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Achromatium oxaliferum is a large sulfur bacterium easily recognized by large intracellular calcium carbonate bodies. Although these bodies often fill major parts of the cells' volume, their role and specific intracellular location are unclear. In this study, we used various microscopy and staining techniques to identify the cell compartment harboring the calcium carbonate bodies. We observed that Achromatium cells often lost their calcium carbonate bodies, either naturally or induced by treatments with diluted acids, ethanol, sodium bicarbonate and UV radiation which did not visibly affect the overall shape and motility of the cells (except for UV radiation). The water-soluble fluorescent dye fluorescein easily diffused into empty cavities remaining after calcium carbonate loss. Membranes (stained with Nile Red) formed a network stretching throughout the cell and surrounding empty or filled calcium carbonate cavities. The cytoplasm (stained with FITC and SYBR Green for nucleic acids) appeared highly condensed and showed spots of dissolved Ca2+ (stained with Fura-2). From our observations, we conclude that the calcium carbonate bodies are located in the periplasm, in extra-cytoplasmic pockets of the cytoplasmic membrane and are thus kept separate from the cell's cytoplasm. This periplasmic localization of the carbonate bodies might explain their dynamic formation and release upon environmental changes.
Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species' populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host-pathogen systems. We adapted an established individual-based model of host-pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host's explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life-history events affect host-pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts' biological events. However, a temporal mismatch reduced host-pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat-dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host-pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change.
In many species, dispersal is decisive for survival in a changing climate. Simulation models for population dynamics under climate change thus need to account for this factor. Moreover, large numbers of species inhabiting agricultural landscapes are subject to disturbances induced by human land use. We included dispersal in the HiLEG model that we previously developed to study the interaction between climate change and agricultural land use in single populations. Here, the model was parameterized for the large marsh grasshopper (LMG) in cultivated grasslands of North Germany to analyze (1) the species development and dispersal success depending on the severity of climate change in subregions, (2) the additional effect of grassland cover on dispersal success, and (3) the role of dispersal in compensating for detrimental grassland mowing. Our model simulated population dynamics in 60-year periods (2020-2079) on a fine temporal (daily) and high spatial (250 x 250 m(2)) scale in 107 subregions, altogether encompassing a range of different grassland cover, climate change projections, and mowing schedules. We show that climate change alone would allow the LMG to thrive and expand, while grassland cover played a minor role. Some mowing schedules that were harmful to the LMG nevertheless allowed the species to moderately expand its range. Especially under minor climate change, in many subregions dispersal allowed for mowing early in the year, which is economically beneficial for farmers. More severe climate change could facilitate LMG expansion to uninhabited regions but would require suitable mowing schedules along the path. These insights can be transferred to other species, given that the LMG is considered a representative of grassland communities. For more specific predictions on the dynamics of other species affected by climate change and land use, the publicly available HiLEG model can be easily adapted to the characteristics of their life cycle.
Vegetation with an adequate supply of water might contribute to cooling the land surface around it through the latent heat flux of transpiration. This study investigates the potential estimation of evaporative cooling at plot scale, using soybean as example. Some of the plants' physiological parameters were monitored and sampled at weekly intervals. A physics-based model was then applied to estimate the irrigation-induced cooling effect within and above the canopy during the middle and late season of the soybean growth period. We then examined the results of the temperature changes at a temporal resolution of ten minutes between every two irrigation rounds. During the middle and late season of growth, the cooling effects caused by evapotranspiration within and above the canopy were, on average, 4.4 K and 2.9 K, respectively. We used quality indicators such as R-squared (R-2) and mean absolute error (MAE) to evaluate the performance of the model simulation. The performance of the model in this study was better above the canopy (R-2 = 0.98, MAE = 0.3 K) than below (R-2 = 0.87, MAE = 0.9 K) due to the predefined thermodynamic condition used to estimate evaporative cooling. Moreover, the study revealed that canopy cooling contributes to mitigating heat stress conditions during the middle and late seasons of crop growth.
Development of a CRISPR/Cas gene editing technique for the coccolithophore Chrysotila carterae
(2024)
The pace-of-life syndrome (POLS) hypothesis posits that suites of traits are correlated along a slow-fast continuum owing to life history trade-offs. Despite widespread adoption, environmental conditions driving the emergence of POLS remain unclear. A recently proposed conceptual framework of POLS suggests that a slow-fast continuum should align to fluctuations in density-dependent selection. We tested three key predictions made by this framework with an ecoevolutionary agent-based population model. Selection acted on responsiveness (behavioral trait) to interpatch resource differences and the reproductive investment threshold (life history trait). Across environments with density fluctuations of different magnitudes, we observed the emergence of a common axis of trait covariation between and within populations (i.e., the evolution of a POLS). Slow-type (fast-type) populations with high (low) responsiveness and low (high) reproductive investment threshold were selected at high (low) population densities and less (more) intense and frequent density fluctuations. In support of the predictions, fast-type populations contained a higher degree of variation in traits and were associated with higher intrinsic reproductive rate (r(0)) and higher sensitivity to intraspecific competition (gamma), pointing to a universal trade-off. While our findings support that POLS aligns with density-dependent selection, we discuss possible mechanisms that may lead to alternative evolutionary pathways.
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.
The use of alternating current (AC) electrokinetic forces, like dielectrophoresis and AC electroosmosis, as a simple and fast method to immobilize sub-micrometer objects onto nanoelectrode arrays is presented. Due to its medical relevance, the influenza virus is chosen as a model organism. One of the outstanding features is that the immobilization of viral material to the electrodes can be achieved permanently, allowing subsequent handling independently from the electrical setup. Thus, by using merely electric fields, we demonstrate that the need of prior chemical surface modification could become obsolete. The accumulation of viral material over time is observed by fluorescence microscopy. The influences of side effects like electrothermal fluid flow, causing a fluid motion above the electrodes and causing an intensity gradient within the electrode array, are discussed. Due to the improved resolution by combining fluorescence microscopy with deconvolution, it is shown that the viral material is mainly drawn to the electrode edge and to a lesser extent to the electrode surface. Finally, areas of application for this functionalization technique are presented.
Selection of high-performance lines with respect to traits of interest is a key step in plant breeding. Genomic prediction allows to determine the genomic estimated breeding values of unseen lines for trait of interest using genetic markers, e.g. single-nucleotide polymorphisms (SNPs), and machine learning approaches, which can therefore shorten breeding cycles, referring to genomic selection (GS). Here, we applied GS approaches in two populations of Solanaceous crops, i.e. tomato and pepper, to predict morphometric and colorimetric traits. The traits were measured by using scoring-based conventional descriptors (CDs) as well as by Tomato Analyzer (TA) tool using the longitudinally and latitudinally cut fruit images. The GS performance was assessed in cross-validations of classification-based and regression-based machine learning models for CD and TA traits, respectively. The results showed the usage of TA traits and tag SNPs provide a powerful combination to predict morphology and color-related traits of Solanaceous fruits. The highest predictability of 0.89 was achieved for fruit width in pepper, with an average predictability of 0.69 over all traits. The multi-trait GS models are of slightly better predictability than single-trait models for some colorimetric traits in pepper. While model validation performs poorly on wild tomato accessions, the usage as many as one accession per wild species in the training set can increase the transferability of models to unseen populations for some traits (e.g. fruit shape for which predictability in unseen scenario increased from zero to 0.6). Overall, GS approaches can assist the selection of high-performance Solanaceous fruits in crop breeding.
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.