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Although temporal heterogeneity is a well-accepted driver of biodiversity, effects of interannual variation in land-use intensity (LUI) have not been addressed yet. Additionally, responses to land use can differ greatly among different organisms; therefore, overall effects of land-use on total local biodiversity are hardly known. To test for effects of LUI (quantified as the combined intensity of fertilization, grazing, and mowing) and interannual variation in LUI (SD in LUI across time), we introduce a unique measure of whole-ecosystem biodiversity, multidiversity. This synthesizes individual diversity measures across up to 49 taxonomic groups of plants, animals, fungi, and bacteria from 150 grasslands. Multidiversity declined with increasing LUI among grasslands, particularly for rarer species and aboveground organisms, whereas common species and belowground groups were less sensitive. However, a high level of interannual variation in LUI increased overall multidiversity at low LUI and was even more beneficial for rarer species because it slowed the rate at which the multidiversity of rare species declined with increasing LUI. In more intensively managed grasslands, the diversity of rarer species was, on average, 18% of the maximum diversity across all grasslands when LUI was static over time but increased to 31% of the maximum when LUI changed maximally over time. In addition to decreasing overall LUI, we suggest varying LUI across years as a complementary strategy to promote biodiversity conservation.
Leaf senescence is an active process with a pivotal impact on plant productivity. It results from extensive signalling cross-talk coordinating environmental factors with intrinsic age-related mechanisms. Although many studies have shown that leaf senescence is affected by a range of external parameters, knowledge about the regulatory systems that govern the interplay between developmental programmes and environmental stress is still vague. Salinity is one of the most important environmental stresses that promote leaf senescence and thus affect crop yield. Improving salt tolerance by avoiding or delaying senescence under stress will therefore play an important role in maintaining high agricultural productivity. Experimental evidence suggests that hydrogen peroxide (H2O2) functions as a common signalling molecule in both developmental and salt-induced leaf senescence. In this study, microarray-based gene expression profiling on Arabidopsis thaliana plants subjected to long-term salinity stress to induce leaf senescence was performed, together with co-expression network analysis for H2O2-responsive genes that are mutually up-regulated by salt induced-and developmental leaf senescence. Promoter analysis of tightly co-expressed genes led to the identification of seven cis-regulatory motifs, three of which were known previously, namely CACGTGT and AAGTCAA, which are associated with reactive oxygen species (ROS)-responsive genes, and CCGCGT, described as a stress-responsive regulatory motif, while the others, namely ACGCGGT, AGCMGNC, GMCACGT, and TCSTYGACG were not characterized previously. These motifs are proposed to be novel elements involved in the H2O2-mediated control of gene expression during salinity stress-triggered and developmental senescence, acting through upstream transcription factors that bind to these sites.
Dendritic cells (DCs) are the cutting edge in innate and adaptive immunity. The major functions of these antigen presenting cells are the capture, endosomal processing and presentation of antigens, providing them an exclusive ability to provoke adaptive immune responses and to induce and control tolerance. Immature DCs capture and process antigens, migrate towards secondary lymphoid organs where they present antigens to naive T cells in a well synchronized sequence of procedures referred to as maturation. Indeed, recent research indicated that sphingolipids are modulators of essential steps in DC homeostasis. It has been recognized that sphingolipids not only modulate the development of DC subtypes from precursor cells but also influence functional activities of DCs such as antigen capture, and cytokine profiling. Thus, it is not astonishing that sphingolipids and sphingolipid metabolism play a substantial role in inflammatory diseases that are modulated by DCs. Here we highlight the function of sphingosine 1-phosphate (S1P) on DC homeostasis and the role of SIP and SW metabolism in inflammatory diseases.
The photosynthetic carbon metabolism, including the Calvin-Benson cycle, is the primary pathway in C-3-plants, producing starch and sucrose from CO2. Understanding the interplay between regulation and efficiency of this pathway requires the development of mathematical models which would explain the observed dynamics of metabolic transformations. Here, we address this question by casting the existing models of Calvin-Benson cycle and the end-product processes into an analysis framework which not only facilitates the comparison of the different models, but also allows for their ranking with respect to chosen criteria, including stability, sensitivity, robustness and/or compliance with experimental data. The importance of the photosynthetic carbon metabolism for the increase of plant biomass has resulted in many models with various levels of detail. We provide the largest compendium of 15 existing, well-investigated models together with a comprehensive classification as well as a ranking framework to determine the best-performing models for metabolic engineering and planning of in silica experiments. The classification can be additionally used, based on the model structure, as a tool to identify the models which match best the experimental design. The provided ranking is just one alternative to score models and, by changing the weighting factor, this framework also could be applied for selection of other criteria of interest.
