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Activated carbon has become a widely used tool to investigate root-mediated allelopathy of plants, especially in plant invasion biology, because it adsorbs and thereby neutralizes root exudates. Allelopathy has been a controversially debated phenomenon for years, which revived in plant invasion biology as one possible reason for the success of invasive plants. Noxious plant exudates may harm other plants and provide an advantage to the allelopathic plant. However, root exudates are not always toxic, but may stimulate the microbial community and change nutrient availability in the rhizosphere. In a greenhouse experiment, we investigated the interacting effects of activated carbon, arbuscular mycorrhiza and plant competition between the invasive Senecio inaequidens and the native Artemisia vulgaris. Furthermore, we tested whether activated carbon showed any undesired effects by directly affecting mycorrhiza or soil chemistry. Contrary to the expectation, S. inaequidens was a weak competitor and we could not support the idea that allelopathy was involved in the competition. Activated carbon led to a considerable increase in the aboveground biomass production and reduced the infection with arbuscular mycorrhiza of both plant species. We expected that arbuscular mycorrhiza promotes plant growth by increasing nutrient availability, but we found the contrary when activated carbon was added. Chemical analyses of the substrate showed, that adding activated carbon resulted in a strong increase in plant available phosphate and in a decrease of the C-organic/N-total ration both of which suggest stimulated microbial activity. Thus, activated carbon not only reduced potential allelopathic effects, but substantially changed the chemistry of the substrate. These results show that activated carbon should be handled with great care in ecological experiments on allelopathy because of possible confounding effects on the soil community.
Hantaviruses are enveloped viruses that possess a tri-segmented, negative-sense RNA genome.
The viral S-segment encodes the multifunctional nucleocapsid protein (N), which is involved in genome packaging, intracellular protein transport, immunoregulation, and several other crucial processes during hantavirus infection.
In this study, we generated fluorescently tagged N protein constructs derived from Puumalavirus (PUUV), the dominant hantavirus species in Central, Northern, and Eastern Europe.
We comprehensively characterized this protein in the rodent cell line CHO-K1, monitoring the dynamics of N protein complex formation and investigating co-localization with host proteins as well as the viral glycoproteins Gc and Gn.
We observed formation of large, fibrillar PUUV N protein aggregates, rapidly coalescing from early punctate and spike-like assemblies.
Moreover, we found significant spatial correlation of N with vimentin, actin, and P-bodies but not with microtubules. N constructs also co-localized with Gn and Gc albeit not as strongly as the glycoproteins associated with each other.
Finally, we assessed oligomerization of N constructs, observing efficient and concentration-dependent multimerization, with complexes comprising more than 10 individual proteins.
Silvicultural practices lead to changes in forest composition and structure and may impact species diversity from the overall regional species pool to stand-level species occurrence. We explored to what extent fine-scale occupancy patterns in differently managed forest stands are driven by environment and ecological traits in three regions in Germany using a multi-species hierarchical model. We tested for the possible impact of environmental variables and ecological traits on occupancy dynamics in a joint modelling exercise while taking possible variation in coefficient estimates over years and plots into account. Bird species richness differed across regions and years, and trends in species richness across years were different in the three regions. On the species level, forest management affected occupancy of species in all regions, but only 35% of the total assemblage-level variation in occurrence probability was explained by either forest type and successional stage and <?1% by forest edge. On the assemblage level, bird occurrence decreased with body mass in all regions. Species with smaller breeding ranges had lower occurrence probabilities in one region, while later spring arrival decreased occurrence probabilities in the two other regions. Spatial variation in the effect size of trait covariates such as species phylogeny and breeding strata showed that variation in patch occupancy due to fine-scale differences in forest management is, to some extent, predictable from ecological traits. Our results show that environmental factors and ecological traits jointly predict variation in bird occupancy patterns and their response to forest management. Observations at the fine scale of forest stands, at which conservation efforts can be arranged along with forest management practices in heterogeneous environments, have been shown to provide meaningful insights despite the difficulties involved in monitoring mobile organisms such as birds at the plot level.
