Arctic sea ice thickness variability and change

Arctic sea ice thickness variability and change and their dependence on the atmospheric and oceanic forcing are at the core of research in Subtopic 2.1, Theme: Ongoing and Future Arctic and Antarctic Climate Change. Our research is particularly focused on a better process understanding and representation in models, and observations during MOSAiC play a strong role. The poster gives examples of such process studies focused on Arctic sea ice thickness variability and change. We outline observations of the long-term and regional variability and change of sea ice thickness using satellite remote sensing, airborne surveying, and ice mass balance buoys. Thermodynamic growth and its interaction with the atmosphere over leads and level ice serves as an example for our joint research interests. The poster also gives examples of causes of sea ice thinning, like increased ocean heat flux to the ice due to Atlantification, and consequences, e.g., for reduced sea ice volume transport through Fram Strait

Editorial: Ecology, Metabolism and Evolution of Archaea-Perspectives From Proceedings of the International Workshop on Geo-Omics of Archaea

To facilitate global efforts in addressing fundamental questions related to the biology of archaea, an international consortium of experts organized the International Workshop on Geo-Omics of Archaea (IWGOA), with the overarching themes of Ecology/Biogeochemistry, Metabolism, and Evolution. The IWGOA was held in Shenzhen, China, from October 25th to 27th, 2019. The meeting was attended by more than 200 attendees from China, Japan, USA, Australia, Germany, and France. Some of the most exciting oral and poster presentations made at the IWGOA are celebrated in this Research Topic Figure 1. The 21 manuscripts herein span different aspects of archaeal biology in both extreme and “non-extreme” environments in both marine and terrestrial settings and use a variety of approaches—community ecology, environmental lipidomics and genomics, organismal biology, and nucleic acid biochemistry—embodying diverse research thrusts that makes archaeal biology so exciting. At the same time, the manuscripts include over 100 authors from Asia, North America, and Europe, realizing our goal to engage a global audience in the biology of archaea

Dr. Strangelove, or how I learned to stop worrying and love the drone: A review of current debates on drone applications

Drohnen werden inzwischen in vielen und sehr unterschiedlichen Kontexten verwendet. Aus dem Blickwinkel der Technikfolgenabschätzung scheint es daher sinnvoll, den Umfang der momentanen und zukünftigen Nutzung von Drohnen und daraus resultierende Implikationen näher zu beleuchten und eine Bestandsaufnahme durchzuführen. Darüber hinaus sollen die voraussichtlichen Pfade der weiteren Technikentwicklung, relevante Akteure und deren Interessenslage sowie zukünftige Anwendungspotenziale und Einsatzfelder analysiert werden.Drones are nowadays used in many and very different contexts. From the technology assessment perspective, it therefore seems reasonable to shed more light on the extent of the current and future use of drones and the resulting consequences. In addition, the expected paths of further technological development, relevant actors and their interests as well as potential future applications and fields of use should be analyzed

ProDeGe: a computational protocol for fully automated decontamination of genomes

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies. On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). The procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence

acdc – Automated Contamination Detection and Confidence estimation for single-cell genome data

Lux M, Krüger J, Rinke C, et al. acdc – Automated Contamination Detection and Confidence estimation for single-cell genome data. BMC Bioinformatics. 2016;17(1): 543.Background A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data. Results We present acdc, a tool specifically developed to aid the quality control process of genomic sequence data. By combining supervised and unsupervised methods, it reliably detects both known and de novo contaminants. First, 16S rRNA gene prediction and the inclusion of ultrafast exact alignment techniques allow sequence classification using existing knowledge from databases. Second, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction of oligonucleotide signatures and subsequent clustering algorithms that automatically estimate the number of clusters. The latter also enables the removal of any contaminant, yielding a clean sample. Furthermore, given the data complexity and the ill-posedness of clustering, acdc employs bootstrapping techniques to provide statistically profound confidence values. Tested on a large number of samples from diverse sequencing projects, our software is able to quickly and accurately identify contamination. Results are displayed in an interactive user interface. Acdc can be run from the web as well as a dedicated command line application, which allows easy integration into large sequencing project analysis workflows. Conclusions Acdc can reliably detect contamination in single-cell genome data. In addition to database-driven detection, it complements existing tools by its unsupervised techniques, which allow for the detection of de novo contaminants. Our contribution has the potential to drastically reduce the amount of resources put into these processes, particularly in the context of limited availability of reference species. As single-cell genome data continues to grow rapidly, acdc adds to the toolkit of crucial quality assurance tools

Comparative Genomic Analysis of the Class \u3ci\u3eEpsilonproteobacteria\u3c/i\u3e and Proposed Reclassification to Epsilonbacteraeota (phyl. nov.)

