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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.
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.
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.
The emergence of carbapenemase-producing multi-drug resistant Enterobacteriaceae poses a dramatic, world-wide health risk. Limited treatment options and a lack of easy-to-use methods for the detection of infections with multi-drug resistant bacteria leave the health-care system with a fast-growing challenge. Aptamers are single stranded DNA or RNA molecules that bind to their targets with high affinity and specificity and can therefore serve as outstanding detection probes. However, an effective aptamer selection process is often hampered by non-specific binding. When selections are carried out against recombinant proteins, purification tags (e.g. polyhistidine) serve as attractive side targets, which may impede protein target binding. In this study, aptamer selection was carried out against N-terminally hexa-histidine tagged New Delhi metallo-ss-lactamase 1. After 14 selection rounds binding to polyhistidine was detected rather than to New Delhi metallo-ss-lactamase 1. Hence, the selection strategy was changed. As one aptamer candidate showed remarkable binding affinity to polyhistidine, it was used as a masking probe and selection was restarted from selection round 10. Finally, after three consecutive selection rounds, an aptamer with specific binding properties to New Delhi metallo-ss-lactamase 1 was identified. This aptamer may serve as a much-needed detection probe for New Delhi metallo-ss-lactamase 1 expressing Enterobacteriaceae.
In June 2019, more than a hundred plant researchers met in Cologne, Germany, for the 6th European Workshop on Plant Chromatin (EWPC). This conference brought together a highly dynamic community of researchers with the common aim to understand how chromatin organization controls gene expression, development, and plant responses to the environment. New evidence showing how epigenetic states are set, perpetuated, and inherited were presented, and novel data related to the three-dimensional organization of chromatin within the nucleus were discussed. At the level of the nucleosome, its composition by different histone variants and their specialized histone deposition complexes were addressed as well as the mechanisms involved in histone post-translational modifications and their role in gene expression. The keynote lecture on plant DNA methylation by Julie Law (SALK Institute) and the tribute session to Lars Hennig, honoring the memory of one of the founders of the EWPC who contributed to promote the plant chromatin and epigenetic field in Europe, added a very special note to this gathering. In this perspective article we summarize some of the most outstanding data and advances on plant chromatin research presented at this workshop.
Background
Secondary endosymbionts of aphids provide benefits to their hosts, but also impose costs such as reduced lifespan and reproductive output. The aphid Aphis fabae is host to different strains of the secondary endosymbiont Hamiltonella defensa, which encode different putative toxins. These strains have very different phenotypes: They reach different densities in the host, and the costs and benefits (protection against parasitoid wasps) they confer to the host vary strongly.
Results
We used RNA-Seq to generate hypotheses on why four of these strains inflict such different costs to A. fabae. We found different H. defensa strains to cause strain-specific changes in aphid gene expression, but little effect of H. defensa on gene expression of the primary endosymbiont, Buchnera aphidicola. The highly costly and over-replicating H. defensa strain H85 was associated with strongly reduced aphid expression of hemocytin, a marker of hemocytes in Drosophila. The closely related strain H15 was associated with downregulation of ubiquitin-related modifier 1, which is related to nutrient-sensing and oxidative stress in other organisms. Strain H402 was associated with strong differential regulation of a set of hypothetical proteins, the majority of which were only differentially regulated in presence of H402.
Conclusions
Overall, our results suggest that costs of different strains of H. defensa are likely caused by different mechanisms, and that these costs are imposed by interacting with the host rather than the host's obligatory endosymbiont B. aphidicola.
Physically interacting proteins form macromolecule complexes that drive diverse cellular processes. Advances in experimental techniques that capture interactions between proteins provide us with protein-protein interaction (PPI) networks from several model organisms. These datasets have enabled the prediction and other computational analyses of protein complexes. Here we provide a systematic review of the state-of-the-art algorithms for protein complex prediction from PPI networks proposed in the past two decades. The existing approaches that solve this problem are categorized into three groups, including: cluster-quality-based, node affinity-based, and network embedding-based approaches, and we compare and contrast the advantages and disadvantages. We further include a comparative analysis by computing the performance of eighteen methods based on twelve well-established performance measures on four widely used benchmark protein-protein interaction networks. Finally, the limitations and drawbacks of both, current data and approaches, along with the potential solutions in this field are discussed, with emphasis on the points that pave the way for future research efforts in this field. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).
