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RangeShifter 2.0
(2021)
Process-based models are becoming increasingly used tools for understanding how species are likely to respond to environmental changes and to potential management options. RangeShifter is one such modelling platform, which has been used to address a range of questions including identifying effective reintroduction strategies, understanding patterns of range expansion and assessing population viability of species across complex landscapes. Here we introduce a new version, RangeShifter 2.0, which incorporates important new functionality. It is now possible to simulate dynamics over user-specified, temporally changing landscapes. Additionally, we integrated a new genetic module, notably introducing an explicit genetic modelling architecture, which allows for simulation of neutral and adaptive genetic processes. Furthermore, emigration, transfer and settlement traits can now all evolve, allowing for sophisticated simulation of the evolution of dispersal. We illustrate the potential application of RangeShifter 2.0's new functionality by two examples. The first illustrates the range expansion of a virtual species across a dynamically changing UK landscape. The second demonstrates how the software can be used to explore the concept of evolving connectivity in response to land-use modification, by examining how movement rules come under selection over landscapes of different structure and composition. RangeShifter 2.0 is built using object-oriented C++ providing computationally efficient simulation of complex individual-based, eco-evolutionary models. The code has been redeveloped to enable use across operating systems, including on high performance computing clusters, and the Windows graphical user interface has been enhanced. RangeShifter 2.0 will facilitate the development of in-silico assessments of how species will respond to environmental changes and to potential management options for conserving or controlling them. By making the code available open source, we hope to inspire further collaborations and extensions by the ecological community.
Leishmaniasis is a vector-borne disease caused by protozoal Leishmania parasites. Previous studies have shown that endoperoxides (EP) can selectively kill Leishmania in host cells.
Therefore, we studied in this work a set of new anthracene-derived EP (AcEP) together with their non-endoperoxidic analogs in model systems of Leishmania tarentolae promastigotes (LtP) and J774 macrophages for their antileishmanial activity and selectivity.
The mechanism of effective compounds was explored by studying their reaction with iron (II) in chemical systems and in Leishmania. The correlation of structural parameters with activity demonstrated that in this compound set, active compounds had a LogP(OW) larger than 3.5 and a polar surface area smaller than 100 angstrom(2).
The most effective compounds (IC50 in LtP < 2 mu M) with the highest selectivity (SI > 30) were pyridyl-/tert-butyl-substituted AcEP.
Interestingly, also their analogs demonstrated activity and selectivity. In mechanistic studies, it was shown that EP were activated by iron in chemical systems and in LtP due to their EP group.
However, the molecular structure beyond the EP group significantly contributed to their differential mitochondrial inhibition in Leishmania.
The identified compound pairs are a good starting point for subsequent experiments in pathogenic Leishmania in vitro and in animal models.
Animal societies are structured of dominance hierarchy (DH). DH can be viewed as networks and analyzed by graph theory. We study the impact of state-dependent feedback (winner-loser effect) on the emergence of local dominance structures after pairwise contests between initially equal-ranking members (equal resource-holding-power, RHP) of small and large social groups. We simulated pairwise agonistic contests between individuals with and without a priori higher RHP by Monte-Carlo-method. Random pairwise contests between equal-ranking competitors result in random dominance structures (‘Null variant’) that are low in transitive triads and high in pass along triads; whereas state-dependent feedback (‘Winner-loser variant’) yields centralized ‘star’ structured DH that evolve from competitors with initially equal RHP and correspond to hierarchies that evolve from keystone individuals. Monte-Carlo simulated DH following state-dependent feedback show motif patterns very similar to those of a variety of natural DH, suggesting that state-dependent feedback plays a pivotal role in robust self-organizing phenomena that transcend the specifics of the individual. Self-organization based on state-dependent feedback leads to social structures that correspond to those resulting from pre-existing keystone individuals. As the efficiency of centralized social networks benefits both, the individual and the group, centralization of social networks appears to be an important evolutionary goal.
