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Institute
- Institut für Biochemie und Biologie (150) (remove)
Species community structures of Afrotropical butterflies differ depending on the monitoring method
(2022)
Standardised biodiversity assessment is crucial to understand community structures and population dynamics of animals.
There exist various methods to monitor biodiversity. Approaches differ depending on the target species group and the aim of study, and show advantages and disadvantages.
The obtained data and results are influenced by local environmental conditions and seasonal variability.
In a comparative approach, we studied butterfly diversity and community structure in the dryland savannah biome of south-eastern Kenya with two different methods, transect counts and bait trapping.
We repeatedly collected data throughout the dry and rainy seasons, in both near natural and anthropogenically influenced landscapes. Significantly more species and individuals were recorded by transect counts than by bait trapping, though the larger and more mobile Nymphalid species (and in particular representatives of the genus Charaxes) were comparatively overrepresented in traps.
The transect data revealed much more pronounced effects of land-use and seasonality than the trap data. These results show that the choice of data collection methods must depend on the general research question, habitat conditions and season. To study the relative variation of species diversity and abundance, the collection of a fraction of the total species diversity might be sufficient.
However, if the focus is on a largely complete recording of species diversity, the use of various collection methods is essential. More specifically, our data clearly demonstrate that transect counts represent a reasonable method for assessing butterfly diversity for the African dryland savannah region, but fails to fully capture occurrences of all species. Bait trapping can be used only as a supplementary method for assessing some few highly mobile low-density species.
Genomic prediction has revolutionized crop breeding despite remaining issues of transferability of models to unseen environmental conditions and environments. Usage of endophenotypes rather than genomic markers leads to the possibility of building phenomic prediction models that can account, in part, for this challenge. Here, we compare and contrast genomic prediction and phenomic prediction models for 3 growth-related traits, namely, leaf count, tree height, and trunk diameter, from 2 coffee 3-way hybrid populations exposed to a series of treatment-inducing environmental conditions. The models are based on 7 different statistical methods built with genomic markers and ChlF data used as predictors. This comparative analysis demonstrates that the best-performing phenomic prediction models show higher predictability than the best genomic prediction models for the considered traits and environments in the vast majority of comparisons within 3-way hybrid populations. In addition, we show that phenomic prediction models are transferrable between conditions but to a lower extent between populations and we conclude that chlorophyll a fluorescence data can serve as alternative predictors in statistical models of coffee hybrid performance. Future directions will explore their combination with other endophenotypes to further improve the prediction of growth-related traits for crops.
The Lena Delta in Siberia is the largest delta in the Arctic and as a snow-dominated ecosystem particularly vulnerable to climate change.
Using the two decades of MODerate resolution Imaging Spectroradiometer satellite acquisitions, this study investigates interannual and spatial variability of snow-cover duration and summer vegetation vitality in the Lena Delta.
We approximated snow by the application of the normalized difference snow index and vegetation greenness by the normalized difference vegetation index (NDVI). We consolidated the analyses by integrating reanalysis products on air temperature from 2001 to 2021, and air temperature, ground temperature, and the date of snow-melt from time-lapse camera (TLC) observations from the Samoylov observatory located in the central delta.
We extracted spring snow-cover duration determined by a latitudinal gradient. The 'regular year' snow-melt is transgressing from mid-May to late May within a time window of 10 days across the delta.
We calculated yearly deviations per grid cell for two defined regions, one for the delta, and one focusing on the central delta. We identified an ensemble of early snow-melt years from 2012 to 2014, with snow-melt already starting in early May, and two late snow-melt years in 2004 and 2017, with snow-melt starting in June. In the times of TLC recording, the years of early and late snow-melt were confirmed.
In the three summers after early snow-melt, summer vegetation greenness showed neither positive nor negative deviations. Whereas, vegetation greenness was reduced in 2004 after late snow-melt together with the lowest June monthly air temperature of the time series record. Since 2005, vegetation greenness is rising, with maxima in 2018 and 2021.
The NDVI rise since 2018 is preceded by up to 4 degrees C warmer than average June air temperature. The ongoing operation of satellite missions allows to monitor a wide range of land surface properties and processes that will provide urgently needed data in times when logistical challenges lead to data gaps in land-based observations in the rapidly changing Arctic.
The production of volatile organic compounds (VOCs) represents a promising strategy of plant-beneficial bacteria to control soil-borne phytopathogens.
Pseudomonas sp. PICF6 and Pseudomonas simiae PICF7 are two indigenous inhabitants of olive roots displaying effective biological control against Verticillium dahliae. Additionally, strain PICF7 is able to promote the growth of barley and Arabidopsis thaliana, VOCs being involved in the growth of the latter species.