Electrochemical polymerization of functionalized thiohene derivatives for immobilization of proteins
(1997)
The rewetting of drained peatlands alters peat geochemistry and often leads to sustained elevated methane emission. Although this methane is produced entirely by microbial activity, the distribution and abundance of methane-cycling microbes in rewetted peatlands, especially in fens, is rarely described. In this study, we compare the community composition and abundance of methane-cycling microbes in relation to peat porewater geochemistry in two rewetted fens in northeastern Germany, a coastal brackish fen and a freshwater riparian fen, with known high methane fluxes. We utilized 16S rRNA high-throughput sequencing and quantitative polymerase chain reaction (qPCR) on 16S rRNA, mcrA, and pmoA genes to determine microbial community composition and the abundance of total bacteria, methanogens, and methanotrophs. Electrical conductivity (EC) was more than 3 times higher in the coastal fen than in the riparian fen, averaging 5.3 and 1.5 mS cm(-1), respectively. Porewater concentrations of terminal electron acceptors (TEAs) varied within and among the fens. This was also reflected in similarly high intra- and inter-site variations of microbial community composition. Despite these differences in environmental conditions and electron acceptor availability, we found a low abundance of methanotrophs and a high abundance of methanogens, represented in particular by Methanosaetaceae, in both fens. This suggests that rapid (re) establishment of methanogens and slow (re) establishment of methanotrophs contributes to prolonged increased methane emissions following rewetting.
COMMIT
(2022)
Composition and functions of microbial communities affect important traits in diverse hosts, from crops to humans. Yet, mechanistic understanding of how metabolism of individual microbes is affected by the community composition and metabolite leakage is lacking. Here, we first show that the consensus of automatically generated metabolic reconstructions improves the quality of the draft reconstructions, measured by comparison to reference models. We then devise an approach for gap filling, termed COMMIT, that considers metabolites for secretion based on their permeability and the composition of the community. By applying COMMIT with two soil communities from the Arabidopsis thaliana culture collection, we could significantly reduce the gap-filling solution in comparison to filling gaps in individual reconstructions without affecting the genomic support. Inspection of the metabolic interactions in the soil communities allows us to identify microbes with community roles of helpers and beneficiaries. Therefore, COMMIT offers a versatile fully automated solution for large-scale modelling of microbial communities for diverse biotechnological applications. <br /> Author summaryMicrobial communities are important in ecology, human health, and crop productivity. However, detailed information on the interactions within natural microbial communities is hampered by the community size, lack of detailed information on the biochemistry of single organisms, and the complexity of interactions between community members. Metabolic models are comprised of biochemical reaction networks based on the genome annotation, and can provide mechanistic insights into community functions. Previous analyses of microbial community models have been performed with high-quality reference models or models generated using a single reconstruction pipeline. However, these models do not contain information on the composition of the community that determines the metabolites exchanged between the community members. In addition, the quality of metabolic models is affected by the reconstruction approach used, with direct consequences on the inferred interactions between community members. Here, we use fully automated consensus reconstructions from four approaches to arrive at functional models with improved genomic support while considering the community composition. We applied our pipeline to two soil communities from the Arabidopsis thaliana culture collection, providing only genome sequences. Finally, we show that the obtained models have 90% genomic support and demonstrate that the derived interactions are corroborated by independent computational predictions.
Rhizophagus irregularis is one of the most extensively studied arbuscular mycorrhizal fungi (AMF) that forms symbioses with and improves the performance of many crops. Lack of transformation protocol for R. irregularis renders it challenging to investigate molecular mechanisms that shape the physiology and interactions of this AMF with plants.
