Frequency of a natural truncated allele of <Emphasis Type="Italic">MdMLO19</Emphasis> in the germplasm of <Emphasis Type="Italic">Malus domestica</Emphasis>

Podosphaera leucotricha is the causal agent of powdery mildew (PM) in apple. To reduce the amount of fungicides required to control this pathogen, the development of resistant apple cultivars should become a priority. Resistance to PM was achieved in various crops by knocking out specific members of the MLO gene family that are responsible for PM susceptibility (S-genes). In apple, the knockdown of MdMLO19 resulted in PM resistance. However, since gene silencing technologies such as RNAi are perceived unfavorably in Europe, a different approach that exploits this type of resistance is needed. This work evaluates the presence of non-functional naturally occurring alleles of MdMLO19 in apple germplasm. The screening of the re-sequencing data of 63 apple individuals led to the identification of 627 single nucleotide polymorphisms (SNPs) in five MLO genes (MdMLO5, MdMLO7, MdMLO11, MdMLO18, and MdMLO19), 127 of which were located in exons. The T-1201 insertion of a single nucleotide in MdMLO19 caused the formation of an early stop codon, resulting in a truncated protein lacking 185 amino acids, including the calmodulin-binding domain. The presence of the insertion was evaluated in 115 individuals. It was heterozygous in 64 and homozygous in 25. Twelve of the 25 individuals carrying the insertion in homozygosity were susceptible to PM. After barley, pea, cucumber, and tomato, apple would be the fifth species for which a natural non-functional mlo allele has been found.     

An Emerging Approach for Parallel Quantification of Intracellular Protozoan Parasites and Host Cell Characterization Using TissueFAXS Cytometry

Characterization of host-pathogen interactions is a fundamental approach in microbiological and immunological oriented disciplines. It is commonly accepted that host cells start to change their phenotype after engulfing pathogens. Techniques such as real time PCR or ELISA were used to characterize the genes encoding proteins that are associated either with pathogen elimination or immune escape mechanisms. Most of such studies were performed in vitro using primary host cells or cell lines. Consequently, the data generated with such approaches reflect the global RNA expression or protein amount recovered from all cells in culture. This is justified when all host cells harbor an equal amount of pathogens under experimental conditions. However, the uptake of pathogens by phagocytic cells is not synchronized. Consequently, there are host cells incorporating different amounts of pathogens that might result in distinct pathogen-induced protein biosynthesis. Therefore, we established a technique able to detect and quantify the number of pathogens in the corresponding host cells using immunofluorescence-based high throughput analysis. Paired with multicolor staining of molecules of interest it is now possible to analyze the infection profile of host cell populations and the corresponding phenotype of the host cells as a result of parasite load.     

Biodiversity impacts from water consumption on a global scale for use in life cycle assessment

Purpose

Agriculture is a major water user worldwide, potentially depriving many ecosystems of water. Comprehensive global impact assessment methodologies are therefore required to assess impacts from water consumption on biodiversity. Since scarcity of water, as well as species richness, varies greatly between different world regions, a spatially differentiated approach is needed. Therefore, our aim is to enhance a previously published methodology in terms of spatial and species coverage.

Methods

We developed characterization factors for lifecycle impact assessment (LCIA) targeting biodiversity loss of various animal taxa (i.e., birds, reptiles, mammals, and amphibians) in wetlands. Data was collected for more than 22,000 wetlands worldwide, distinguishing between surface water- and groundwater-fed wetlands. Additionally, we account for a loss of vascular plant species in terrestrial ecosystems, based on precipitation. The characterization factors are expressed as global fractions of potential species extinctions (PDF) per cubic meter of water consumed annually and are developed with a spatial resolution of 0.05 arc degrees. Based on the geographic range of species, as well as their current threat level, as indicated by the International Union for Conservation of Nature (IUCN), we developed a vulnerability indicator that is included in the characterization factor.

Results and discussion

Characterization factors have maximal values in the order of magnitude of 10^?11 PDF·year/m³ for animal taxa combined and 10^?12 PDF·year/m³ for vascular plants. The application of the developed factors for global cultivation of wheat, maize, cotton, and rice highlights that the amount of water consumption alone is not sufficient to indicate the places of largest impacts but that species richness and vulnerability of species are indeed important factors to consider. Largest impacts are calculated for vascular plants in Madagascar, for maize, and for animal taxa; in Australia and the USA for surface water consumption (cotton); and in Algeria and Tunisia for groundwater consumption (cotton).

Conclusions

We developed a spatially differentiated approach to account for impacts from water consumption on a global level. We demonstrated its functionality with an application to a global case study of four different crops.

     

Morphometry, densitometry and pattern analysis of plastic-embedded histologic material from urothelial cell carcinoma of the bladder.

An image analysis method of grading histologic sections of bladder carcinoma was tested. The method was new in four respects. First, for fixation of the biopsies a coagulant fixative was used. Second, 2-microns plastic sections were used to ensure the reproducibility of nuclear imaging. Third, a new stereologic approach was used for calculation of the nuclear volume and DNA content. Fourth, for the classification rule the morphometric, densitometric and texture features were used in concert. The IBAS 2000 instrument was used for the measurements. Texture analysis of the chromatin patterns was performed using Markovian texture features. Using discriminant analysis, of 22 parameters, 2 morphometric, 2 densitometric and 3 texture features were selected for the classification rule. With them, 89% of the bladder carcinomas were correctly classified into the three grades. All grade III tumors were classified correctly. Among the features tested, the densitometry of the DNA had the highest F values. All of the grade III tumors and 45% of the grade II tumor group had DNA histograms indicating aneuploidy. This study showed that plastic-embedded material is well suited to morphometry and densitometry and can be used for quantitative grading of bladder carcinoma.     

When the Background Matters: Using Scenarios from Integrated Assessment Models in Prospective Life Cycle Assessment

Prospective life cycle assessment (LCA) needs to deal with the large epistemological uncertainty about the future to support more robust future environmental impact assessments of technologies. This study proposes a novel approach that systematically changes the background processes in a prospective LCA based on scenarios of an integrated assessment model (IAM), the IMAGE model. Consistent worldwide scenarios from IMAGE are evaluated in the life cycle inventory using ecoinvent v3.3. To test the approach, only the electricity sector was changed in a prospective LCA of an internal combustion engine vehicle (ICEV) and an electric vehicle (EV) using six baseline and mitigation climate scenarios until 2050. This case study shows that changes in the electricity background can be very important for the environmental impacts of EV. Also, the approach demonstrates that the relative environmental performance of EV and ICEV over time is more complex and multifaceted than previously assumed. Uncertainty due to future developments manifests in different impacts depending on the product (EV or ICEV), the impact category, and the scenario and year considered. More robust prospective LCAs can be achieved, particularly for emerging technologies, by expanding this approach to other economic sectors beyond electricity background changes and mobility applications as well as by including uncertainty and changes in foreground parameters. A more systematic and structured composition of future inventory databases driven by IAM scenarios helps to acknowledge epistemological uncertainty and to increase the temporal consistency of foreground and background systems in LCAs of emerging technologies.