In this study, the antagonistic capacity of these endophytic bacteria against relevant phytopathogens (Verticillium spp., Rhizoctonia solani, Sclerotinia sclerotiorum and Fusarium oxysporum f.sp. lycopersici) was assessed. Under in vitro conditions, PICF6 and PICF7 were only able to antagonize representative isolates of V. dahliae and V. longisporum. Remarkably, both strains produced an impressive portfolio of up to twenty VOCs, that included compounds with reported antifungal (e.g., 1-undecene, (methyldisulfanyl) methane and 1-decene) or plant growth promoting (e.g., tridecane, 1-decene) activities. Moreover, their volatilomes differed strongly in the absence and presence of V. dahliae.
For example, when co incubated with the defoliating pathotype of V. dahliae, the antifungal compound 4-methyl-2,6-bis(2-methyl-2-propanyl)phenol was produced. Results suggest that volatiles emitted by these endophytes may differ in their modes of action, and that potential benefits for the host needs further investigation in planta.
Microbe-mediated enzymatic hydrolysis of organic matter entails the production of hydrolysate, the recovery of which may be more or less efficient. The selfish uptake mechanism, recently discovered, allows microbes to hydrolyze polysaccharides and take up large oligomers, which are then degraded in the periplasmic space. By minimizing the hydrolysate loss, selfish behaviour may be profitable for free-living cells dwelling in a patchy substrate landscape. However, selfish uptake seems to be tailored to algal-derived polysaccharides, abundant in organic particles, suggesting that particle-attached microbes may use this strategy. We tracked selfish polysaccharides uptake in surface microbial communities of the northeastern Mediterranean Sea, linking the occurrence of this processing mode with microbial lifestyle. Additionally, we set up fluorescently labelled polysaccharides incubations supplying phytodetritus to investigate a 'pioneer' scenario for particle-attached microbes. Under both conditions, selfish behaviour was almost exclusively carried out by particle-attached microbes, suggesting that this mechanism may represent an advantage in the race for particle exploitation. Our findings shed light on the selfish potential of particle-attached microbes, suggesting multifaceted foraging strategies exerted by particle colonizers.
Consumers are increasingly demanding higher quality and safety standards for the products they consume, and one of this is wheat flour, the basis of a wide variety of processed products. This major component in the diet of many communities can be contaminated by microorganisms before the grain harvest, or during the grain storage right before processing. These microorganisms include several fungal species, many of which produce mycotoxins, secondary metabolites that can cause severe acute and chronic disorders. Yet, we still know little about the overall composition of fungal communities associated with wheat flour. In this study, we contribute to fill this gap by characterizing the fungal microbiome of different types of wheat flour using culture-dependent and -independent techniques. Qualitatively, these approaches suggested similar results, highlighting the presence of several fungal taxa able to produce mycotoxins. In-vitro isolation of fungal species suggest a higher frequency of Penicillium, while metabarcoding suggest a higher abundance of Alternaria. This discrepancy might reside on the targeted portion of the community (alive vs. overall) or in the specific features of each technique. Thus, this study shows that commercial wheat flour hosts a wide fungal diversity with several taxa potentially representing concerns for consumers, aspects that need more attention throughout the food production chain.
The Brassica napus seed microbiota is cultivar-specific and transmitted via paternal breeding lines
(2022)
Seed microbiota influence germination and plant health and have the potential to improve crop performance, but the factors that determine their structure and functions are still not fully understood.
Here, we analysed the impact of plant-related and external factors on seed endophyte communities of 10 different oilseed rape (Brassica napus L.) cultivars from 26 field sites across Europe.
All seed lots harboured a high abundance and diversity of endophytes, which were dominated by six genera: Ralstonia, Serratia, Enterobacter, Pseudomonas, Pantoea, and Sphingomonas.
The cultivar was the main factor explaining the variations in bacterial diversity, abundance and composition. In addition, the latter was significantly influenced by diverse biotic and abiotic factors, for example host germination rates and disease resistance against Plasmodiophora brassicae.
A set of bacterial biomarkers was identified to discriminate between characteristics of the seeds, for example Sphingomonas for improved germination and Brevundimonas for disease resistance.
Application of a Bayesian community approach suggested vertical transmission of seed endophytes, where the paternal parent plays a major role and might even determine the germination performance of the offspring.
This study contributes to the understanding of seed microbiome assembly and underlines the potential of the microbiome to be implemented in crop breeding and biocontrol programmes.
