Showing papers by "Technical University of Denmark published in 2017"

Combining theory and experiment in electrocatalysis: Insights into materials design

Abstract: BACKGROUND With a rising global population, increasing energy demands, and impending climate change, major concerns have been raised over the security of our energy future. Developing sustainable, fossil-free pathways to produce fuels and chemicals of global importance could play a major role in reducing carbon dioxide emissions while providing the feedstocks needed to make the products we use on a daily basis. One prospective goal is to develop electrochemical conversion processes that can convert molecules in the atmosphere (e.g., water, carbon dioxide, and nitrogen) into higher-value products (e.g., hydrogen, hydrocarbons, oxygenates, and ammonia) by coupling to renewable energy. Electrocatalysts play a key role in these energy conversion technologies because they increase the rate, efficiency, and selectivity of the chemical transformations involved. Today’s electrocatalysts, however, are inadequate. The grand challenge is to develop advanced electrocatalysts with the enhanced performance needed to enable widespread penetration of clean energy technologies. ADVANCES Over the past decade, substantial progress has been made in understanding several key electrochemical transformations, particularly those that involve water, hydrogen, and oxygen. The combination of theoretical and experimental studies working in concert has proven to be a successful strategy in this respect, yielding a framework to understand catalytic trends that can ultimately provide rational guidance toward the development of improved catalysts. Catalyst design strategies that aim to increase the number of active sites and/or increase the intrinsic activity of each active site have been successfully developed. The field of hydrogen evolution, for example, has seen important breakthroughs over the years in the development of highly active non–precious metal catalysts in acid. Notable advancements have also been made in the design of oxygen reduction and evolution catalysts, although there remains substantial room for improvement. The combination of theory and experiment elucidates the remaining challenges in developing further improved catalysts, often involving scaling relations among reactive intermediates. This understanding serves as an initial platform to design strategies to circumvent technical obstacles, opening up opportunities and approaches to develop higher-performance electrocatalysts for a wide range of reactions. OUTLOOK A systematic framework of combining theory and experiment in electrocatalysis helps to uncover broader governing principles that can be used to understand a wide variety of electrochemical transformations. These principles can be applied to other emerging and promising clean energy reactions, including hydrogen peroxide production, carbon dioxide reduction, and nitrogen reduction, among others. Although current paradigms for catalyst development have been helpful to date, a number of challenges need to be successfully addressed in order to achieve major breakthroughs. One important frontier, for example, is the development of both experimental and computational methods that can rapidly elucidate reaction mechanisms on broad classes of materials and in a wide range of operating conditions (e.g., pH, solvent, electrolyte). Such efforts would build on current frameworks for understanding catalysis to provide the deeper insights needed to fine-tune catalyst properties in an optimal manner. The long-term goal is to continue improving the activity and selectivity of these catalysts in order to realize the prospects of using renewable energy to provide the fuels and chemicals that we need for a sustainable energy future.

Gravitational Waves and Gamma-Rays from a Binary Neutron Star Merger: GW170817 and GRB 170817A

Abstract: On 2017 August 17, the gravitational-wave event GW170817 was observed by the Advanced LIGO and Virgo detectors, and the gamma-ray burst (GRB) GRB 170817A was observed independently by the Fermi Gamma-ray Burst Monitor, and the Anti-Coincidence Shield for the Spectrometer for the International Gamma-Ray Astrophysics Laboratory. The probability of the near-simultaneous temporal and spatial observation of GRB 170817A and GW170817 occurring by chance is $5.0\times {10}^{-8}$. We therefore confirm binary neutron star mergers as a progenitor of short GRBs. The association of GW170817 and GRB 170817A provides new insight into fundamental physics and the origin of short GRBs. We use the observed time delay of $(+1.74\pm 0.05)\,{\rm{s}}$ between GRB 170817A and GW170817 to: (i) constrain the difference between the speed of gravity and the speed of light to be between $-3\times {10}^{-15}$ and $+7\times {10}^{-16}$ times the speed of light, (ii) place new bounds on the violation of Lorentz invariance, (iii) present a new test of the equivalence principle by constraining the Shapiro delay between gravitational and electromagnetic radiation. We also use the time delay to constrain the size and bulk Lorentz factor of the region emitting the gamma-rays. GRB 170817A is the closest short GRB with a known distance, but is between 2 and 6 orders of magnitude less energetic than other bursts with measured redshift. A new generation of gamma-ray detectors, and subthreshold searches in existing detectors, will be essential to detect similar short bursts at greater distances. Finally, we predict a joint detection rate for the Fermi Gamma-ray Burst Monitor and the Advanced LIGO and Virgo detectors of 0.1–1.4 per year during the 2018–2019 observing run and 0.3–1.7 per year at design sensitivity.

