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Institute
- Institut für Biochemie und Biologie (4180) (remove)
The Proteasome Acts as a Hub for Plant Immunity and Is Targeted by Pseudomonas Type III Effectors
(2016)
Recent evidence suggests that the ubiquitin-proteasome system is involved in several aspects of plant immunity and that a range of plant pathogens subvert the ubiquitin-proteasome system to enhance their virulence. Here, we show that proteasome activity is strongly induced during basal defense in Arabidopsis (Arabidopsis thaliana). Mutant lines of the proteasome subunits RPT2a and RPN12a support increased bacterial growth of virulent Pseudomonas syringae pv tomato DC3000 (Pst) and Pseudomonas syringae pv maculicola ES4326. Both proteasome subunits are required for pathogen-associated molecular pattern-triggered immunity responses. Analysis of bacterial growth after a secondary infection of systemic leaves revealed that the establishment of systemic acquired resistance (SAR) is impaired in proteasome mutants, suggesting that the proteasome also plays an important role in defense priming and SAR. In addition, we show that Pst inhibits proteasome activity in a type III secretion-dependent manner. A screen for type III effector proteins from Pst for their ability to interfere with proteasome activity revealed HopM1, HopAO1, HopA1, and HopG1 as putative proteasome inhibitors. Biochemical characterization of HopM1 by mass spectrometry indicates that HopM1 interacts with several E3 ubiquitin ligases and proteasome subunits. This supports the hypothesis that HopM1 associates with the proteasome, leading to its inhibition. Thus, the proteasome is an essential component of pathogen-associated molecular pattern-triggered immunity and SAR, which is targeted by multiple bacterial effectors.
XopJ is a Xanthomonas type III effector protein that promotes bacterial virulence on susceptible pepper plants through the inhibition of the host cell proteasome and a resultant suppression of salicylic acid (SA) - dependent defense responses. We show here that Nicotiana benthamiana leaves transiently expressing XopJ display hypersensitive response (HR) -like symptoms when exogenously treated with SA. This apparent avirulence function of XopJ was further dependent on effector myristoylation as well as on an intact catalytic triad, suggesting a requirement of its enzymatic activity for HR-like symptom elicitation. The ability of XopJ to cause a HR-like symptom development upon SA treatment was lost upon silencing of SGT1 and NDR1, respectively, but was independent of EDS1 silencing, suggesting that XopJ is recognized by an R protein of the CC-NBS-LRR class. Furthermore, silencing of NPR1 abolished the elicitation of HR-like symptoms in XopJ expressing leaves after SA application. Measurement of the proteasome activity indicated that proteasome inhibition by XopJ was alleviated in the presence of SA, an effect that was not observed in NPR1 silenced plants. Our results suggest that XopJ - triggered HR-like symptoms are closely related to the virulence function of the effector and that XopJ follows a two-signal model in order to elicit a response in the non-host plant N. benthamiana.
Because of political conflicts and climate change, migration will be increased worldwide and integration in host societies is a challenge also for migrants. We hypothesize that migrants, who take up the challenge in a new social environment are taller than migrants who do not pose this challenge. We analyze by a questionnaire possible social, nutritional and ethnic influencing factors to body height (BH) of adult offspring of Turkish migrants (n = 82, 39 males) aged from 18 to 34 years (mean age 24.6 years). The results of multiple regression (downward selection) show that the more a male adult offspring of Turkish migrants feels like belonging to the Turkish culture, the smaller he is (95% CI, -3.79, -0.323). Further, the more a male adult offspring of Turkish migrants feels like belonging to the German culture, the taller he is (95% CI, -0.152, 1.738). We discussed it comparable to primates taking up their challenge in dominance, where as a result their body size increase is associated with higher IGF-1 level. IGF-1 is associated with emotional belonging and has a fundamental role in the regulation of metabolism and growth of the human body. With all pilot characteristics of our study results show that the successful challenge of integration in a new society is strongly associated with the emotional integration and identification in the sense of a personal sense of belonging to society. We discuss taller BH as a signal of social growth adjustment. In this sense, a secular trend of BH adaptation of migrants to hosts is a sign of integration.