Urokinase-type plasminogen activator is widely discussed as a marker for cancer prognosis and diagnosis and as a target for cancer therapies. Together with its receptor, uPA plays an important role in tumorigenesis, tumor progression and metastasis. In the present study, systematic evolution of ligands by exponential enrichment (SELEX) was used to select single-stranded DNA aptamers targeting different forms of human uPA. Selected aptamers allowed the distinction between HMW-uPA and LMW-uPA, and therefore, presumably, have different binding regions. Here, uPAapt-02-FR showed highly affine binding with a K-D of 0.7 nM for HMW-uPA and 21 nM for LMW-uPA and was also able to bind to pro-uPA with a K-D of 14 nM. Furthermore, no cross-reactivity to mouse uPA or tissue-type plasminogen activator (tPA) was measured, demonstrating high specificity. Suppression of the catalytic activity of uPA and inhibition of uPAR-binding could be demonstrated through binding with different aptamers and several of their truncated variants. Since RNA aptamers are already known to inhibit uPA-uPAR binding and other pathological functions of the uPA system, these aptamers represent a novel, promising tool not only for detection of uPA but also for interfering with the pathological functions of the uPA system by additionally inhibiting uPA activity.
Biodegradation of polyester polyurethane by the marine fungus Cladosporium halotolerans 6UPA1
(2022)
Lack of degradability and the accumulation of polymeric wastes increase the risk for the health of the environment. Recently, recycling of polymeric waste materials becomes increasingly important as raw materials for polymer synthesis are in short supply due to the rise in price and supply chain disruptions. As an important polymer, polyurethane (PU) is widely used in modern life, therefore, PU biodegradation is desirable to avoid its accumulation in the environment. In this study, we isolated a fungal strain Cladosporium halotolerans from the deep sea which can grow in mineral medium with a polyester PU (Impranil DLN) as a sole carbon source. Further, we demonstrate that it can degrade up to 80% of Impranil PU after 3 days of incubation at 28 celcius by breaking the carbonyl groups (1732 cm(-1)) and C-N-H bonds (1532 cm(-1) and 1247 cm(-1)) as confirmed by Fourier-transform infrared (FTIR) spectroscopy analysis. Gas chromatography-mass spectrometry (GC-MS) analysis revealed polyols and alkanes as PU degradation intermediates, indicating the hydrolysis of ester and urethane bonds. Esterase and urease activities were detected in 7 days-old cultures with PU as a carbon source. Transcriptome analysis showed a number of extracellular protein genes coding for enzymes such as cutinase, lipase, peroxidase and hydrophobic surface binding proteins A (HsbA) were expressed when cultivated on Impranil PU. The yeast two-hybrid assay revealed that the hydrophobic surface binding protein ChHsbA1 directly interacts with inducible esterases, ChLip1 (lipase) and ChCut1 (cutinase). Further, the KEGG pathway for "fatty acid degradation " was significantly enriched in Impranil PU inducible genes, indicating that the fungus may use the degradation intermediates to generate energy via this pathway. Taken together, our data indicates secretion of both esterase and hydrophobic surface binding proteins by C. halotolerans plays an important role in Impranil PU absorption and subsequent degradation. Our study provides a mechanistic insight into Impranil PU biodegradation by deep sea fungi and provides the basis for future development of biotechnological PU recycling.
As a critical part of plant immunity, cells that are attacked by pathogens undergo rapid transcriptional reprogramming to minimize virulence. Many bacterial phytopathogens use type III effector (T3E) proteins to interfere with plant defense responses, including this transcriptional reprogramming. Here, we show that Xanthomonas outer protein S (XopS), a T3E of Xanthomonas campestris pv. vesicatoria (Xcv), interacts with and inhibits proteasomal degradation of WRKY40, a transcriptional regulator of defense gene expression. Virus-induced gene silencing of WRKY40 in pepper (Capsicum annuum) enhanced plant tolerance to Xcv infection, indicating that WRKY40 represses immunity. Stabilization of WRKY40 by XopS reduces the expression of its targets, which include salicylic acid-responsive genes and the jasmonic acid signaling repressor JAZ8. Xcv bacteria lacking XopS display significantly reduced virulence when surface inoculated onto susceptible pepper leaves. XopS delivery by Xcv, as well as ectopic expression of XopS in Arabidopsis thaliana or Nicotiana benthamiana, prevented stomatal closure in response to bacteria and biotic elicitors. Silencing WRKY40 in pepper or N. benthamiana abolished XopS's ability to prevent stomatal closure. This suggests that XopS interferes with both preinvasion and apoplastic defense by manipulating WRKY40 stability and downstream gene expression, eventually altering phytohormone crosstalk to promote pathogen proliferation.