A Cell-free Expression Pipeline for the Generation and Functional Characterization of Nanobodies
(2022)
Cell-free systems are well-established platforms for the rapid synthesis, screening, engineering and modification of all kinds of recombinant proteins ranging from membrane proteins to soluble proteins, enzymes and even toxins. Also within the antibody field the cell-free technology has gained considerable attention with respect to the clinical research pipeline including antibody discovery and production. Besides the classical full-length monoclonal antibodies (mAbs), so-called "nanobodies" (Nbs) have come into focus. A Nb is the smallest naturally-derived functional antibody fragment known and represents the variable domain (VHH, similar to 15 kDa) of a camelid heavy-chain-only antibody (HCAb). Based on their nanoscale and their special structure, Nbs display striking advantages concerning their production, but also their characteristics as binders, such as high stability, diversity, improved tissue penetration and reaching of cavity-like epitopes. The classical way to produce Nbs depends on the use of living cells as production host. Though cell-based production is well-established, it is still time-consuming, laborious and hardly amenable for high-throughput applications. Here, we present for the first time to our knowledge the synthesis of functional Nbs in a standardized mammalian cell-free system based on Chinese hamster ovary (CHO) cell lysates. Cell-free reactions were shown to be time-efficient and easy-to-handle allowing for the "on demand" synthesis of Nbs. Taken together, we complement available methods and demonstrate a promising new system for Nb selection and validation.
Simple Summary:& nbsp;High alpine meadows are home to numerous endemic butterfly species. A combination of climate change and changes in agricultural practices has led to a severe decline in many species. A seemingly unaffected representative of this habitat is Erebia pronoe. We studied the behaviour, resource use and population structure of this species to explain its resilience and estimate its future survival potential. This species shows pronounced protandry in combination with serial eclosion. Males were significantly more active and mobile and were also caught significantly more often than females, resulting in a pronounced shift in sex ratio in the predicted population structure. The adults use a wide range of nectar plants and establish homeranges in areas of high habitat quality. Thus, Erebia pronoe adults use a wide array of resources combined with a slight specialisation to avoid niche overlap with closely related species. The resulting ecological flexibility seems to be an adaptation to unpredictable environmental conditions, which should be the result of a long-lasting adaptation process. Moreover, the combination of opportunism and modest specialisation should also be a good basis for coping with future changes caused by climate and land-use change.</p> <br /> <br></p> <br /> A mark-recapture study of the nominotypical Erebia pronoe in the Alps was conducted to survey its ecological demands and characteristics. Population structure analysis revealed a combination of protandry (one-week earlier eclosion of males) and serial eclosion. Significant differences between both sexes were found in population density (males: 580/ha & PLUSMN; 37 SE; females: 241/ha & PLUSMN; 66 SE), sex-ratio (2.4) and behaviour (57.7 vs. 11.9% flying). Both sexes used a wide range of nectar plants (Asteraceae, 77.3%; Dipsacaceae, 12.3%; Gentianaceae, 9.7%). The use of nectar plants shows a non-specific spectrum, which, however, completely avoids overlap with the locally co-occurring species Erebia nivalis. Movement patterns show the establishment of homeranges, which significantly limits the migration potential. Due to its broad ecological niche, E. pronoe will probably be able to react plastically to the consequences of climate change. The formation of high population densities, the unconcerned endangerment status, the unspecific resource spectrum and the sedentary character of the species make E. pronoe a potential indicator of the quality and general resource occurrence of alpine rupicolous grasslands.
Resource polymorphism is common across taxa and can result in alternate ecotypes with specific morphologies, feeding modes, and behaviors that increase performance in a specific habitat. This can result in high intraspecific variation in the expression of specific traits and the extent to which these traits are correlated within a single population. Although metabolic rate influences resource acquisition and the overall pace of life of individuals it is not clear how metabolic rate interacts with the larger suite of traits to ultimately determine individual fitness. We examined the relationship between metabolic rates and the major differences (habitat use, morphology, and resource use) between littoral and pelagic ecotypes of European perch (Perca fluviatilis) from a single lake in Central Sweden. Standard metabolic rate (SMR) was significantly higher in pelagic perch but did not correlate with resource use or morphology. Maximum metabolic rate (MMR) was not correlated with any of our explanatory variables or with SMR. Aerobic scope (AS) showed the same pattern as SMR, differing across habitats, but contrary to expectations, was lower in pelagic perch. This study helps to establish a framework for future experiments further exploring the drivers of intraspecific differences in metabolism. In addition, since metabolic rates scale with temperature and determine predator energy requirements, our observed differences in SMR across habitats will help determine ecotype-specific vulnerabilities to climate change and differences in top-down predation pressure across habitats.
