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Institute
- Institut für Biochemie und Biologie (179) (remove)
Aldehyde oxidases (AOXs) are a small group of enzymes belonging to the larger family of molybdo-flavoenzymes, along with the well-characterized xanthine oxidoreductase. The two major types of reactions that are catalyzed by AOXs are the hydroxylation of heterocycles and the oxidation of aldehydes to their corresponding carboxylic acids. Different animal species have different complements of AOX genes. The two extremes are represented in humans and rodents; whereas the human genome contains a single active gene (AOX1), those of rodents, such as mice, are endowed with four genes (Aox1-4), clustering on the same chromosome, each encoding a functionally distinct AOX enzyme. It still remains enigmatic why some species have numerous AOX enzymes, whereas others harbor only one functional enzyme. At present, little is known about the physiological relevance of AOX enzymes in humans and their additional forms in other mammals. These enzymes are expressed in the liver and play an important role in the metabolisms of drugs and other xenobiotics. In this review, we discuss the expression, tissue-specific roles, and substrate specificities of the different mammalian AOX enzymes and highlight insights into their physiological roles.
Broad and unspecific use of antibiotics accelerates spread of resistances. Sensitive and robust pathogen detection is thus important for a more targeted application. Bacteriophages contain a large repertoire of pathogen-binding proteins. These tailspike proteins (TSP) often bind surface glycans and represent a promising design platform for specific pathogen sensors. We analysed bacteriophage Sf6 TSP that recognizes the O-polysaccharide of dysentery-causing Shigella flexneri to develop variants with increased sensitivity for sensor applications. Ligand polyrhamnose backbone conformations were obtained from 2D H-1,H-1-trNOESY NMR utilizing methine-methine and methine-methyl correlations. They agreed well with conformations obtained from molecular dynamics (MD), validating the method for further predictions. In a set of mutants, MD predicted ligand flexibilities that were in good correlation with binding strength as confirmed on immobilized S. flexneri O-polysaccharide (PS) with surface plasmon resonance. In silico approaches combined with rapid screening on PS surfaces hence provide valuable strategies for TSP-based pathogen sensor design.
In nature, plants are constantly exposed to many transient, but recurring, stresses. Thus, to complete their life cycles, plants require a dynamic balance between capacities to recover following cessation of stress and maintenance of stress memory. Recently, we uncovered a new functional role for macroautophagy/autophagy in regulating recovery from heat stress (HS) and resetting cellular memory of HS inArabidopsis thaliana. Here, we demonstrated that NBR1 (next to BRCA1 gene 1) plays a crucial role as a receptor for selective autophagy during recovery from HS. Immunoblot analysis and confocal microscopy revealed that levels of the NBR1 protein, NBR1-labeled puncta, and NBR1 activity are all higher during the HS recovery phase than before. Co-immunoprecipitation analysis of proteins interacting with NBR1 and comparative proteomic analysis of annbr1-null mutant and wild-type plants identified 58 proteins as potential novel targets of NBR1. Cellular, biochemical and functional genetic studies confirmed that NBR1 interacts with HSP90.1 (heat shock protein 90.1) and ROF1 (rotamase FKBP 1), a member of the FKBP family, and mediates their degradation by autophagy, which represses the response to HS by attenuating the expression ofHSPgenes regulated by the HSFA2 transcription factor. Accordingly, loss-of-function mutation ofNBR1resulted in a stronger HS memory phenotype. Together, our results provide new insights into the mechanistic principles by which autophagy regulates plant response to recurrent HS.
Both climate change and land use regimes affect the viability of populations, but they are often studied separately. Moreover, population viability analyses (PVAs) often ignore the effects of large environmental gradients and use temporal resolutions that are too coarse to take into account that different stages of a population's life cycle may be affected differently by climate change. Here, we present the High-resolution Large Environmental Gradient (HiLEG) model and apply it in a PVA with daily resolution based on daily climate projections for Northwest Germany. We used the large marsh grasshopper (LMG) as the target species and investigated (1) the effects of climate change on the viability and spatial distribution of the species, (2) the influence of the timing of grassland mowing on the species and (3) the interaction between the effects of climate change and grassland mowing. The stageand cohort-based model was run for the spatially differentiated environmental conditions temperature and soil moisture across the whole study region. We implemented three climate change scenarios and analyzed the population dynamics for four consecutive 20-year periods. Climate change alone would lead to an expansion of the regions suitable for the LMG, as warming accelerates development and due to reduced drought stress. However, in combination with land use, the timing of mowing was crucial, as this disturbance causes a high mortality rate in the aboveground life stages. Assuming the same date of mowing throughout the region, the impact on viability varied greatly between regions due to the different climate conditions. The regional negative effects of the mowing date can be divided into five phases: (1) In early spring, the populations were largely unaffected in all the regions; (2) between late spring and early summer, they were severely affected only in warm regions; (3) in summer, all the populations were severely affected so that they could hardly survive; (4) between late summer and early autumn, they were severely affected in cold regions; and (5) in autumn, the populations were equally affected across all regions. The duration and start of each phase differed slightly depending on the climate change scenario and simulation period, but overall, they showed the same pattern. Our model can be used to identify regions of concern and devise management recommendations. The model can be adapted to the life cycle of different target species, climate projections and disturbance regimes. We show with our adaption of the HiLEG model that high-resolution PVAs and applications on large environmental gradients can be reconciled to develop conservation strategies capable of dealing with multiple stressors.
