle. Conclusions This work provides important new information regarding the origins and functional evolution of modern cattle, revealing that the interface between early European domestic populations and wild aurochs was significantly more complex than previously thought

The periodic topography of ice stream beds: Insights from the Fourier spectra of mega-scale glacial lineations

Ice stream bed topography contains key evidence for the ways ice streams interact with, and are potentially controlled by, their beds. Here we present the first application of two-dimensional Fourier analysis to 22 marine and terrestrial topographies from 5 regions in Antarctica and Canada, with and without mega-scale glacial lineations (MSGLs). We find that the topography of MSGL-rich ice stream sedimentary beds is characterized by multiple, periodic wavelengths between 300 and 1200 m and amplitudes from decimeters to a few meters. This periodic topography is consistent with the idea that instability is a key element to the formation of MSGL bedforms. Dominant wavelengths vary among locations and, on one paleo ice stream bed, increase along the direction of ice flow by 1.7 ± 0.52% km−1. We suggest that these changes are likely to reflect pattern evolution via downstream wavelength coarsening, even under potentially steady ice stream geometry and flow conditions. The amplitude of MSGLs is smaller than that of other fluvial and glacial topographies but within the same order of magnitude. However, MSGLs are a striking component of ice stream beds because the topographic amplitude of features not aligned with ice flow is reduced by an order of magnitude relative to those oriented with the flow direction. This study represents the first attempt to automatically derive the spectral signatures of MSGLs. It highlights the plausibility of identifying these landform assemblages using automated techniques and provides a benchmark for numerical models of ice stream flow and subglacial landscape evolution.The research was funded by the NE/J004766/1 UK NERC New Investigator and a SAGES 728 PECRE grants awarded to MS

Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study

BACKGROUND: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. METHODS: We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal-external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). FINDINGS: 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal-external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [-0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. INTERPRETATION: The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19. FUNDING: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London