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Methane (CH4) from aquatic ecosystems contributes to about half of total global CH4 emissions to the atmosphere. Until recently, aquatic biogenic CH4 production was exclusively attributed to methanogenic archaea living under anoxic or suboxic conditions in sediments, bottom waters, and wetlands. However, evidence for oxic CH4 production (OMP) in freshwater, brackish, and marine habitats is increasing. Possible sources were found to be driven by various planktonic organisms supporting different OMP mechanisms. Surprisingly, submerged macrophytes have been fully ignored in studies on OMP, yet they are key components of littoral zones of ponds, lakes, and coastal systems. High CH4 concentrations in these zones have been attributed to organic substrate production promoting classic methanogenesis in the absence of oxygen. Here, we review existing studies and argue that, similar to terrestrial plants and phytoplankton, macroalgae and submerged macrophytes may directly or indirectly contribute to CH4 formation in oxic waters. We propose several potential direct and indirect mechanisms: (1) direct production of CH4; (2) production of CH4 precursors and facilitation of their bacterial breakdown or chemical conversion; (3) facilitation of classic methanogenesis; and (4) facilitation of CH4 ebullition. As submerged macrophytes occur in many freshwater and marine habitats, they are important in global carbon budgets and can strongly vary in their abundance due to seasonal and boom-bust dynamics. Knowledge on their contribution to OMP is therefore essential to gain a better understanding of spatial and temporal dynamics of CH4 emissions and thus to substantially reduce current uncertainties when estimating global CH4 emissions from aquatic ecosystems.
Advanced catalysis triggered by photothermal conversion effects has aroused increasing interest due to its huge potential in environmental purification.
In this work, we developed a novel approach to the fast degradation of 4-nitrophenol (4-Nip) using porous MoS2 nanoparticles as catalysts, which integrate the intrinsic catalytic property of MoS2 with its photothermal conversion capability.
Using assembled polystyrene-b-poly(2-vinylpyridine) block copolymers as soft templates, various MoS 2 particles were prepared, which exhibited tailored morphologies (e.g., pomegranate-like, hollow, and open porous structures).
The photothermal conversion performance of these featured particles was compared under near-infrared (NIR) light irradiation.
Intriguingly, when these porous MoS2 particles were further employed as catalysts for the reduction of 4-Nip, the reaction rate constant was increased by a factor of 1.5 under NIR illumination.
We attribute this catalytic enhancement to the open porous architecture and light-to-heat conversion performance of the MoS2 particles. This contribution offers new opportunities for efficient photothermal-assisted catalysis.
Genetic population structure defines wild boar as an urban exploiter species in Barcelona, Spain
(2022)
Urban wildlife ecology is gaining relevance as metropolitan areas grow throughout the world, reducing natural habitats and creating new ecological niches.
However, knowledge is still scarce about the colonisation processes of such urban niches, the establishment of new communities, populations and/or species, and the related changes in behaviour and life histories of urban wildlife.
Wild boar (Sus scrofa) has successfully colonised urban niches throughout Europe.
The aim of this study is to unveil the processes driving the establishment and maintenance of an urban wild boar population by analysing its genetic structure.
A set of 19 microsatellite loci was used to test whether urban wild boars in Barcelona, Spain, are an isolated population or if gene flow prevents genetic differentiation between rural and urban wild boars.
This knowledge will contribute to the understanding of the effects of synurbisation and the associated management measures on the genetic change of large mammals in urban ecosystems. Despite the unidirectional gene flow from rural to urban areas, the urban wild boars in Barcelona form an island population genotypically differentiated from the surrounding rural ones.
The comparison with previous genetic studies of urban wild boar populations suggests that forest patches act as suitable islands for wild boar genetic differentiation.
Previous results and the genetic structure of the urban wild boar population in Barcelona classify wild boar as an urban exploiter species.
These wild boar peri-urban island populations are responsible for conflict with humans and thus should be managed by reducing the attractiveness of urban areas.
The management of peri-urban wild boar populations should aim at reducing migration into urban areas and preventing phenotypic changes (either genetic or plastic) causing habituation of wild boars to humans and urban environments.
Mitochondria in animals are associated with development, as well as physiological and pathological behaviors. Several conserved mitochondrial genes exist between plants and higher eukaryotes. Yet, the similarities in mitochondrial function between plant and animal species is poorly understood. Here, we show that FMT (FRIENDLY MITOCHONDRIA) from Arabidopsis thaliana, a highly conserved homolog of the mammalian CLUH (CLUSTERED MITOCHONDRIA) gene family encoding mitochondrial proteins associated with developmental alterations and adult physiological and pathological behaviors, affects whole plant morphology and development under both stressed and normal growth conditions. FMT was found to regulate mitochondrial morphology and dynamics, germination, and flowering time. It also affects leaf expansion growth, salt stress responses and hyponastic behavior, including changes in speed of hyponastic movements. Strikingly, Cluh(+/-) heterozygous knockout mice also displayed altered locomotive movements, traveling for shorter distances and had slower average and maximum speeds in the open field test. These observations indicate that homologous mitochondrial genes may play similar roles and affect homologous functions in both plants and animals.
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.
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.
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.
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.
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.
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.