The Atomic Simulation Environment - A Python library for working with atoms

Abstract: The Atomic Simulation Environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simula- tions. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks. For example, a sequence of calculations may be performed with the use of a simple "for-loop" construction. Calculations of energy, forces, stresses and other quantities are performed through interfaces to many external electronic structure codes or force fields using a uniform interface. On top of this calculator interface, ASE provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.

A pathology atlas of the human cancer transcriptome

Abstract: Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

The Human Cell Atlas

Abstract: The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution

Abstract: The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies.

antiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification.

Abstract: Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the â € antibiotics and secondary metabolite analysis shell - antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules.

NetMHCpan-4.0: Improved Peptide–MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data

Abstract: Cytotoxic T cells are of central importance in the immune system's response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC class I molecules. Peptide binding to MHC molecules is the single most selective step in the Ag-presentation pathway. Therefore, in the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has attracted widespread attention. In the past, predictors of peptide-MHC interactions have primarily been trained on binding affinity data. Recently, an increasing number of MHC-presented peptides identified by mass spectrometry have been reported containing information about peptide-processing steps in the presentation pathway and the length distribution of naturally presented peptides. In this article, we present NetMHCpan-4.0, a method trained on binding affinity and eluted ligand data leveraging the information from both data types. Large-scale benchmarking of the method demonstrates an increase in predictive performance compared with state-of-the-art methods when it comes to identification of naturally processed ligands, cancer neoantigens, and T cell epitopes.

BepiPred-2.0: Improving sequence-based B-cell epitope prediction using conformational epitopes

Abstract: Antibodies have become an indispensable tool for many biotechnological and clinical applications. They bind their molecular target (antigen) by recognizing a portion of its structure (epitope) in a highly specific manner. The ability to predict epitopes from antigen sequences alone is a complex task. Despite substantial effort, limited advancement has been achieved over the last decade in the accuracy of epitope prediction methods, especially for those that rely on the sequence of the antigen only. Here, we present BepiPred-2.0 (http://www.cbs.dtu.dk/services/BepiPred/), a web server for predicting B-cell epitopes from antigen sequences. BepiPred-2.0 is based on a random forest algorithm trained on epitopes annotated from antibody-antigen protein structures. This new method was found to outperform other available tools for sequence-based epitope prediction both on epitope data derived from solved 3D structures, and on a large collection of linear epitopes downloaded from the IEDB database. The method displays results in a user-friendly and informative way, both for computer-savvy and non-expert users. We believe that BepiPred-2.0 will be a valuable tool for the bioinformatics and immunology community.

The gut microbiome in atherosclerotic cardiovascular disease

Abstract: The gut microbiota has been linked to cardiovascular diseases. However, the composition and functional capacity of the gut microbiome in relation to cardiovascular diseases have not been systematically examined. Here, we perform a metagenome-wide association study on stools from 218 individuals with atherosclerotic cardiovascular disease (ACVD) and 187 healthy controls. The ACVD gut microbiome deviates from the healthy status by increased abundance of Enterobacteriaceae and Streptococcus spp. and, functionally, in the potential for metabolism or transport of several molecules important for cardiovascular health. Although drug treatment represents a confounding factor, ACVD status, and not current drug use, is the major distinguishing feature in this cohort. We identify common themes by comparison with gut microbiome data associated with other cardiometabolic diseases (obesity and type 2 diabetes), with liver cirrhosis, and rheumatoid arthritis. Our data represent a comprehensive resource for further investigations on the role of the gut microbiome in promoting or preventing ACVD as well as other related diseases. The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease.