An amperometric trimethylamine N-oxide (TMAO) biosensor is reported, where TMAO reductase (TorA) and glucose oxidase (GOD) and catalase (Cat) were immobilized on the electrode surface, enabling measurements of mediated enzymatic TMAO reduction at low potential under ambient air conditions. The oxygen anti-interference membrane composed of GOD, Cat and polyvinyl alcohol (PVA) hydrogel, together with glucose concentration, was optimized until the O-2 reduction current of a Clark-type electrode was completely suppressed for at least 3 h. For the preparation of the TMAO biosensor, Escherichia coli TorA was purified under anaerobic conditions and immobilized on the surface of a carbon electrode and covered by the optimized O-2 scavenging membrane. The TMAO sensor operates at a potential of -0.8 V vs. Ag/AgCl (1 M KCl), where the reduction of methylviologen (MV) is recorded. The sensor signal depends linearly on TMAO concentrations between 2 mu M and 15 mM, with a sensitivity of 2.75 +/- 1.7 mu A/mM. The developed biosensor is characterized by a response time of about 33 s and an operational stability over 3 weeks. Furthermore, measurements of TMAO concentration were performed in 10% human serum, where the lowest detectable concentration is of 10 mu M TMAO.
Background: Microbiome assembly was identified as an important factor for plant growth and health, but this process is largely unknown, especially for the fruit microbiome. Therefore, we analyzed strawberry plants of two cultivars by focusing on microbiome tracking during the different growth stages and storage using amplicon sequencing, qPCR, and microscopic approaches. <br /> Results: Strawberry plants carried a highly diverse microbiome, therein the bacterial families Sphingomonadaceae (25%), Pseudomonadaceae (17%), and Burkholderiaceae (11%); and the fungal family Mycosphaerella (45%) were most abundant. All compartments were colonized by high number of bacteria and fungi (10(7)-10(10) marker gene copies per g fresh weight), and were characterized by high microbial diversity (6049 and 1501 ASVs); both were higher for the belowground samples than in the phyllosphere. Compartment type was the main driver of microbial diversity, structure, and abundance (bacterial: 45%; fungal: 61%) when compared to the cultivar (1.6%; 2.2%). Microbiome assembly was strongly divided for belowground habitats and the phyllosphere; only a low proportion of the microbiome was transferred from soil via the rhizosphere to the phyllosphere. During fruit development, we observed the highest rates of microbial transfer from leaves and flowers to ripe fruits, where most of the bacteria occured inside the pulp. In postharvest fruits, microbial diversity decreased while the overall abundance increased. Developing postharvest decay caused by Botrytis cinerea decreased the diversity as well, and induced a reduction of potentially beneficial taxa. <br /> Conclusion: Our findings provide insights into microbiome assembly in strawberry plants and highlight the importance of microbe transfer during fruit development and storage with potential implications for food health and safety.
First Steps towards the development of epigenetic biomarkers in female cheetahs (Acinonyx jubatus)
(2022)
Free-ranging cheetahs (Acinonyx jubatus) are generally healthy, whereas cheetahs under human care, such as those in zoological gardens, suffer from ill-defined infectious and degenerative pathologies. These differences are only partially explained by husbandry management programs because both groups share low genetic diversity. However, mounting evidence suggests that physiological differences between populations in different environments can be tracked down to differences in epigenetic signatures. Here, we identified differentially methylated regions (DMRs) between free-ranging cheetahs and conspecifics in zoological gardens and prospect putative links to pathways relevant to immunity, energy balance and homeostasis. Comparing epigenomic DNA methylation profiles obtained from peripheral blood mononuclear cells (PBMCs) from eight free-ranging female cheetahs from Namibia and seven female cheetahs living in zoological gardens within Europe, we identified DMRs of which 22 were hypermethylated and 23 hypomethylated. Hypermethylated regions in cheetahs under human care were located in the promoter region of a gene involved in host-pathogen interactions (KLC1) and in an intron of a transcription factor relevant for the development of pancreatic beta-cells, liver, and kidney (GLIS3). The most canonical mechanism of DNA methylation in promoter regions is assumed to repress gene transcription. Taken together, this could indicate that hypermethylation at the promoter region of KLC1 is involved in the reduced immunity in cheetahs under human care. This approach can be generalized to characterize DNA methylation profiles in larger cheetah populations under human care with a more granular longitudinal data collection, which, in the future, could be used to monitor the early onset of pathologies, and ultimately translate into the development of biomarkers with prophylactic and/or therapeutic potential.