Next-generation sequencing methods provide comprehensive data for the analysis of structural and functional analysis of the genome. The draft genomes with low contig number and high N50 value can give insight into the structure of the genome as well as provide information on the annotation of the genome. In this study, we designed a pipeline that can be used to assemble prokaryotic draft genomes with low number of contigs and high N50 value. We aimed to use combination of two de novo assembly tools (SPAdes and IDBA-Hybrid) and evaluate the impact of this approach on the quality metrics of the assemblies. The followed pipeline was tested with the raw sequence data with short reads (< 300) for a total of 10 species from four different genera. To obtain the final draft genomes, we firstly assembled the sequences using SPAdes to find closely related organism using the extracted 16 s rRNA from it. IDBA-Hybrid assembler was used to obtain the second assembly data using the closely related organism genome. SPAdes assembler tool was implemented using the second assembly, produced by IDBA-hybrid as a hint. The results were evaluated using QUAST and BUSCO. The pipeline was successful for the reduction of the contig numbers and increasing the N50 statistical values in the draft genome assemblies while preserving the coverage of the draft genomes.
Measures for interoperability of phenotypic data: minimum information requirements and formatting
(2016)
Background: Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse. Results: In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called "Minimum Information About a Plant Phenotyping Experiment", which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented. Conclusions: Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.
Necrotrophic as well as saprophytic small-spored Altemaria (A.) species are annually responsible for major losses of agricultural products, such as cereal crops, associated with the contamination of food and feedstuff with potential health-endangering Altemaria toxins. Knowledge of the metabolic capabilities of different species-groups to form mycotoxins is of importance for a reliable risk assessment. 93 Altemaria strains belonging to the four species groups Alternaria tenuissima, A. arborescens, A. altemata, and A. infectoria were isolated from winter wheat kernels harvested from fields in Germany and Russia and incubated under equal conditions. Chemical analysis by means of an HPLC-MS/MS multi-Alternaria-toxin-method showed that 95% of all strains were able to form at least one of the targeted 17 non-host specific Altemaria toxins. Simultaneous production of up to 15 (modified) Altemaria toxins by members of the A. tenuissima, A. arborescens, A. altemata species-groups and up to seven toxins by A. infectoria strains was demonstrated. Overall tenuazonic acid was the most extensively formed mycotoxin followed by alternariol and alternariol mono methylether, whereas altertoxin I was the most frequently detected toxin. Sulfoconjugated modifications of alternariol, alternariol mono methylether, altenuisol and altenuene were frequently determined. Unknown perylene quinone derivatives were additionally detected. Strains of the species-group A. infectoria could be segregated from strains of the other three species-groups due to significantly lower toxin levels and the specific production of infectopyrone. Apart from infectopyrone, alterperylenol was also frequently produced by 95% of the A. infectoria strains. Neither by the concentration nor by the composition of the targeted Altemaria toxins a differentiation between the species-groups A. altemata, A. tenuissima and A. arborescens was possible.
Alternaria (A.) is a genus of widespread fungi capable of producing numerous, possibly health-endangering Alternaria toxins (ATs), which are usually not the focus of attention. The formation of ATs depends on the species and complex interactions of various environmental factors and is not fully understood. In this study the influence of temperature (7 degrees C, 25 degrees C), substrate (rice, wheat kernels) and incubation time (4, 7, and 14 days) on the production of thirteen ATs and three sulfoconjugated ATs by three different Alternaria isolates from the species groups A. tenuissima and A. infectoria was determined. High-performance liquid chromatography coupled with tandem mass spectrometry was used for quantification. Under nearly all conditions, tenuazonic acid was the most extensively produced toxin. At 25 degrees C and with increasing incubation time all toxins were formed in high amounts by the two A. tenuissima strains on both substrates with comparable mycotoxin profiles. However, for some of the toxins, stagnation or a decrease in production was observed from day 7 to 14. As opposed to the A. tenuissima strains, the A. infectoria strain only produced low amounts of ATs, but high concentrations of stemphyltoxin III. The results provide an essential insight into the quantitative in vitro AT formation under different environmental conditions, potentially transferable to different field and storage conditions.