The Epsilonproteobacteria is the fifth validly described class of the phylum Proteobacteria, known primarily for clinical relevance and for chemolithotrophy in various terrestrial and marine environments, including deep-sea hydrothermal vents. As 16S rRNA gene repositories have expanded and protein marker analysis become more common, the phylogenetic placement of this class has become less certain. A number of recent analyses of the bacterial tree of life using both 16S rRNA and concatenated marker gene analyses have failed to recover the Epsilonproteobacteria as monophyletic with all other classes of Proteobacteria. In order to address this issue, we investigated the phylogenetic placement of this class in the bacterial domain using 16S and 23S rRNA genes, as well as 120 single-copy marker proteins. Single- and concatenated-marker trees were created using a data set of 4,170 bacterial representatives, including 98 Epsilonproteobacteria. Phylogenies were inferred under a variety of tree building methods, with sequential jackknifing of outgroup phyla to ensure robustness of phylogenetic affiliations under differing combinations of bacterial genomes. Based on the assessment of nearly 300 phylogenetic tree topologies, we conclude that the continued inclusion of Epsilonproteobacteria within the Proteobacteria is not warranted, and that this group should be reassigned to a novel phylum for which we propose the name Epsilonbacteraeota (phyl. nov.). We further recommend the reclassification of the order Desulfurellales (Deltaproteobacteria) to a novel class within this phylum and a number of subordinate changes to ensure consistency with the genome-based phylogeny. Phylogenomic analysis of 658 genomes belonging to the newly proposed Epsilonbacteraeota suggests that the ancestor of this phylum was an autotrophic, motile, thermophilic chemolithotroph that likely assimilated nitrogen from ammonium taken up from the environment or generated from environmental nitrate and nitrite by employing a variety of functional redox modules. The emergence of chemoorganoheterotrophic lifestyles in several Epsilonbacteraeota families is the result of multiple independent losses of various ancestral chemolithoautotrophic pathways. Our proposed reclassification of this group resolves an important anomaly in bacterial systematics and ensures that the taxonomy of Proteobacteria remains robust, specifically as genome-based taxonomies become more common

ASXL1 mutations predict inferior molecular response to nilotinib treatment in chronic myeloid leukemia

Gene mutations independent of BCR::ABL1 have been identified in newly diagnosed patients with chronic myeloid leukemia (CML) in chronic phase, whereby mutations in epigenetic modifier genes were most common. These findings prompted the systematic analysis of prevalence, dynamics, and prognostic significance of such mutations, in a clinically well-characterized patient population of 222 CML patients from the TIGER study (CML-V) by targeted next-generation sequencing covering 54 myeloid leukemia-associated genes. In total, 53/222 CML patients (24%) carried 60 mutations at diagnosis with ASXL1 being most commonly affected (n = 20). To study mutation dynamics, longitudinal deep sequencing analysis of serial samples was performed in 100 patients after 12, 24, and 36 months of therapy. Typical patterns of clonal evolution included eradication, persistence, and emergence of mutated clones. Patients carrying an ASXL1 mutation at diagnosis showed a less favorable molecular response to nilotinib treatment, as a major molecular response (MMR) was achieved less frequently at month 12, 18, and 24 compared to all other patients. Patients with ASXL1 mutations were also younger and more frequently found in the high risk category, suggesting a central role of clonal evolution associated with ASXL1 mutations in CML pathogenesis

Decontamination of MDA Reagents for Single Cell Whole Genome Amplification

Single cell genomics is a powerful and increasingly popular tool for studying the genetic make-up of uncultured microbes. A key challenge for successful single cell sequencing and analysis is the removal of exogenous DNA from whole genome amplification reagents. We found that UV irradiation of the multiple displacement amplification (MDA) reagents, including the Phi29 polymerase and random hexamer primers, effectively eliminates the amplification of contaminating DNA. The methodology is quick, simple, and highly effective, thus significantly improving whole genome amplification from single cells