Even though the effects of insect pests on global agricultural productivity are well recognised, little is known about movement and dispersal of many species, especially in the context of global warming. This work evaluates how temperature and light conditions affect different movement metrics and the feeding rate of the large lupine beetle, an agricultural pest responsible for widespread damage in leguminous crops. By using video recordings, the movement of 384 beetles was digitally analysed under six different temperatures and light conditions in the laboratory. Bayesian linear mixed-effect models were used to analyse the data. Furthermore, the effects of temperature on the daily diffusion coefficient of beetles were estimated by using hidden Markov models and random walk simulations. Results of this work show that temperature, light conditions, and beetles' weight were the main factors affecting the flight probability, displacement, time being active and the speed of beetles. Significant variations were also observed in all evaluated metrics. On average, beetles exposed to light conditions and higher temperatures had higher mean speed and flight probability. However, beetles tended to stay more active at higher temperatures and less active at intermediate temperatures, around 20 degrees C. Therefore, both the diffusion coefficient and displacement of beetles were lower at intermediate temperatures. These results show that the movement behaviour and feeding rates of beetles can present different relationships in the function of temperature. It also shows that using a single diffusion coefficient for insects in spatially explicit models may lead to over- or underestimation of pest spread.
(1) Background:
Adaptive diversification of complex traits plays a pivotal role in the evolution of organismal diversity. In the freshwater snail genus Tylomelania, adaptive radiations were likely promoted by trophic specialization via diversification of their key foraging organ, the radula.
(2) Methods:
To investigate the molecular basis of radula diversification and its contribution to lineage divergence, we used tissue-specific transcriptomes of two sympatric Tylomelania sarasinorum ecomorphs.
(3) Results:
We show that ecomorphs are genetically divergent lineages with habitat-correlated abundances. Sequence divergence and the proportion of highly differentially expressed genes are significantly higher between radula transcriptomes compared to the mantle and foot. However, the same is not true when all differentially expressed genes or only non-synonymous SNPs are considered. Finally, putative homologs of some candidate genes for radula diversification (hh, arx, gbb) were also found to contribute to trophic specialization in cichlids and Darwin's finches.
(4) Conclusions:
Our results are in line with diversifying selection on the radula driving Tylomelania ecomorph divergence and indicate that some molecular pathways may be especially prone to adaptive diversification, even across phylogenetically distant animal groups.
Marine macroalgae are a key primary producer in coastal ecosystems, but are often overlooked in blue carbon inventories. Large quantities of macroalgal detritus deposit on beaches, but the fate of wrack carbon (C) is little understood. If most of the wrack carbon is respired back to CO2, there would be no net carbon sequestration. However, if most of the wrack carbon is converted to bicarbonate (alkalinity) or refractory DOC, wrack deposition would represent net carbon sequestration if at least part of the metabolic products (e.g., reduced Fe and S) are permanently removed (i.e., long-term burial) and the DOC is not remineralised. To investigate the release of macroalgal C via porewater and its potential to contribute to C sequestration (blue carbon), we monitored the degradation of Ecklonia radiata in flow-through mesocosms simulating tidal flushing on sandy beaches. Over 60 days, 81% of added E. radiata organic matter (OM) decomposed. Per 1 mol of detritus C, the degradation produced 0.48 +/- 0.34 mol C of dissolved organic carbon (DOC) (59%) and 0.25 +/- 0.07 mol C of dissolved inorganic carbon (DIC) (31%) in porewater, and a small amount of CO2 (0.3 +/- 0.0 mol C; ca. 3%) which was emitted to the atmosphere. A significant amount of carbonate alkalinity was found in porewater, equating to 33% (0.27 +/- 0.05 mol C) of the total degraded C. The degradation occurred in two phases. In the first phase (days 0-3), 27% of the OM degraded, releasing highly reactive DOC. In the second phase (days 4-60), the labile DOC was converted to DIC. The mechanisms underlying E. radiata degradation were sulphate reduction and ammonification. It is likely that the carbonate alkalinity was primarily produced through sulphate reduction. The formation of carbonate alkalinity and semi-labile or refractory DOC from beach wrack has the potential to play an overlooked role in coastal carbon cycling and contribute to marine carbon sequestration.
Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating N-15 isotope enrichment and identifying nitrogen (N)-containing metabolites which show enrichment patterns that are informative for flux estimation in future N-15-MFA studies of A. thaliana. The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph-theoretic structural analyses with large-scale metabolic networks.
Successful conservation efforts have led to recent increases of large mammals such as European bison Bison bonasus, moose Alces alces and grey wolf Canis lupus and their return to former habitats in central Europe.