We recently demonstrated that the sympathetic nervous system can be voluntarily activated following a training program consisting of cold exposure, breathing exercises, and meditation. This resulted in profound attenuation of the systemic inflammatory response elicited by lipopolysaccharide (LPS) administration. Herein, we assessed whether this training program affects the plasma metabolome and if these changes are linked to the immunomodulatory effects observed. A total of 224 metabolites were identified in plasma obtained from 24 healthy male volunteers at six timepoints, of which 98 were significantly altered following LPS administration. Effects of the training program were most prominent shortly after initiation of the acquired breathing exercises but prior to LPS administration, and point towards increased activation of the Cori cycle. Elevated concentrations of lactate and pyruvate in trained individuals correlated with enhanced levels of anti-inflammatory interleukin (IL)-10. In vitro validation experiments revealed that co-incubation with lactate and pyruvate enhances IL-10 production and attenuates the release of pro-inflammatory IL-1 beta and IL-6 by LPS-stimulated leukocytes. Our results demonstrate that practicing the breathing exercises acquired during the training program results in increased activity of the Cori cycle. Furthermore, this work uncovers an important role of lactate and pyruvate in the anti-inflammatory phenotype observed in trained subjects.
Home range size and resource use of breeding and non-breeding white storks along a land use gradient
(2018)
Biotelemetry is increasingly used to study animal movement at high spatial and temporal resolution and guide conservation and resource management. Yet, limited sample sizes and variation in space and habitat use across regions and life stages may compromise robustness of behavioral analyses and subsequent conservation plans. Here, we assessed variation in (i) home range sizes, (ii) home range selection, and (iii) fine-scale resource selection of white storks across breeding status and regions and test model transferability. Three study areas were chosen within the Central German breeding grounds ranging from agricultural to fluvial and marshland. We monitored GPS-locations of 62 adult white storks equipped with solar-charged GPS/3D-acceleration (ACC) transmitters in 2013-2014. Home range sizes were estimated using minimum convex polygons. Generalized linear mixed models were used to assess home range selection and fine-scale resource selection by relating the home ranges and foraging sites to Corine habitat variables and normalized difference vegetation index in a presence/pseudo-absence design. We found strong variation in home range sizes across breeding stages with significantly larger home ranges in non-breeding compared to breeding white storks, but no variation between regions. Home range selection models had high explanatory power and well predicted overall density of Central German white stork breeding pairs. Also, they showed good transferability across regions and breeding status although variable importance varied considerably. Fine-scale resource selection models showed low explanatory power. Resource preferences differed both across breeding status and across regions, and model transferability was poor. Our results indicate that habitat selection of wild animals may vary considerably within and between populations, and is highly scale dependent. Thereby, home range scale analyses show higher robustness whereas fine-scale resource selection is not easily predictable and not transferable across life stages and regions. Such variation may compromise management decisions when based on data of limited sample size or limited regional coverage. We thus recommend home range scale analyses and sampling designs that cover diverse regional landscapes and ensure robust estimates of habitat suitability to conserve wild animal populations.
Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long-term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.
SDM performance varied for different range dynamics. Prediction accuracies decreased when abrupt range shifts occurred as species were outpaced by the rate of climate change, and increased again when a new equilibrium situation was realised. When ranges contracted, prediction accuracies increased as the absences were predicted well. Far- dispersing species were faster in tracking climate change, and were predicted more accurately by SDMs than short- dispersing species. BRTs mostly outperformed GLMs. The presence of a predator, and the inclusion of its incidence as an environmental predictor, made BRTs and GLMs perform similarly. Results are discussed in light of other studies dealing with effects of ecological traits and processes on SDM performance. Perspectives are given on further advancements of SDMs and for possible interfaces with more mechanistic approaches in order to improve predictions under environmental change.
Data limitations can lead to unrealistic fits of predictive species distribution models (SDMs) and spurious extrapolation to novel environments. Here, we want to draw attention to novel combinations of environmental predictors that are within the sampled range of individual predictors but are nevertheless outside the sample space. These tend to be overlooked when visualizing model behaviour. They may be a cause of differing model transferability and environmental change predictions between methods, a problem described in some studies but generally not well understood. We here use a simple simulated data example to illustrate the problem and provide new and complementary visualization techniques to explore model behaviour and predictions to novel environments. We then apply these in a more complex real-world example. Our results underscore the necessity of scrutinizing model fits, ecological theory and environmental novelty.
