An empirical, Bayesian approach to modelling crop yield: Maize in USA

We apply an empirical, data-driven approach for describing crop yield as a function of monthly temperature and precipitation by employing generative probabilistic models with parameters determined through Bayesian inference. Our approach is applied to state-scale maize yield and meteorological data for the US Corn Belt from 1981 to 2014 as an exemplar, but would be readily transferable to other crops, locations and spatial scales. Experimentation with a number of models shows that maize growth rates can be characterised by a two-dimensional Gaussian function of temperature and precipitation with monthly contributions accumulated over the growing period. This approach accounts for non-linear growth responses to the individual meteorological variables, and allows for interactions between them. Our models correctly identify that temperature and precipitation have the largest impact on yield in the six months prior to the harvest, in agreement with the typical growing season for US maize (April to September). Maximal growth rates occur for monthly mean temperature 18 °C–19 °C, corresponding to a daily maximum temperature of 24 °C–25 °C (in broad agreement with previous work) and monthly total precipitation 115 mm. Our approach also provides a self-consistent way of investigating climate change impacts on current US maize varieties in the absence of adaptation measures. Keeping precipitation and growing area fixed, a temperature increase of 2 °C, relative to 1981–2014, results in the mean yield decreasing by 8%, while the yield variance increases by a factor of around 3. We thus provide a flexible, data-driven framework for exploring the impacts of natural climate variability and climate change on globally significant crops based on their observed behaviour. In concert with other approaches, this can help inform the development of adaptation strategies that will ensure food security under a changing climate

Discovery, characterization and engineering of bacterial thermostable cellulose- degrading enzymes

Lignocellulose is the most abundant biomass on Earth, and thus our largest organic carbon reservoir. Enzymatic depolymerization of recalcitrant polysaccharides, notably cellulose, is a major cost driver in accessing the renewable energy stored within lignocellulosic biomass. Natural biodiversities may be explored to discover microbial enzymes that have evolved to conquer this task in various environments. We are studying novel enzymes from various biodiversities for the conversion of lignocellulosic materials, using (meta)genome mining and functional screening of fosmid libraries. Targeted biodiversities include deep-sea hot vents of the Arctic mid-ocean ridge (AMOR), the microbiome of the wood-eating Arctic shipworm, thermophilic enrichment cultures from biogas reactors, the Svalbard reindeer gut microbiome, and publicly available metagenomic data from various hot environments. Bioprospecting of the different biodiversities has so far resulted in the discovery of approximately 20 novel enzymes active on lignocellulosic substrates. The significant differences in the origin of the enzymes is reflected in their properties, both beneficial and challenging, and provide us with interesting engineering targets for improved performance in industrial settings. We will present case studies, including work on a novel thermostable cellulase named mgCel6A, with good activity on sulfite-pulped Norway spruce. This enzyme consists of a glycoside hydrolase family 6 catalytic domain (GH6) connected to a family 2 carbohydrate binding module (CBM2) and both the activity profile and predicted structural similarities to known cellulases suggest that mgCel6A is an endo-acting cellulase. Comparison of the full-length enzyme with the catalytic domain showed that the CBM strongly increases substrate binding, while not affecting thermal stability. However, importantly, in reactions with higher substrate concentrations the full-length enzyme was outperformed by the catalytic domain alone, underpinning previous suggestions that CBMs may be less useful in high-consistency bioprocessing. This enzyme is currently being targeted for rational engineering in an effort to decrease the pH optimum and improve the pH stability. Other case studies include GH48 cellulases and lytic polysaccharide monooxygenases (LPMOs). One important aspect of this work concerns the possible assembly of novel enzyme cocktails for lignocellulose processing that can compete with exiting commercial cocktails, which are primarily composed of fungal enzymes. Thus, comparative studies of our most promising bacterial enzymes with their well-known fungal counterparts are also being conducted

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

Characterization of the cecum microbiome from wild and captive rock ptarmigans indigenous to Arctic Norway.

Rock ptarmigans (Lagopus muta) are gallinaceous birds inhabiting arctic and sub-arctic environments. Their diet varies by season, including plants or plant parts of high nutritional value, but also toxic plant secondary metabolites (PSMs). Little is known about the microbes driving organic matter decomposition in the cecum of ptarmigans, especially the last steps leading to methanogenesis. The cecum microbiome in wild rock ptarmigans from Arctic Norway was characterized to unveil their functional potential for PSM detoxification, methanogenesis and polysaccharides degradation. Cecal samples were collected from wild ptarmigans from Svalbard (L. m. hyperborea) and northern Norway (L. m. muta) during autumn/winter (Sept-Dec). Samples from captive Svalbard ptarmigans fed commercial pelleted feed were included to investigate the effect of diet on microbial composition and function. Abundances of methanogens and bacteria were determined by qRT-PCR, while microbial community composition and functional potential were studied using 16S rRNA gene sequencing and shotgun metagenomics. Abundances of bacteria and methanogenic Archaea were higher in wild ptarmigans compared to captive birds. The ceca of wild ptarmigans housed bacterial groups involved in PSM-degradation, and genes mediating the conversion of phenol compounds to pyruvate. Methanomassiliicoccaceae was the major archaeal family in wild ptarmigans, carrying the genes for methanogenesis from methanol. It might be related to increased methanol production from pectin degradation in wild birds due to a diet consisting of primarily fresh pectin-rich plants. Both wild and captive ptarmigans possessed a broad suite of genes for the depolymerization of hemicellulose and non-cellulosic polysaccharides (e.g. starch). In conclusion, there were no physiological and phenotypical dissimilarities in the microbiota found in the cecum of wild ptarmigans on mainland Norway and Svalbard. While substantial differences in the functional potential for PSM degradation and methanogenesis in wild and captive birds seem to be a direct consequence of their dissimilar diets

DRAM for distilling microbial metabolism to automate the curation of microbiome function.

Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function

ESARDA Bulletin n. 59

ESARDA is an association initially formed to advance and harmonize research and development for nuclear safeguards whose scope has in recent year expanded as the number and type of its working groups’ activities below indicates. Esarda is currently composed of about 30 laboratories, private and governmental institutions worldwide. Within Esarda (http://esarda.jrc.ec.europa.eu/), a number working groups have been over the years established and active namely: Techniques and Standards for Destructive Analysis, Techniques and Standards for Non-Destructive Analysis, Containment and Surveillance, Novel Approaches / Novel Technologies, Implementation of Safeguards, Verification Technologies and Methodologies, Training and Knowledge Management, Editorial Committee. ESARDA publishes a Bulletin containing peer reviewed scientific related to nuclear Safeguards, verification and non-proliferation. This publication appears generally twice a year. In addition, thematic special issues are published as proposed by the ESARDA community. The Bulletin Editorial Board is composed of about 10 experts in the various technical and scientific fields related to safeguards. They are all actively engaged in safeguards R&D or in safeguards implementation and other fields. The Editorial Board decides the contents of the Bulletin, selects the papers to be published and reviews them before publication. All ESARDA editorial activities are carried out at JRC in Ispra. Scientific papers submitted for publication are reviewed by independent authors and by members of the Editorial Committee. The Bulletin is currently submitted to Scopus for evaluation in view of citation. ESARDA Bulletin is published jointly by ESARDA and the Joint Research Centre of the European Commission and distributed free of charge to over 1000 registered members, libraries and institutions worldwide.JRC.G.II.7-Nuclear securit

DRAM for distilling microbial metabolism to automate the curation of microbiome function

Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function