Microservices: Yesterday, Today, and Tomorrow

Abstract: Microservices is an architectural style inspired by service-oriented computing that has recently started gaining popularity. Before presenting the current state of the art in the field, this chapter reviews the history of software architecture, the reasons that led to the diffusion of objects and services first, and microservices later. Finally, open problems and future challenges are introduced. This survey primarily addresses newcomers to the discipline, while offering an academic viewpoint on the topic. In addition, we investigate some practical issues and point out a few potential solutions.

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Abstract: Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10-15), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10-6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10-5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.

DeepLoc: prediction of protein subcellular localization using deep learning.

Abstract: Motivation The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only. Results Here, we present a prediction algorithm using deep neural networks to predict protein subcellular localization relying only on sequence information. At its core, the prediction model uses a recurrent neural network that processes the entire protein sequence and an attention mechanism identifying protein regions important for the subcellular localization. The model was trained and tested on a protein dataset extracted from one of the latest UniProt releases, in which experimentally annotated proteins follow more stringent criteria than previously. We demonstrate that our model achieves a good accuracy (78% for 10 categories; 92% for membrane-bound or soluble), outperforming current state-of-the-art algorithms, including those relying on homology information. Availability and implementation The method is available as a web server at http://www.cbs.dtu.dk/services/DeepLoc. Example code is available at https://github.com/JJAlmagro/subcellular_localization. The dataset is available at http://www.cbs.dtu.dk/services/DeepLoc/data.php. Contact jjalma@dtu.dk.

Predicting Secretory Proteins with SignalP

Abstract: SignalP is the currently most widely used program for prediction of signal peptides from amino acid sequences. Proteins with signal peptides are targeted to the secretory pathway, but are not necessarily secreted. After a brief introduction to the biology of signal peptides and the history of signal peptide prediction, this chapter will describe all the options of the current version of SignalP and the details of the output from the program. The chapter includes a case study where the scores of SignalP were used in a novel way to predict the functional effects of amino acid substitutions in signal peptides.

Critical review on biofilm methods

Abstract: Biofilms are widespread in nature and constitute an important strategy implemented by microorganisms to survive in sometimes harsh environmental conditions. They can be beneficial or have a negative impact particularly when formed in industrial settings or on medical devices. As such, research into the formation and elimination of biofilms is important for many disciplines. Several new methodologies have been recently developed for, or adapted to, biofilm studies that have contributed to deeper knowledge on biofilm physiology, structure and composition. In this review, traditional and cutting-edge methods to study biofilm biomass, viability, structure, composition and physiology are addressed. Moreover, as there is a lack of consensus among the diversity of techniques used to grow and study biofilms. This review intends to remedy this, by giving a critical perspective, highlighting the advantages and limitations of several methods. Accordingly, this review aims at helping scientists in finding the most appropriate and up-to-date methods to study their biofilms.

Plasmonic colour generation

Abstract: Plasmonic colours are structural colours that emerge from resonant interactions between light and metallic nanostructures. The engineering of plasmonic colours is a promising, rapidly emerging research field that could have a large technological impact. We highlight basic properties of plasmonic colours and recent nanofabrication developments, comparing technology-performance indicators for traditional and nanophotonic colour technologies. The structures of interest include diffraction gratings, nanoaperture arrays, thin films, and multilayers and structures that support Mie resonances and whispering-gallery modes. We discuss plasmonic colour nanotechnology based on localized surface plasmon resonances, such as gap plasmons and hybridized disk–hole plasmons, which allow for colour printing with sub-diffraction resolution. We also address a range of fabrication approaches that enable large-area printing and nanoscale lithography compatible with complementary metal-oxide semiconductor technologies, including nanoimprint lithography and self-assembly. Finally, we review recent developments in dynamically reconfigurable plasmonic colours and in the laser-induced post-processing of plasmonic colour surfaces. Plasmonic colours can be used to colour large surfaces, can be mass-produced and dynamically reconfigured, and can provide sub-diffraction resolution. In this Review, basic properties of plasmonic colours, different platforms supporting them and recent developments in the field are discussed.

Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

Abstract: NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment analysis and related tasks, researchers have therefore used binarized emoticons and specific hashtags as forms of distant supervision. Our paper shows that by extending the distant supervision to a more diverse set of noisy labels, the models can learn richer representations. Through emoji prediction on a dataset of 1246 million tweets containing one of 64 common emojis we obtain state-of-the-art performance on 8 benchmark datasets within emotion, sentiment and sarcasm detection using a single pretrained model. Our analyses confirm that the diversity of our emotional labels yield a performance improvement over previous distant supervision approaches.