Density regulation influences population dynamics through its effects on demographic rates and consequently constitutes a key mechanism explaining the response of organisms to environmental changes. Yet, it is difficult to establish the exact form of density dependence from empirical data. Here, we developed an individual-based model to explore how resource limitation and behavioural processes determine the spatial structure of white stork Ciconia ciconia populations and regulate reproductive rates. We found that the form of density dependence differed considerably between landscapes with the same overall resource availability and between home range selection strategies, highlighting the importance of fine-scale resource distribution in interaction with behaviour. In accordance with theories of density dependence, breeding output generally decreased with density but this effect was highly variable and strongly affected by optimal foraging strategy, resource detection probability and colonial behaviour. Moreover, our results uncovered an overlooked consequence of density dependence by showing that high early nestling mortality in storks, assumed to be the outcome of harsh weather, may actually result from density dependent effects on food provision. Our findings emphasize that accounting for interactive effects of individual behaviour and local environmental factors is crucial for understanding density-dependent processes within spatially structured populations. Enhanced understanding of the ways animal populations are regulated in general, and how habitat conditions and behaviour may dictate spatial population structure and demographic rates is critically needed for predicting the dynamics of populations, communities and ecosystems under changing environmental conditions.
The ability of some plant species to dominate communities in new biogeographical ranges has been attributed to an innate higher competitive ability and release from co-evolved specialist enemies. Specifically, invasive success in the new range might be explained by release from biotic negative soil-feedbacks, which control potentially dominant species in their native range. To test this hypothesis, we grew individuals from sixteen phylogenetically paired European grassland species that became either invasive or naturalized in new ranges, in either sterilized soil or in sterilized soil with unsterilized soil inoculum from their native home range. We found that although the native members of invasive species generally performed better than those of naturalized species, these native members of invasive species also responded more negatively to native soil inoculum than did the native members of naturalized species. This supports our hypothesis that potentially invasive species in their native range are held in check by negative soil-feedbacks. However, contrary to expectation, negative soil-feedbacks in potentially invasive species were not much increased by interspecific competition. There was no significant variation among families between invasive and naturalized species regarding their feedback response (negative vs. neutral). Therefore, we conclude that the observed negative soil feedbacks in potentially invasive species may be quite widespread in European families of typical grassland species.
Bacterial molybdoenzymes are key enzymes involved in the global sulphur, nitrogen and carbon cycles. These enzymes require the insertion of the molybdenum cofactor (Moco) into their active sites and are able to catalyse a large range of redox-reactions. Escherichia coli harbours nineteen different molybdoenzymes that require a tight regulation of their synthesis according to substrate availability, oxygen availability and the cellular concentration of molybdenum and iron. The synthesis and assembly of active molybdoenzymes are regulated at the level of transcription of the structural genes and of translation in addition to the genes involved in Moco biosynthesis. The action of global transcriptional regulators like FNR, NarXL/QP, Fur and ArcA and their roles on the expression of these genes is described in detail. In this review we focus on what is known about the molybdenum- and iron-dependent regulation of molybdoenzyme and Moco biosynthesis genes in the model organism E. coli. The gene regulation in E. coli is compared to two other well studied model organisms Rhodobacter capsulatus and Shewanella oneidensis.
Molybdenum cofactor (Moco) biosynthesis is a complex process that involves the coordinated function of several proteins. In recent years it has become obvious that the availability of iron plays an important role in the biosynthesis of Moco. First, the MoaA protein binds two (4Fe-4S] clusters per monomer. Second, the expression of the moaABCDE and moeAB operons is regulated by FNR, which senses the availability of oxygen via a functional NFe-4S) cluster. Finally, the conversion of cyclic pyranopterin monophosphate to molybdopterin requires the availability of the L-cysteine desulfurase IscS, which is a shared protein with a main role in the assembly of Fe-S clusters. In this report, we investigated the transcriptional regulation of the moaABCDE operon by focusing on its dependence on cellular iron availability. While the abundance of selected molybdoenzymes is largely decreased under iron-limiting conditions, our data show that the regulation of the moaABCDE operon at the level of transcription is only marginally influenced by the availability of iron. Nevertheless, intracellular levels of Moco were decreased under iron-limiting conditions, likely based on an inactive MoaA protein in addition to lower levels of the L-cysteine desulfurase IscS, which simultaneously reduces the sulfur availability for Moco production. IMPORTANCE FNR is a very important transcriptional factor that represents the master switch for the expression of target genes in response to anaerobiosis. Among the FNR-regulated operons in Escherichia coli is the moaABCDE operon, involved in Moco biosynthesis. Molybdoenzymes have essential roles in eukaryotic and prokaryotic organisms. In bacteria, molybdoenzymes are crucial for anaerobic respiration using alternative electron acceptors. This work investigates the connection of iron availability to the biosynthesis of Moco and the production of active molybdoenzymes.