While embraced by some, the recovery of these species is a controversial topic and holds potential for human-wildlife conflicts.
Involving the public has been suggested to be an effective method for monitoring wildlife and mitigating associated conflicts.
To assess two interrelated prerequisites for engaging people in Citizen Science (CS)-knowledge of returning species and respondents' readiness to participate in CS activities for monitoring and managing these species-we conducted a survey (questionnaire) in two wildlife parks located in different states of Germany.
Based on 472 complete questionnaires, we developed generalized linear models to understand how sociodemographic variables and exposure to the species affected visitors' knowledge of each species, and to investigate if sociodemographic variables and knowledge influenced the likelihood of visitors to participate in CS activities.
Almost all visitors were aware of the returning wolf population, while knowledge and awareness about bison and moose were significantly lower.
Knowledge of the two herbivores differed geographically (higher knowledge of moose in the north-eastern state), possibly indicating a positive association between exposure to the species and knowledge.
However, models generally performed poorly in predicting knowledge about wildlife, suggesting that such specific knowledge is insufficiently explained by sociodemographic variables. Our model, which explained stated willingness in CS indicated that younger participants and those with higher knowledge scores in the survey were more willing to engage in CS activities.
Overall, our analyses highlight how exposure to large mammals, knowledge about wildlife and human demographics are interrelated-insights that are helpful for effectively recruiting citizen scientists for wildlife conservation.
Read the free Plain Language Summary for this article on the Journal blog.
Supergenes are nonrecombining genomic regions ensuring the coinheritance of multiple, coadapted genes. Despite the importance of supergenes in adaptation, little is known on how they originate. A classic example of supergene is the S locus controlling heterostyly, a floral heteromorphism occurring in 28 angiosperm families. In Primula, heterostyly is characterized by the cooccurrence of two complementary, self-incompatible floral morphs and is controlled by five genes clustered in the hemizygous, ca. 300-kb S locus. Here, we present the first chromosome-scale genome assembly of any heterostylous species, that of Primula veris (cowslip). By leveraging the high contiguity of the P. veris assembly and comparative genomic analyses, we demonstrated that the S-locus evolved via multiple, asynchronous gene duplications and independent gene translocations. Furthermore, we discovered a new whole-genome duplication in Ericales that is specific to the Primula lineage. We also propose a mechanism for the origin of S-locus hemizygosity via nonhomologous recombination involving the newly discovered two pairs of CFB genes flanking the S locus. Finally, we detected only weak signatures of degeneration in the S locus, as predicted for hemizygous supergenes. The present study provides a useful resource for future research addressing key questions on the evolution of supergenes in general and the S locus in particular: How do supergenes arise? What is the role of genome architecture in the evolution of complex adaptations? Is the molecular architecture of heterostyly supergenes across angiosperms similar to that of Primula?
Ancient genome provides insights into the history of Eurasian lynx in Iberia and Western Europe
(2022)
The Eurasian lynx (Lynx lynx) is one of the most widely distributed felids in the world. However, most of its populations started to decline a few millennia ago. Historical declines have been especially severe in Europe, and particularly in Western Europe, from where the species disappeared in the last few centuries. Here, we analyze the genome of an Eurasian lynx inhabiting the Iberian Peninsula 2500 ya, to gain insights into the phylogeographic position and genetic status of this extinct population. Also, we contextualize previous ancient data in the light of new phylogeographic studies of the species. Our results suggest that the Iberian population is part of an extinct European lineage closely related to the current Carpathian-Baltic lineages. Also, this sample holds the lowest diversity reported for the species so far, and similar to that of the highly endangered Iberian lynx. A combination of historical factors, such as a founder effect while colonizing the peninsula, together with intensified human impacts during the Holocene in the Cantabrian strip, could have led to a genetic impoverishment of the population and precipitated its extinction. Mitogenomic lineages distribution in space and time support the long-term coexistence of several lineages of Eurasian lynx in Western Europe with fluctuating ranges. While mitochondrial sequences related to the lineages currently found in Balkans and Caucasus were predominant during the Pleistocene, those more closely related to the lineage currently distributed in Central Europe prevailed during the Holocene. The use of ancient genomics has proven to be a useful tool to understand the biogeographic pattern of the Eurasian lynx in the past.