BedMachine v3: Complete Bed Topography and Ocean Bathymetry Mapping of Greenland From Multibeam Echo Sounding Combined With Mass Conservation.

Abstract: Greenland's bed topography is a primary control on ice flow, grounding line migration, calving dynamics, and subglacial drainage. Moreover, fjord bathymetry regulates the penetration of warm Atlantic water (AW) that rapidly melts and undercuts Greenland's marine-terminating glaciers. Here we present a new compilation of Greenland bed topography that assimilates seafloor bathymetry and ice thickness data through a mass conservation approach. A new 150 m horizontal resolution bed topography/bathymetric map of Greenland is constructed with seamless transitions at the ice/ocean interface, yielding major improvements over previous data sets, particularly in the marine-terminating sectors of northwest and southeast Greenland. Our map reveals that the total sea level potential of the Greenland ice sheet is 7.42 ± 0.05 m, which is 7 cm greater than previous estimates. Furthermore, it explains recent calving front response of numerous outlet glaciers and reveals new pathways by which AW can access glaciers with marine-based basins, thereby highlighting sectors of Greenland that are most vulnerable to future oceanic forcing.

The microbiota continuum along the female reproductive tract and its relation to uterine-related diseases

Abstract: Reports on bacteria detected in maternal fluids during pregnancy are typically associated with adverse consequences, and whether the female reproductive tract harbours distinct microbial communities beyond the vagina has been a matter of debate. Here we systematically sample the microbiota within the female reproductive tract in 110 women of reproductive age, and examine the nature of colonisation by 16S rRNA gene amplicon sequencing and cultivation. We find distinct microbial communities in cervical canal, uterus, fallopian tubes and peritoneal fluid, differing from that of the vagina. The results reflect a microbiota continuum along the female reproductive tract, indicative of a non-sterile environment. We also identify microbial taxa and potential functions that correlate with the menstrual cycle or are over-represented in subjects with adenomyosis or infertility due to endometriosis. The study provides insight into the nature of the vagino-uterine microbiome, and suggests that surveying the vaginal or cervical microbiota might be useful for detection of common diseases in the upper reproductive tract. Whether the female reproductive tract harbours distinct microbiomes beyond the vagina has been a matter of debate. Here, the authors show a subject-specific continuity in microbial communities at six sites along the female reproductive tract, indicative of a non-sterile environment.

A scored human protein–protein interaction network to catalyze genomic interpretation

Abstract: Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism.

Recent Advances and Challenges towards Sustainable Polyhydroxyalkanoate (PHA) Production

Abstract: Sustainable biofuels, biomaterials, and fine chemicals production is a critical matter that research teams around the globe are focusing on nowadays. Polyhydroxyalkanoates represent one of the biomaterials of the future due to their physicochemical properties, biodegradability, and biocompatibility. Designing efficient and economic bioprocesses, combined with the respective social and environmental benefits, has brought together scientists from different backgrounds highlighting the multidisciplinary character of such a venture. In the current review, challenges and opportunities regarding polyhydroxyalkanoate production are presented and discussed, covering key steps of their overall production process by applying pure and mixed culture biotechnology, from raw bioprocess development to downstream processing.

Dietary fibre in Europe: current state of knowledge on definitions, sources, recommendations, intakes and relationships to health

Abstract: Research into the analysis, physical properties and health effects of dietary fibre has continued steadily over the last 40-50 years. From the knowledge gained, countries have developed guidelines for their populations on the optimal amount of fibre to be consumed each day. Food composition tables from many countries now contain values for the dietary fibre content of foods, and, from these, combined with dietary surveys, population intakes have been determined. The present review assessed the uniformity of the analytical methods used, health claims permitted, recommendations and intakes, particularly from national surveys across Europe and around the world. It also assessed current knowledge on health effects of dietary fibre and related the impact of different fibre types on health. The overall intent was to be able to provide more detailed guidance on the types of fibre which should be consumed for good health, rather than simply a total intake figure, the current situation. Analysis of data indicated a fair degree of uniformity in the definition of dietary fibre, the method used for analysis, the recommended amount to be consumed and a growing literature on effects on digestive health and disease risk. However, national dietary survey data showed that intakes do not reach recommendations and very few countries provide guidance on the types of fibre that are preferable to achieve recommended intakes. Research gaps were identified and ideas suggested to provide information for more detailed advice to the public about specific food sources that should be consumed to achieve health benefits.