Here, we used all published genomics, transcriptomics, and metabolomics resources to gain insights into the metabolic functionalities of R. irregularis by reconstructing its high-quality genome-scale metabolic network that considers enzyme constraints. Extensive validation tests with the enzyme-constrained metabolic model demonstrated that it can be used to (i) accurately predict increased growth of R. irregularis on myristate with minimal medium; (ii) integrate enzyme abundances and carbon source concentrations that yield growth predictions with high and significant Spearman correlation (rS = 0.74) to measured hyphal dry weight; and (iii) simulate growth rate increases with tighter association of this AMF with the host plant across three fungal structures.
Based on the validated model and system-level analyses that integrate data from transcriptomics studies, we predicted that differences in flux distributions between intraradical mycelium and arbuscles are linked to changes in amino acid and cofactor biosynthesis.
Therefore, our results demonstrated that the enzyme-constrained metabolic model can be employed to pinpoint mechanisms driving developmental and physiological responses of R. irregularis to different environmental cues.
In conclusion, this model can serve as a template for other AMF and paves the way to identify metabolic engineering strategies to modulate fungal metabolic traits that directly affect plant performance.
IMPORTANCE Mounting evidence points to the benefits of the symbiotic interactions between the arbuscular mycorrhiza fungus Rhizophagus irregularis and crops; however, the molecular mechanisms underlying the physiological responses of this fungus to different host plants and environments remain largely unknown.
We present a manually curated, enzyme-constrained, genome-scale metabolic model of R. irregularis that can accurately predict experimentally observed phenotypes.
We show that this high-quality model provides an entry point into better understanding the metabolic and physiological responses of this fungus to changing environments due to the availability of different nutrients.
The model can be used to design metabolic engineering strategies to tailor R. irregularis metabolism toward improving the performance of host plants.
Proteasomes are key proteases in regulating protein homeostasis. Their holo-enzymes are composed of 40 different subunits which are arranged in a proteolytic core (CP) flanked by one to two regulatory particles (RP). Proteasomal proteolysis is essential for the degradation of proteins which control time-sensitive processes like cell cycle progression and stress response. In dividing yeast and human cells, proteasomes are primarily nuclear suggesting that proteasomal proteolysis is mainly required in the nucleus during cell proliferation. In yeast, which have a closed mitosis, proteasomes are imported into the nucleus as immature precursors via the classical import pathway. During quiescence, the reversible absence of proliferation induced by nutrient depletion or growth factor deprivation, proteasomes move from the nucleus into the cytoplasm. In the cytoplasm of quiescent yeast, proteasomes are dissociated into CP and RP and stored in membrane-less cytoplasmic foci, named proteasome storage granules (PSGs). With the resumption of growth, PSGs clear and mature proteasomes are transported into the nucleus by Blm10, a conserved 240 kDa protein and proteasome-intrinsic import receptor. How proteasomes are exported from the nucleus into the cytoplasm is unknown.
Several morphological and mitochondrial lineages of the alpine ringlet butterfly species Erebia pronoe have been described, indicating a complex phylogenetic structure. However, the existing data were insufficient and allow neither a reconstruction of the biogeographic history, nor an assessment of the genetic lineages. Therefore, we analysed mitochondrial (COI, NDI) and nuclear (EF1 alpha, RPS5) gene sequences and compared them with sequences from the sister species Erebia melas. Additionally, we combined this information with morphometric data of the male genitalia and the infection patterns with Wolbachia strains, based on a WSP analysis. We obtained a distinct phylogeographic structure within the E. pronoe-melas complex with eight well-distinguishable geographic groups, but also a remarkable mito-nuclear discordance. The mito-nuclear discordance in E. melas and E. pronoe glottis can be explained by different ages of Wolbachia infections with different Wolbachia strains, associated selective sweeps, and hybridisation inhibition. Additionally, we found indications for incipient speciation of E. pronoe glottis in the Pyrenees and a pronounced range dynamic within and among the other high mountain systems of Europe. Our results emphasize the importance of combined approaches in reconstructing biogeographic patterns and evaluating phylogeographic splits.