Many animals form aggregations with individuals of the same species (single-species aggregations, SSA). Less frequently, individuals may also aggregate with individuals of other species (mixed-species aggregations, MSA). Although the benefits and costs of SSA have been intensively studied, the same is not true for MSA. Here, we first review the cases of MSA in harvestmen, an arachnid order in which the records of MSA are more frequent than other arthropod orders. We then propose several benefits and costs of MSA in harvestmen, and contrast them with those of SSA. Second, using field-gathered data we describe gregariousness in seven species of Prionostemma harvestmen from Costa Rica. These species form MSA, but individuals are also found solitarily or in SSA. We tested one possible benefit and one possible cost of gregariousness in Prionostemma harvestmen. Regarding the benefit, we hypothesized that individuals missing legs would be more exposed to predation than eight-legged individuals and thus they should be found preferentially in aggregations, where they would be more protected from predators. Our data, however, do not support this hypothesis. Regarding the cost, we hypothesized that gregariousness increases the chances of parasitism. We found no support for this hypothesis either because both mite prevalence and infestation intensity did not differ between solitary or aggregated individuals. Additionally, the type of aggregation (SSA or MSA) was not associated with the benefit or the cost we explored. This lack of effect may be explained by the fluid membership of the aggregations, as we found high turnover over time in the number of individuals and species composition of the aggregations. In conclusion, we hope our review and empirical data stimulate further studies on MSA, which remains one of the most elusive forms of group living in animals.
Deciphering chemical mediators regulating specialized metabolism in a symbiotic cyanobacterium
(2022)
Genomes of cyanobacteria feature a variety of cryptic biosynthetic pathways for complex natural products, but the peculiarities limiting the discovery and exploitation of the metabolic dark matter are not well understood. Here we describe the discovery of two cell density-dependent chemical mediators, nostoclide and nostovalerolactone, in the symbiotic model strain Nostoc punctiforme, and demonstrate their pronounced impact on the regulation of specialized metabolism. Through transcriptional, bioinformatic and labeling studies we assigned two adjacent biosynthetic gene clusters to the biosynthesis of the two polyketide mediators. Our findings provide insight into the orchestration of specialized metabolite production and give lessons for the genomic mining and high-titer production of cyanobacterial bioactive compounds.
We present a chronology framework named LegacyAge 1.0 containing harmonized chronologies for 2831 pollen records (downloaded from the Neotoma Paleoecology Database and the supplementary Asian datasets) together with their age control points and metadata in machine-readable data formats.
All chronologies use the Bayesian framework implemented in Bacon version 2.5.3. Optimal parameter settings of priors (accumulation.shape, memory.strength, memory.mean, accumulation.rate, and thickness) were identified based on information in the original publication or iteratively after preliminary model inspection.
The most common control points for the chronologies are radiocarbon dates (86.1 %), calibrated by the latest calibration curves (IntCal20 and SHCal20 for the terrestrial radiocarbon dates in the Northern Hemisphere and Southern Hemisphere and Marine20 for marine materials).
The original publications were consulted when dealing with outliers and inconsistencies. Several major challenges when setting up the chronologies included the waterline issue (18.8% of records), reservoir effect (4.9 %), and sediment deposition discontinuity (4.4 %).
Finally, we numerically compare the LegacyAge 1.0 chronologies to those published in the original publications and show that the reliability of the chronologies of 95.4% of records could be improved according to our assessment.
Our chronology framework and revised chronologies provide the opportunity to make use of the ages and age uncertainties in synthesis studies of, for example, pollen-based vegetation and climate change.
The LegacyAge 1.0 dataset, including metadata, datings, harmonized chronologies, and R code used, is openaccess and available at PANGAEA (https://doi.org/10.1594/PANGAEA.933132; Li et al., 2021) and Zenodo (https://doi.org/10.5281/zenodo.5815192; Li et al., 2022), respectively.
Changing climatic conditions and unsustainable land use are major threats to savannas worldwide. Historically, many African savannas were used intensively for livestock grazing, which contributed to widespread patterns of bush encroachment across savanna systems. To reverse bush encroachment, it has been proposed to change the cattle-dominated land use to one dominated by comparatively specialized browsers and usually native herbivores. However, the consequences for ecosystem properties and processes remain largely unclear. We used the ecohydrological, spatially explicit model EcoHyD to assess the impacts of two contrasting, herbivore land-use strategies on a Namibian savanna: grazer- versus browser-dominated herbivore communities. We varied the densities of grazers and browsers and determined the resulting composition and diversity of the plant community, total vegetation cover, soil moisture, and water use by plants. Our results showed that plant types that are less palatable to herbivores were best adapted to grazing or browsing animals in all simulated densities. Also, plant types that had a competitive advantage under limited water availability were among the dominant ones irrespective of land-use scenario. Overall, the results were in line with our expectations: under high grazer densities, we found heavy bush encroachment and the loss of the perennial grass matrix. Importantly, regardless of the density of browsers, grass cover and plant functional diversity were significantly higher in browsing scenarios. Browsing herbivores increased grass cover, and the higher total cover in turn improved water uptake by plants overall. We concluded that, in contrast to grazing-dominated land-use strategies, land-use strategies dominated by browsing herbivores, even at high herbivore densities, sustain diverse vegetation communities with high cover of perennial grasses, resulting in lower erosion risk and bolstering ecosystem services.