With the advent of increasingly powerful computational architectures, scientists use these possibilities to create simulations of ever-increasing size and complexity. Large-scale simulations of environmental systems require huge amounts of resources. Managing these in an operational way becomes increasingly complex and difficult to handle for individual scientists. State-of-the-art simulation infrastructures usually provide the necessary re-sources in a centralised setup, which often results in an all-or-nothing choice for the user. Here, we outline an alternative approach to handling this complexity, while rendering the use of high-performance hardware and large datasets still possible. It retains a number of desirable properties: (i) a decentralised structure, (ii) easy sharing of resources to promote collaboration and (iii) secure access to everything, including natural delegation of authority across levels and system boundaries. We show that the object capability paradigm will cover these issues, and present the first steps towards developing a simulation infrastructure based on these principles.
Next-generation sequencing methods provide comprehensive data for the analysis of structural and functional analysis of the genome. The draft genomes with low contig number and high N50 value can give insight into the structure of the genome as well as provide information on the annotation of the genome. In this study, we designed a pipeline that can be used to assemble prokaryotic draft genomes with low number of contigs and high N50 value. We aimed to use combination of two de novo assembly tools (SPAdes and IDBA-Hybrid) and evaluate the impact of this approach on the quality metrics of the assemblies. The followed pipeline was tested with the raw sequence data with short reads (< 300) for a total of 10 species from four different genera. To obtain the final draft genomes, we firstly assembled the sequences using SPAdes to find closely related organism using the extracted 16 s rRNA from it. IDBA-Hybrid assembler was used to obtain the second assembly data using the closely related organism genome. SPAdes assembler tool was implemented using the second assembly, produced by IDBA-hybrid as a hint. The results were evaluated using QUAST and BUSCO. The pipeline was successful for the reduction of the contig numbers and increasing the N50 statistical values in the draft genome assemblies while preserving the coverage of the draft genomes.
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.
Building and changing a microbiome at will and maintaining it over hundreds of generations has so far proven challenging. Despite best efforts, complex microbiomes appear to be susceptible to large stochastic fluctuations. Current capabilities to assemble and control stable complex microbiomes are limited. Here, we propose a looped mass transfer design that stabilizes microbiomes over long periods of time. Five local microbiomes were continuously grown in parallel for over 114 generations and connected by a loop to a regional pool. Mass transfer rates were altered and microbiome dynamics were monitored using quantitative high-throughput flow cytometry and taxonomic sequencing of whole communities and sorted subcommunities. Increased mass transfer rates reduced local and temporal variation in microbiome assembly, did not affect functions, and overcame stochasticity, with all microbiomes exhibiting high constancy and increasing resistance. Mass transfer synchronized the structures of the five local microbiomes and nestedness of certain cell types was eminent. Mass transfer increased cell number and thus decreased net growth rates mu'. Subsets of cells that did not show net growth mu'SCx were rescued by the regional pool R and thus remained part of the microbiome. The loop in mass transfer ensured the survival of cells that would otherwise go extinct, even if they did not grow in all local microbiomes or grew more slowly than the actual dilution rate D would allow. The rescue effect, known from metacommunity theory, was the main stabilizing mechanism leading to synchrony and survival of subcommunities, despite differences in cell physiological properties, including growth rates.
Provisioning a sufficient stable source of food requires sound knowledge about current and upcoming threats to agricultural production. To that end machine learning approaches were used to identify the prevailing climatic and soil hydrological drivers of spatial and temporal yield variability of four crops, comprising 40 years yield data each from 351 counties in Germany. Effects of progress in agricultural management and breeding were subtracted from the data prior the machine learning modelling by fitting smooth non-linear trends to the 95th percentiles of observed yield data. An extensive feature selection approach was followed then to identify the most relevant predictors out of a large set of candidate predictors, comprising various soil and meteorological data. Particular emphasis was placed on studying the uniqueness of identified key predictors. Random Forest and Support Vector Machine models yielded similar although not identical results, capturing between 50% and 70% of the spatial and temporal variance of silage maize, winter barley, winter rapeseed and winter wheat yield. Equally good performance could be achieved with different sets of predictors. Thus identification of the most reliable models could not be based on the outcome of the model study only but required expert's judgement. Relationships between drivers and response often exhibited optimum curves, especially for summer air temperature and precipitation. In contrast, soil moisture clearly proved less relevant compared to meteorological drivers. In view of the expected climate change both excess precipitation and the excess heat effect deserve more attention in breeding as well as in crop modelling.
The degree of detrimental effects inflicted on mankind by the COVID-19 pandemic increased the need to develop ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable) POCT (point of care testing) to overcome the current and any future pandemics. Much effort in research and development is currently advancing the progress to overcome the diagnostic pressure built up by emerging new pathogens. LAMP (loop-mediated isothermal amplification) is a well-researched isothermal technique for specific nucleic acid amplification which can be combined with a highly sensitive immunochromatographic readout via lateral flow assays (LFA). Here we discuss LAMP-LFA robustness, sensitivity, and specificity for SARS-CoV-2 N-gene detection in cDNA and clinical swab-extracted RNA samples. The LFA readout is designed to produce highly specific results by incorporation of biotin and FITC labels to 11-dUTP and LF (loop forming forward) primer, respectively. The LAMP-LFA assay was established using cDNA for N-gene with an accuracy of 95.65%. To validate the study, 82 SARS-CoV-2-positive RNA samples were tested. Reverse transcriptase (RT)-LAMP-LFA was positive for the RNA samples with an accuracy of 81.66%; SARS-CoV-2 viral RNA was detected by RT-LAMP-LFA for as low as CT-33. Our method reduced the detection time to 15 min and indicates therefore that RT-LAMP in combination with LFA represents a promising nucleic acid biosensing POCT platform that combines with smartphone based semi-quantitative data analysis.