The discovery of the 2012 extreme melt event across almost the entire surface of the Greenland ice sheet is presented. Data from three different satellite sensors – including the Oceansat‐2 scatterometer, the Moderate‐resolution Imaging Spectroradiometer, and the Special Sensor Microwave Imager/Sounder – are combined to obtain composite melt maps, representing the most complete melt conditions detectable across the ice sheet. Satellite observations reveal that melt occurred at or near the surface of the Greenland ice sheet across 98.6% of its entire extent on 12 July 2012, including the usually cold polar areas at high altitudes like Summit in the dry snow facies of the ice sheet. This melt event coincided with an anomalous ridge of warm air that became stagnant over Greenland. As seen in melt occurrences from multiple ice core records at Summit reported in the published literature, such a melt event is rare with the last significant one occurring in 1889 and the next previous one around seven centuries earlier in the Medieval Warm Period. Given its rarity, the 2012 extreme melt across Greenland provides an exceptional opportunity for new studies in broad interdisciplinary geophysical research.
Circadian clocks drive rhythmic behaviour in animals and are regulated by transcriptional feedback loops. For example, the Drosophila proteins Clock (Clk) and Cycle (Cyc) activate transcription of period (per) and timeless (tim). Per and Tim then associate, translocate to the nucleus, and repress the activity of Clk and Cyc. However, post-translational modifications are also critical to proper timing. Per and Tim undergo rhythmic changes in phosphorylation, and evidence supports roles for two kinases in this process: Doubletime (Dbt) phosphorylates Per, whereas Shaggy (Sgg) phosphorylates Tim. Yet Sgg and Dbt often require a phosphoserine in their target site, and analysis of Per phosphorylation in dbt mutants suggests a role for other kinases. Here we show that the catalytic subunit of Drosophila casein kinase 2 (CK2alpha) is expressed predominantly in the cytoplasm of key circadian pacemaker neurons. CK2alpha mutant flies show lengthened circadian period, decreased CK2 activity, and delayed nuclear entry of Per. These effects are probably direct, as CK2alpha specifically phosphorylates Per in vitro. We propose that CK2 is an evolutionary link between the divergent circadian systems of animals, plants and fungi.
The fruitfly, Drosophila melanogaster, exhibits many of the cardinal features of sleep, yet little is known about the neural circuits governing its sleep. Here we have performed a screen of GAL4 lines expressing a temperature-sensitive synaptic blocker shibire(ts1) (ref. 2) in a range of discrete neural circuits, and assayed the amount of sleep at different temperatures. We identified three short-sleep lines at the restrictive temperature with shared expression in the mushroom bodies, a neural locus central to learning and memory. Chemical ablation of the mushroom bodies also resulted in reduced sleep. These studies highlight a central role for the mushroom bodies in sleep regulation.
Approaches in molecular biology, particularly those that deal with high-throughput sequencing of entire microbial communities (the field of metagenomics), are rapidly advancing our understanding of the composition and functional content of microbial communities involved in climate change, environmental pollution, human health, biotechnology, etc. Metagenomics provides researchers with the most complete picture of the taxonomic (i.e., what organisms are there) and functional (i.e., what are those organisms doing) composition of natively sampled microbial communities, making it possible to perform investigations that include organisms that were previously intractable to laboratory-controlled culturing; currently, these constitute the vast majority of all microbes on the planet. All organisms contained in environmental samples are sequenced in a culture-independent manner, most often with 16S ribosomal amplicon methods to investigate the taxonomic or whole-genome shotgun-based methods to investigate the functional content of sampled communities. Metagenomics allows researchers to characterize the community composition and functional content of microbial communities, but it cannot show which functional processes are active; however, near parallel developments in transcriptomics promise a dramatic increase in our knowledge in this area as well. Since 2008, MG-RAST (Meyer et al., BMC Bioinformatics 9:386, 2008) has served as a public resource for annotation and analysis of metagenomic sequence data, providing a repository that currently houses more than 150,000 data sets (containing 60+ tera-base-pairs) with more than 23,000 publically available. MG-RAST, or the metagenomics RAST (rapid annotation using subsystems technology) server makes it possible for users to upload raw metagenomic sequence data in (preferably) fastq or fasta format. Assessments of sequence quality, annotation with respect to multiple reference databases, are performed automatically with minimal input from the user (see Subheading 4 at the end of this chapter for more details). Post-annotation analysis and visualization are also possible, directly through the web interface, or with tools like matR (metagenomic analysis tools for R, covered later in this chapter) that utilize the MG-RAST API ( http://api.metagenomics.anl.gov/api.html ) to easily download data from any stage in the MG-RAST processing pipeline. Over the years, MG-RAST has undergone substantial revisions to keep pace with the dramatic growth in the number, size, and types of sequence data that accompany constantly evolving developments in metagenomics and related -omic sciences (e.g., metatranscriptomics).
The inertial sensor system used to measure asymmetry of head and pelvic movement as an aid in the detection and evaluation of lameness in horses trotting in a straight line was sufficiently repeatable to investigate for clinical use.
A search for and the development of more objective and reliable methods of lameness evaluation is justified and should be encouraged and supported.
The soil ecosystem is critical for human health, affecting aspects of the environment from key agricultural and edaphic parameters to critical influence on climate change. Soil has more unknown biodiversity than any other ecosystem. We have applied diverse DNA extraction methods coupled with high throughput pyrosequencing to explore 4.88 Â 10 9 bp of metagenomic sequence data from the longest continually studied soil environment (Park Grass experiment at Rothamsted Research in the UK). Results emphasize important DNA extraction biases and unexpectedly low seasonal and vertical soil metagenomic functional class variations. Clustering-based subsystems and carbohydrate metabolism had the largest quantity of annotated reads assigned although o50% of reads were assigned at an E value cutoff of 10 À5. In addition, with the more detailed subsystems, cAMP signaling in bacteria (3.24±0.27% of the annotated reads) and the Ton and Tol transport systems (1.69±0.11%) were relatively highly represented. The most highly represented genome from the database was that for a Bradyrhizobium species. The metagenomic variance created by integrating natural and methodological fluctuations represents a global picture of the Rothamsted soil metagenome that can be used for specific questions and future inter-environmental metagenomic comparisons. However, only 1% of annotated sequences correspond to already sequenced genomes at 96% similarity and E values of o10 À5, thus, considerable genomic reconstructions efforts still have to be performed.
scite is a Brooklyn-based startup that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2023 scite Inc. All rights reserved.
Made with 💙 for researchers