Microplastics as vectors for environmental contaminants: Exploring sorption, desorption, and transfer to biota.

Abstract: The occurrence and effects of microplastics (MPs) in the aquatic environment are receiving increasing attention. In addition to their possible direct adverse effects on biota, the potential role of MPs as vectors for hydrophobic organic chemicals (HOCs), compared to natural pathways, is a topic of much debate. It is evident, however, that temporal and spatial variations of MP occurrence do (and will) occur. To further improve the estimations of the role of MPs as vectors for HOC transfer into biota under varying MP concentrations and environmental conditions, it is important to identify and understand the governing processes. Here, we explore HOC sorption to and desorption from MPs and the underlying principles for their interactions. We discuss intrinsic and extrinsic parameters influencing these processes and focus on the importance of the exposure route for diffusive mass transfer. Also, we outline research needed to fill knowledge gaps and improve model-based calculations of MP-facilitated HOC transfer in the environment. Integr Environ Assess Manag 2017;13:488–493. © 2017 SETAC

Discovery of high-performance low-cost n-type Mg 3 Sb 2 -based thermoelectric materials with multi-valley conduction bands

Abstract: Widespread application of thermoelectric devices for waste heat recovery requires low-cost high-performance materials. The currently available n-type thermoelectric materials are limited either by their low efficiencies or by being based on expensive, scarce or toxic elements. Here we report a low-cost n-type material, Te-doped Mg3Sb1.5Bi0.5, that exhibits a very high figure of merit zT ranging from 0.56 to 1.65 at 300−725 K. Using combined theoretical prediction and experimental validation, we show that the high thermoelectric performance originates from the significantly enhanced power factor because of the multi-valley band behaviour dominated by a unique near-edge conduction band with a sixfold valley degeneracy. This makes Te-doped Mg3Sb1.5Bi0.5 a promising candidate for the low- and intermediate-temperature thermoelectric applications. Zintl-phase thermoelectrics are predominantly p-type. Here, Zhanget al. use tellurium to n-dope Mg3Sb1.5Bi0.5and obtain thermoelectric figures of merit up to 1.6 at 700 K. Calculations show that these performances result from a conduction band with sixfold valley degeneracy.

Strategies for stable water splitting via protected photoelectrodes

Abstract: Photoelectrochemical (PEC) solar-fuel conversion is a promising approach to provide clean and storable fuel (e.g., hydrogen and methanol) directly from sunlight, water and CO2. However, major challenges still have to be overcome before commercialization can be achieved. One of the largest barriers to overcome is to achieve a stable PEC reaction in either strongly basic or acidic electrolytes without degradation of the semiconductor photoelectrodes. In this work, we discuss fundamental aspects of protection strategies for achieving stable solid/liquid interfaces. We then analyse the charge transfer mechanism through the protection layers for both photoanodes and photocathodes. In addition, we review protection layer approaches and their stabilities for a wide variety of experimental photoelectrodes for water reduction. Finally, we discuss key aspects which should be addressed in continued work on realizing stable and practical PEC solar water splitting systems.

PointFinder: a novel web tool for WGS-based detection of antimicrobial resistance associated with chromosomal point mutations in bacterial pathogens.

Abstract: Background Antibiotic resistance is a major health problem, as drugs that were once highly effective no longer cure bacterial infections. WGS has previously been shown to be an alternative method for detecting horizontally acquired antimicrobial resistance genes. However, suitable bioinformatics methods that can provide easily interpretable, accurate and fast results for antimicrobial resistance associated with chromosomal point mutations are still lacking. Methods Phenotypic antimicrobial susceptibility tests were performed on 150 isolates covering three different bacterial species: Salmonella enterica, Escherichia coli and Campylobacter jejuni. The web-server ResFinder-2.1 was used to identify acquired antimicrobial resistance genes and two methods, the novel PointFinder (using BLAST) and an in-house method (mapping of raw WGS reads), were used to identify chromosomal point mutations. Results were compared with phenotypic antimicrobial susceptibility testing results. Results A total of 685 different phenotypic tests associated with chromosomal resistance to quinolones, polymyxin, rifampicin, macrolides and tetracyclines resulted in 98.4% concordance. Eleven cases of disagreement between tested and predicted susceptibility were observed: two C. jejuni isolates with phenotypic fluoroquinolone resistance and two with phenotypic erythromycin resistance and five colistin-susceptible E. coli isolates with a detected pmrB V161G mutation when assembled with Velvet, but not when using SPAdes or when mapping the reads. Conclusions PointFinder proved, with high concordance between phenotypic and predicted antimicrobial susceptibility, to be a user-friendly web tool for detection of chromosomal point mutations associated with antimicrobial resistance.