The c-Fosc-Jun complex forms the activator protein 1 transcription factor, a therapeutic target in the treatment of cancer. Various synthetic peptides have been designed to try to selectively disrupt the interaction between c-Fos and c-Jun at its leucine zipper domain. To evaluate the binding affinity between these synthetic peptides and c-Fos, polarizable and nonpolarizable molecular dynamics (MD) simulations were conducted, and the resulting conformations were analyzed using the molecular mechanics generalized Born surface area (MM/GBSA) method to compute free energies of binding. In contrast to empirical and semiempirical approaches, the estimation of free energies of binding using a combination of MD simulations and the MM/GBSA approach takes into account dynamical properties such as conformational changes, as well as solvation effects and hydrophobic and hydrophilic interactions. The predicted binding affinities of the series of c-Jun-based peptides targeting the c-Fos peptide show good correlation with experimental melting temperatures. This provides the basis for the rational design of peptides based on internal, van der Waals, and electrostatic interactions.
Background: Protein kinases constitute a particularly large protein family in Arabidopsis with important functions in cellular signal transduction networks. At the same time Arabidopsis is a model plant with high frequencies of gene duplications. Here, we have conducted a systematic analysis of the Arabidopsis kinase complement, the kinome, with particular focus on gene duplication events. We matched Arabidopsis proteins to a Hidden-Markov Model of eukaryotic kinases and computed a phylogeny of 942 Arabidopsis protein kinase domains and mapped their origin by gene duplication.
Results: The phylogeny showed two major clades of receptor kinases and soluble kinases, each of which was divided into functional subclades. Based on this phylogeny, association of yet uncharacterized kinases to families was possible which extended functional annotation of unknowns. Classification of gene duplications within these protein kinases revealed that representatives of cytosolic subfamilies showed a tendency to maintain segmentally duplicated genes, while some subfamilies of the receptor kinases were enriched for tandem duplicates. Although functional diversification is observed throughout most subfamilies, some instances of functional conservation among genes transposed from the same ancestor were observed. In general, a significant enrichment of essential genes was found among genes encoding for protein kinases.
Conclusions: The inferred phylogeny allowed classification and annotation of yet uncharacterized kinases. The prediction and analysis of syntenic blocks and duplication events within gene families of interest can be used to link functional biology to insights from an evolutionary viewpoint. The approach undertaken here can be applied to any gene family in any organism with an annotated genome.
In high-value sweet cherry (Prunus avium), the red coloration - determined by the anthocyanins content - is correlated with the fruit ripeness stage and market value. Non-destructive spectroscopy has been introduced in practice and may be utilized as a tool to assess the fruit pigments in the supply chain processes. From the fruit spectrum in the visible (Vis) wavelength range, the pigment contents are analyzed separately at their specific absorbance wavelengths.
A drawback of the method is the need for re-calibration due to varying optical properties of the fruit tissue. In order to correct for the scattering differences, most often the spectral intensity in the visible spectrum is normalized by wavelengths in the near infrared (NIR) range, or pre-processing methods are applied in multivariate calibrations.
In the present study, the influence of the fruit scattering properties on the Vis/NIR fruit spectrum were corrected by the effective pathlength in the fruit tissue obtained from time-resolved readings of the distribution of time-of-flight (DTOF). Pigment analysis was carried out according to Lambert-Beer law, considering fruit spectral intensities, effective pathlength, and refractive index. Results were compared to commonly applied linear color and multivariate partial least squares (PLS) regression analysis. The approaches were validated on fruits at different ripeness stages, providing variation in the scattering coefficient and refractive index exceeding the calibration sample set.
In the validation, the measuring uncertainty of non-destructively analyzing fruits with Vis/NIR spectra by means of PLS or Lambert-Beer in comparison with combined application of Vis/NIR spectroscopy and DTOF measurements showed a dramatic bias reduction as well as enhanced coefficients of determination when using both, the spectral intensities and apparent information on the scattering influence by means of DTOF readings. Corrections for the refractive index did not render improved results.