Forest microclimate can buffer biotic responses to summer heat waves, which are expected to become more extreme under climate warming. Prediction of forest microclimate is limited because meteorological observation standards seldom include situations inside forests.
We use eXtreme Gradient Boosting - a Machine Learning technique - to predict the microclimate of forest sites in Brandenburg, Germany, using seasonal data comprising weather features.
The analysis was amended by applying a SHapley Additive explanation to show the interaction effect of variables and individualised feature attributions.
We evaluate model performance in comparison to artificial neural networks, random forest, support vector machine, and multi-linear regression.
After implementing a feature selection, an ensemble approach was applied to combine individual models for each forest and improve robustness over a given single prediction model.
The resulting model can be applied to translate climate change scenarios into temperatures inside forests to assess temperature-related ecosystem services provided by forests.
Nocardioides alcanivorans sp. nov., a novel hexadecane-degrading species isolated from plastic waste
(2022)
Strain NGK65(T), a novel hexadecane degrading, non-motile, Gram-positive, rod-to-coccus shaped, aerobic bacterium, was isolated from plastic polluted soil sampled at a landfill.
Strain NGK65(T) hydrolysed casein, gelatin, urea and was catalase-positive. It optimally grew at 28 degrees C. in 0-1% NaCl and at pH 7.5-8.0. Glycerol, D-glucose, arbutin, aesculin, salicin, potassium 5-ketogluconate. sucrose, acetate, pyruvate and hexadecane were used as sole carbon sources.
The predominant membrane fatty acids were iso-C-16:0 followed by iso-C(17:)0 and C-18:1 omega 9c. The major polar lipids were phosphatidylglycerol, phosphatidylethanolamine, phosphatidylinositol and hydroxyphosphatidylinositol.
The cell-wall peptidoglycan type was A3 gamma, with LL-diaminopimelic acid and glycine as the diagnostic amino acids. MK 8 (H-4) was the predominant menaquinone. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain NGK65(T) belongs to the genus Nocardioides (phylum Actinobacteria). appearing most closely related to Nocardioides daejeonensis MJ31(T) (98.6%) and Nocardioides dubius KSL-104(T) (98.3%).
The genomic DNA G+C content of strain NGK65(T) was 68.2%.
Strain NGK65(T) and the type strains of species involved in the analysis had average nucleotide identity values of 78.3-71.9% as well as digital DNA-DNA hybridization values between 22.5 and 19.7%, which clearly indicated that the isolate represents a novel species within the genus Nocardioides.
Based on phenotypic and molecular characterization, strain NGK65(T) can clearly be differentiated from its phylogenetic neighbours to establish a novel species, for which the name Nocardioides alcanivorans sp. nov. is proposed.
The type strain is NGK65(T) (=DSM 113112(T)=NCCB 100846(T)).
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.
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.
Biological carbon dioxide (CO2) reduction is an important step by which organisms form valuable energy-richer molecules required for further metabolic processes. The Mo-dependent formate dehydrogenase (FDH) from Rhodobacter capsulatus catalyzes reversible formate oxidation to CO2 at a bis-molybdopterin guanine dinucleotide (bis-MGD) cofactor. To elucidate potential substrate binding sites relevant for the mechanism, we studied herein the interaction with the inhibitory molecules azide and cyanate, which are isoelectronic to CO2 and charged as formate. We employed infrared (IR) spectroscopy in combination with density functional theory (DFT) and inhibition kinetics. One distinct inhibitory molecule was found to bind to either a non-competitive or a competitive binding site in the secondary coordination sphere of the active site. Site-directed mutagenesis of key amino acid residues in the vicinity of the bis-MGD cofactor revealed changes in both non-competitive and competitive binding, whereby the inhibitor is in case of the latter interaction presumably bound between the cofactor and the adjacent Arg587.
Review exploring the regulation of PHYTOCHROME-INTERACTING FACTORS by light, their role in abiotic stress tolerance and plant architecture, and their influence on crop productivity.