Extracellular polymeric substances are transient media for microbial extracellular electron transfer

Abstract: Microorganisms exploit extracellular electron transfer (EET) in growth and information exchange with external environments or with other cells. Every microbial cell is surrounded by extracellular polymeric substances (EPS). Understanding the roles of three-dimensional (3D) EPS in EET is essential in microbiology and microbial exploitation for mineral bio-respiration, pollutant conversion, and bioenergy production. We have addressed these challenges by comparing pure and EPS-depleted samples of three representative electrochemically active strains viz Gram-negative Shewanella oneidensis MR-1, Gram-positive Bacillus sp. WS-XY1, and yeast Pichia stipites using technology from electrochemistry, spectroscopy, atomic force microscopy, and microbiology. Voltammetry discloses redox signals from cytochromes and flavins in intact MR-1 cells, whereas stronger signals from cytochromes and additional signals from both flavins and cytochromes are found after EPS depletion. Flow cytometry and fluorescence microscopy substantiated by N-acetylglucosamine and electron transport system activity data showed less than 1.5% cell damage after EPS extraction. The electrochemical differences between normal and EPS-depleted cells therefore originate from electrochemical species in cell walls and EPS. The 35 ± 15-nm MR-1 EPS layer is also electrochemically active itself, with cytochrome electron transfer rate constants of 0.026 and 0.056 s-1 for intact MR-1 and EPS-depleted cells, respectively. This surprisingly small rate difference suggests that molecular redox species at the core of EPS assist EET. The combination of all the data with electron transfer analysis suggests that electron "hopping" is the most likely molecular mechanism for electrochemical electron transfer through EPS.

Identification of a novel transposon-associated phosphoethanolamine transferase gene, mcr-5, conferring colistin resistance in d-tartrate fermenting Salmonella enterica subsp. enterica serovar Paratyphi B.

Abstract: Objectives Plasmid-mediated mobilized colistin resistance is currently known to be caused by phosphoethanolamine transferases termed MCR-1, MCR-2, MCR-3 and MCR-4. However, this study focuses on the dissection of a novel resistance mechanism in mcr-1-, mcr-2- and mcr-3-negative d-tartrate fermenting Salmonella enterica subsp. enterica serovar Paratyphi B (Salmonella Paratyphi B dTa+) isolates with colistin MIC values >2 mg/L. Methods A selected isolate from the strain collection of the German National Reference Laboratory for Salmonella was investigated by WGS and bioinformatical analysis to identify novel phosphoethanolamine transferase genes involved in colistin resistance. Subsequently PCR screening, S1-PFGE and DNA-DNA hybridization were performed to analyse the prevalence and location of the identified mcr-5 gene. Cloning and transformation experiments in Escherichia coli DH5α and Salmonella Paratyphi B dTa+ control strains were carried out and the activity of MCR-5 was determined in vitro by MIC testing. Results In this study, we identified a novel phosphoethanolamine transferase in 14 mcr-1-, mcr-2- and mcr-3-negative Salmonella Paratyphi B dTa+ isolates with colistin MIC values >2 mg/L that were received during 2011-13. The respective gene, further termed as mcr-5 (1644 bp), is part of a 7337 bp transposon of the Tn3 family and usually located on related multi-copy ColE-type plasmids. Interestingly, in one isolate an additional subclone with a chromosomal location of the mcr-5 transposon was observed. Conclusions Our findings suggest that the transfer of colistin-resistance-mediating phosphoethanolamine transferase genes from bacterial chromosomes to mobile genetic elements has occurred in multiple independent events raising concern regarding their variety, prevalence and impact on public health.