Forage availability has been suggested as one driver of the observed decline in honey bees. However, little is known about the effects of its spatiotemporal variation on colony success. We present a modeling framework for assessing honey bee colony viability in cropping systems. Based on two real farmland structures, we developed a landscape generator to design cropping systems varying in crop species identity, diversity, and relative abundance. The landscape scenarios generated were evaluated using the existing honey bee colony model BEEHAVE, which links foraging to in-hive dynamics. We thereby explored how different cropping systems determine spatiotemporal forage availability and, in turn, honey bee colony viability (e.g., time to extinction, TTE) and resilience (indicated by, e.g., brood mortality). To assess overall colony viability, we developed metrics,P(H)andP(P,)which quantified how much nectar and pollen provided by a cropping system per year was converted into a colony's adult worker population. Both crop species identity and diversity determined the temporal continuity in nectar and pollen supply and thus colony viability. Overall farmland structure and relative crop abundance were less important, but details mattered. For monocultures and for four-crop species systems composed of cereals, oilseed rape, maize, and sunflower,P(H)andP(P)were below the viability threshold. Such cropping systems showed frequent, badly timed, and prolonged forage gaps leading to detrimental cascading effects on life stages and in-hive work force, which critically reduced colony resilience. Four-crop systems composed of rye-grass-dandelion pasture, trefoil-grass pasture, sunflower, and phacelia ensured continuous nectar and pollen supply resulting in TTE > 5 yr, andP(H)(269.5 kg) andP(P)(108 kg) being above viability thresholds for 5 yr. Overall, trefoil-grass pasture, oilseed rape, buckwheat, and phacelia improved the temporal continuity in forage supply and colony's viability. Our results are hypothetical as they are obtained from simplified landscape settings, but they nevertheless match empirical observations, in particular the viability threshold. Our framework can be used to assess the effects of cropping systems on honey bee viability and to develop land-use strategies that help maintain pollination services by avoiding prolonged and badly timed forage gaps.
Studies on the diversity, distribution and ecological role of Saprolegniales (Oomycota) in freshwater ecosystems are currently receiving attention due to a greater understanding of their role in carbon cycling in various aquatic ecosystems. In this study, we characterized several Saprolegniales species isolated from Anzali lagoon, Gilan province, Iran, using morphological and molecular methods. Four species of Saprolegnia were identified, including S. anisospora and S. diclina as first reports for Iran, as well as Achlya strains, which were closely related to A. bisexualis, A. debaryana and A. intricata. Evaluation of the ligno-, cellulo- and chitinolytic activities was performed using plate assay methods. Most of the Saprolegniales isolates were obtained in autumn, and nearly 50% of the strains showed chitinolytic and cellulolytic activities. However, only a few Saprolegniales strains showed lignolytic activities. This study has important implications for better understanding the ecological niche of oomycetes, and to differentiate them from morphologically similar, but functionally different aquatic fungi in freshwater ecosystems.
Monocytes and macrophages are key players in maintaining immune homeostasis. Identifying strategies to manipulate their functions via gene delivery is thus of great interest for immunological research and biomedical applications. We set out to establish conditions for mRNA transfection in hard-to-transfect primary human monocytes and monocyte-derived macrophages due to the great potential of gene expression from in vitro transcribed mRNA for modulating cell phenotypes. mRNA doses, nucleotide modifications, and different carriers were systematically explored in order to optimize high mRNA transfer rates while minimizing cell stress and immune activation. We selected three commercially available mRNA transfection reagents including liposome and polymer-based formulations, covering different application spectra. Our results demonstrate that liposomal reagents can particularly combine high gene transfer rates with only moderate immune cell activation. For the latter, use of specific nucleotide modifications proved essential. In addition to improving efficacy of gene transfer, our findings address discrete aspects of innate immune activation using cytokine and surface marker expression, as well as cell viability as key readouts to judge overall transfection efficiency. The impact of this study goes beyond optimizing transfection conditions for immune cells, by providing a framework for assessing new gene carrier systems for monocyte and macrophage, tailored to specific applications.
Metagenomic sequencing has revolutionised our knowledge of virus diversity, with new virus sequences being reported faster than ever before. However, virus discovery from metagenomic sequencing usually depends on detectable homology: without a sufficiently close relative, so-called ‘dark’ virus sequences remain unrecognisable. An alternative approach is to use virus-identification methods that do not depend on detecting homology, such as virus recognition by host antiviral immunity. For example, virus-derived small RNAs have previously been used to propose ‘dark’ virus sequences associated with the Drosophilidae (Diptera). Here, we combine published Drosophila data with a comprehensive search of transcriptomic sequences and selected meta-transcriptomic datasets to identify a completely new lineage of segmented positive-sense single-stranded RNA viruses that we provisionally refer to as the Quenyaviruses. Each of the five segments contains a single open reading frame, with most encoding proteins showing no detectable similarity to characterised viruses, and one sharing a small number of residues with the RNA-dependent RNA polymerases of single- and double-stranded RNA viruses. Using these sequences, we identify close relatives in approximately 20 arthropods, including insects, crustaceans, spiders, and a myriapod. Using a more conserved sequence from the putative polymerase, we further identify relatives in meta-transcriptomic datasets from gut, gill, and lung tissues of vertebrates, reflecting infections of vertebrates or of their associated parasites. Our data illustrate the utility of small RNAs to detect viruses with limited sequence conservation, and provide robust evidence for a new deeply divergent and phylogenetically distinct RNA virus lineage.