Light is a key determinant for plant growth, development, and ultimately yield. Phytochromes, red/far-red photoreceptors, play an important role in plant architecture, stress tolerance, and productivity. In the model plant Arabidopsis, it has been shown that PHYTOCHROME-INTERACTING FACTORS (PIFs; bHLH transcription factors) act as central hubs in the integration of external stimuli to regulate plant development. Recent studies have unveiled the importance of PIFs in crops. They are involved in the modulation of plant architecture and productivity through the regulation of cell division and elongation in response to different environmental cues. These studies show that different PIFs have overlapping but also distinct functions in the regulation of plant growth. Therefore, understanding the molecular mechanisms by which PIFs regulate plant development is crucial to improve crop productivity under both optimal and adverse environmental conditions. In this review, we discuss current knowledge of PIFs acting as integrators of light and other signals in different crops, with particular focus on the role of PIFs in responding to different environmental conditions and how this can be used to improve crop productivity.
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.
Dielectrophoresis (DEP) is an AC electrokinetic effect mainly used to manipulate cells. Smaller particles, like virions, antibodies, enzymes, and even dye molecules can be immobilized by DEP as well. In principle, it was shown that enzymes are active after immobilization by DEP, but no quantification of the retained activity was reported so far. In this study, the activity of the enzyme horseradish peroxidase (HRP) is quantified after immobilization by DEP. For this, HRP is immobilized on regular arrays of titanium nitride ring electrodes of 500 nm diameter and 20 nm widths. The activity of HRP on the electrode chip is measured with a limit of detection of 60 fg HRP by observing the enzymatic turnover of Amplex Red and H2O2 to fluorescent resorufin by fluorescence microscopy. The initial activity of the permanently immobilized HRP equals up to 45% of the activity that can be expected for an ideal monolayer of HRP molecules on all electrodes of the array. Localization of the immobilizate on the electrodes is accomplished by staining with the fluorescent product of the enzyme reaction. The high residual activity of enzymes after AC field induced immobilization shows the method's suitability for biosensing and research applications.
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.
Background
Long-term selection experiments are a powerful tool to understand the genetic background of complex traits. The longest of such experiments has been conducted in the Research Institute for Farm Animal Biology (FBN), generating extreme mouse lines with increased fertility, body mass, protein mass and endurance. For >140 generations, these lines have been maintained alongside an unselected control line, representing a valuable resource for understanding the genetic basis of polygenic traits. However, their history and genomes have not been reported in a comprehensive manner yet. Therefore, the aim of this study is to provide a summary of the breeding history and phenotypic traits of these lines along with their genomic characteristics. We further attempt to decipher the effects of the observed line-specific patterns of genetic variation on each of the selected traits.
Results
Over the course of >140 generations, selection on the control line has given rise to two extremely fertile lines (>20 pups per litter each), two giant growth lines (one lean, one obese) and one long-distance running line. Whole genome sequencing analysis on 25 animals per line revealed line-specific patterns of genetic variation among lines, as well as high levels of homozygosity within lines. This high degree of distinctiveness results from the combined effects of long-term continuous selection, genetic drift, population bottleneck and isolation. Detection of line-specific patterns of genetic differentiation and structural variation revealed multiple candidate genes behind the improvement of the selected traits.
Conclusions
The genomes of the Dummerstorf trait-selected mouse lines display distinct patterns of genomic variation harbouring multiple trait-relevant genes. Low levels of within-line genetic diversity indicate that many of the beneficial alleles have arrived to fixation alongside with neutral alleles. This study represents the first step in deciphering the influence of selection and neutral evolutionary forces on the genomes of these extreme mouse lines and depicts the genetic complexity underlying polygenic traits.
Polymeric antimicrobial peptide mimics are a promising alternative for the future management of the daunting problems associated with antimicrobial resistance. However, the development of successful antimicrobial polymers (APs) requires careful control of factors such as amphiphilic balance, molecular weight, dispersity, sequence, and architecture. While most of the earlier developed APs focus on random linear copolymers, the development of APs with advanced architectures proves to be more potent. It is recently developed multivalent bottlebrush APs with improved antibacterial and hemocompatibility profiles, outperforming their linear counterparts. Understanding the rationale behind the outstanding biological activity of these newly developed antimicrobials is vital to further improving their performance. This work investigates the physicochemical properties governing the differences in activity between linear and bottlebrush architectures using various spectroscopic and microscopic techniques. Linear copolymers are more solvated, thermo-responsive, and possess facial amphiphilicity resulting in random aggregations when interacting with liposomes mimicking Escheria coli membranes. The bottlebrush copolymers adopt a more stable secondary conformation in aqueous solution in comparison to linear copolymers, conferring rapid and more specific binding mechanism to membranes. The advantageous physicochemical properties of the bottlebrush topology seem to be a determinant factor in the activity of these promising APs.