Identification of a super-functional Tfh-like subpopulation in murine lupus by pattern perception
(2020)
Dysregulated cytokine expression by T cells plays a pivotal role in the pathogenesis of autoimmune diseases. However, the identification of the corresponding pathogenic subpopulations is a challenge, since a distinction between physiological variation and a new quality in the expression of protein markers requires combinatorial evaluation. Here, we were able to identify a super-functional follicular helper T cell (Tfh)-like subpopulation in lupus-prone NZBxW mice with our binning approach "pattern recognition of immune cells (PRI)". PRI uncovered a subpopulation of IL-21(+) IFN-gamma(high) PD-1(low) CD40L(high) CXCR5(-) Bcl-6(-) T cells specifically expanded in diseased mice. In addition, these cells express high levels of TNF-alpha and IL-2, and provide B cell help for IgG production in an IL-21 and CD40L dependent manner. This super-functional T cell subset might be a superior driver of autoimmune processes due to a polyfunctional and high cytokine expression combined with Tfh-like properties.
Water stable isotopes (delta O-18 and delta H-2) were analyzed in samples collected in lakes, associated with riverine systems in northeastern Germany, throughout 2020. The dataset (Aichner et al., 2021; https://doi.org/10.1594/PANGAEA.935633) is derived from water samples collected at (a) lake shores (sampled in March and July 2020), (b) buoys which were temporarily installed in deep parts of the lake (sampled monthly from March to October 2020), (c) multiple spatially distributed spots in four selected lakes (in September 2020), and (d) the outflow of Muggelsee (sampled biweekly from March 2020 to January 2021). At shores, water was sampled with a pipette from 40-60 cm below the water surface and directly transferred into a measurement vial, while at buoys a Limnos water sampler was used to obtain samples from 1 m below the surface. Isotope analysis was conducted at IGB Berlin, using a Picarro L2130-i cavity ring-down spectrometer, with a measurement uncertainty of < 0.15 parts per thousand (delta O-18) and < 0.0 parts per thousand (delta H-2). The data give information about the vegetation period and the full seasonal isotope amplitude in the sampled lakes and about spatial isotope variability in different branches of the associated riverine systems.
The Brachionus calyciflorus species complex was recently subdivided into four species, but genetic resources to resolve phylogenetic relationships within this complex are still lacking. We provide two complete mitochondrial (mt) genomes from B. calyciflorus sensu stricto (Germany, USA) and the mt coding sequences (cds) from a German B. fernandoi. Phylogenetic analysis placed our B. calyciflorus sensu stricto strains close to the published genomes of B. calyciflorus, forming the putative sister species to B. fernandoi. Global representatives of B. calyciflorus sensu stricto (i.e. Europe, USA, and China) are genetically closer related to each other than to B. fernandoi (average pairwise nucleotide diversity 0.079 intraspecific vs. 0.254 interspecific).
Biodiversity conservation and agricultural production have been largely framed as separate goals for landscapes in the discourse on land use. Although there is an increasing tendency to move away from this dichotomy in theory, the tendency is perpetuated by the spatially explicit approaches used in research and management practice. Transition zones (TZ) have previously been defined as areas where two adjacent fields or patches interact, and so they occur abundantly throughout agricultural landscapes. Biodiversity patterns in TZ have been extensively studied, but their relationship to yield patterns and social-ecological dimensions has been largely neglected. Focusing on European, temperate agricultural landscapes, we outline three areas of research and management that together demonstrate how TZ might be used to facilitate an integrated landscape approach: (i) plant and animal species' use and response to boundaries and the resulting effects on yield, for a deeper understanding of how landscape structure shapes quantity and quality of TZ; (ii) local knowledge on field or patch-level management and its interactions with biodiversity and yield in TZ, and (iii) conflict prevention and collaborative management across land-use boundaries.