Epitop-Kartierung von PBP2A und Identifizierung MRSA-spezifischer immunodominanter Peptidsequenzen
(2014)
Dissolved organic carbon (DOC) concentrations - mainly of terrestrial origin - are increasing worldwide in inland waters. Heterotrophic bacteria are the main consumers of DOC and thus determine DOC temporal dynamics and availability for higher trophic levels. Our aim was to study bacterial carbon (C) turnover with respect to DOC quantity and chemical quality using both allochthonous and autochthonous DOC sources. We incubated a natural bacterial community with allochthonous C (C-13-labeled beech leachate) and increased concentrations and pulses (intermittent occurrence of organic matter input) of autochthonous C (phytoplankton lysate). We then determined bacterial C consumption, activities, and community composition together with the C flow through bacteria using stable C isotopes. The chemical analysis of single sources revealed differences in aromaticity and low-and high-molecular-weight substance fractions (LMWS and HMWS, respectively) between allochthonous and autochthonous C sources. Both DOC sources (allochthonous and autochthonous DOC) were metabolized at a high bacterial growth efficiency (BGE) around 50%. In treatments with mixed sources, rising concentrations of added autochthonous DOC resulted in a further, significant increase in bacterial DOC consumption of up to 68% when nutrients were not limiting. This rise was accompanied by a decrease in the humic substance (HS) fraction and an increase in bacterial biomass. Changes in DOC concentration and consumption in mixed treatments did not affect bacterial community composition (BCC), but BCC differed in single vs. mixed incubations. Our study highlights that DOC quantity affects bacterial C consumption but not BCC in nutrient-rich aquatic systems. BCC shifted when a mixture of allochthonous and autochthonous C was provided simultaneously to the bacterial community. Our results indicate that chemical quality rather than source of DOC per se (allochthonous vs. autochthonous) determines bacterial DOC turnover.
Confusion about model validation is one of the main challenges in using ecological models for decision support, such as the regulation of pesticides. Decision makers need to know whether a model is a sufficiently good representation of its real counterpart and what criteria can be used to answer this question. Unclear terminology is one of the main obstacles to a good understanding of what model validation is, how it works, and what it can deliver. Therefore, we performed a literature review and derived a standard set of terms. 'Validation' was identified as a catch-all term, which is thus useless for any practical purpose. We introduce the term 'evaludation', a fusion of 'evaluation' and 'validation', to describe the entire process of assessing a model's quality and reliability. Considering the iterative nature of model development, the modelling cycle, we identified six essential elements of evaludation: (i) 'data evaluation' for scrutinising the quality of numerical and qualitative data used for model development and testing; (ii) 'conceptual model evaluation' for examining the simplifying assumptions underlying a model's design; (iii) 'implementation verification' for testing the model's implementation in equations and as a computer programme; (iv) 'model output verification' for comparing model output to data and patterns that guided model design and were possibly used for calibration; (v) 'model analysis' for exploring the model's sensitivity to changes in parameters and process formulations to make sure that the mechanistic basis of main behaviours of the model has been well understood; and (vi) 'model output corroboration' for comparing model output to new data and patterns that were not used for model development and parameterisation. Currently, most decision makers require 'validating' a model by testing its predictions with new experiments or data. Despite being desirable, this is neither sufficient nor necessary for a model to be useful for decision support. We believe that the proposed set of terms and its relation to the modelling cycle can help to make quality assessments and reality checks of ecological models more comprehensive and transparent. (C) 2013 Elsevier B.V. All rights reserved.
Biosensors for the detection of benzaldehyde and g-aminobutyric acid (GABA) are reported using aldehyde oxidoreductase PaoABC from Escherichia coli immobilized in a polymer containing bound low potential osmium redox complexes. The electrically connected enzyme already electrooxidizes benzaldehyde at potentials below −0.15 V (vs. Ag|AgCl, 1 M KCl). The pH-dependence of benzaldehyde oxidation can be strongly influenced by the ionic strength. The effect is similar with the soluble osmium redox complex and therefore indicates a clear electrostatic effect on the bioelectrocatalytic efficiency of PaoABC in the osmium containing redox polymer. At lower ionic strength, the pH-optimum is high and can be switched to low pH-values at high ionic strength. This offers biosensing at high and low pH-values. A “reagentless” biosensor has been formed with enzyme wired onto a screen-printed electrode in a flow cell device. The response time to addition of benzaldehyde is 30 s, and the measuring range is between 10–150 µM and the detection limit of 5 µM (signal to noise ratio 3:1) of benzaldehyde. The relative standard deviation in a series (n = 13) for 200 µM benzaldehyde is 1.9%. For the biosensor, a response to succinic semialdehyde was also identified. Based on this response and the ability to work at high pH a biosensor for GABA is proposed by coimmobilizing GABA-aminotransferase (GABA-T) and PaoABC in the osmium containing redox polymer.