Small temporary wetlands, like kettle holes, provide many valuable ecosystem functions and serve as refuge habitats in otherwise monotonous agricultural landscapes. However, the mechanisms that maintain biodiversity in these habitats are still poorly understood. In this study, we investigate how three taxa (vascular plants, ground beetles and spiders) respond to small-scale flooding and disturbance gradients in kettle holes as well as kettle hole area. For this purpose, we determined total, hygrophilic and red list species richness for all taxa and activity density for arthropods along transects extending from the edge towards the center of kettle holes. Furthermore, we calculated the community-weighted mean body size for arthropods and seed mass for plants as surrogates for the ability to respond to disturbance. Our analyses revealed that in particular plants and ground beetles showed strong responses along the small-scale spatial gradient. Total plant species richness decreased towards the center, while hygrophilic plant species increased. In contrast, both total and hygrophilic species richness of ground beetles increased towards the center. Spiders showed similar responses as ground beetles, but less pronounced. We found no evidence that disturbance at the edge of kettle holes leads to smaller body sizes or seed masses. However, arthropods in adjacent arable fields (one meter from the kettle hole edge) were particularly small. Kettle hole area had only weak effects on plants, but not on arthropods. Our study indicates that differences in the depth at the drier edge and the moist, regularly flooded center have a large and taxon-dependent influence on the species composition. Therefore, small-scale heterogeneity seems to be an important predictor for the maintenance of species diversity.
Formate dehydrogenases catalyze the reversible oxidation of formate to carbon dioxide. These enzymes play an important role in CO2 reduction and serve as nicotinamide cofactor recycling enzymes. More recently, the CO2-reducing activity of formate dehydrogenases, especially metal-containing formate dehydrogenases, has been further explored for efficient atmospheric CO2 capture. Here, we investigate the nicotinamide binding site of formate dehydrogenase from Rhodobacter capsulatus for its specificity toward NAD+ vs. NADP+ reduction. Starting from the NAD+-specific wild-type RcFDH, key residues were exchanged to enable NADP+ binding on the basis of the NAD+-bound cryo-EM structure (PDB-ID: 6TG9). It has been observed that the lysine at position 157 (Lys157) in the β-subunit of the enzyme is essential for the binding of NAD+. RcFDH variants that had Glu259 exchanged for either a positively charged or uncharged amino acid had additional activity with NADP+. The FdsBL279R and FdsBK276A variants also showed activity with NADP+. Kinetic parameters for all the variants were determined and tested for activity in CO2 reduction. The variants were able to reduce CO2 using NADPH as an electron donor in a coupled assay with phosphite dehydrogenase (PTDH), which regenerates NADPH. This makes the enzyme suitable for applications where it can be coupled with other enzymes that use NADPH.
A minimal light-driven approach was established for studying enzymatic CO2 conversion spectroscopically. The system consists of a photosensitizer Eosin Y, EDTA as a sacrificial electron donor and substrate source, and formate dehydrogenase from Rhodobacter capsulatus (RcFDH) as a biocatalyst. This simplified three-component system provides a photo-triggered control for in situ characterization of the entire catalytic reaction. Direct reduction of RcFDH by the photosensitizer without additional electron carriers was confirmed via UV-Vis spectroscopy, while GC-MS and IR spectroscopy were used to follow photoinduced CO2 generation from EDTA and its subsequent enzymatic reduction, yielding the product formate. Photo-driven and in vitro, dye-based CO2 reduction was inhibited by azide under a mixed (competitive-non-competitive) inhibition mode. IR spectroscopy reveals displacement of the competitively-bound azide by CO2, reflecting an interaction of both with the active site cofactor. This work comprises a proof-of-concept for a new approach to employ light for regulating the reaction of formate dehydrogenases and other CO2 reductases.
Carl Bergmann was an astute naturalist and physiologist. His ideas about animal size and shape were important advances in the pre-Darwinian nineteenth century. Bergmann's rule claims that that in cold climates, large body mass increases the ratio of volume-to-surface area and provides for maximum metabolic heat retention in mammals and birds. Conversely, in warmer temperatures, smaller body mass increases surface area relative to volume and allows for greater heat loss. For humans, we now know that body size and shape are regulated more by social-economic-political-emotional (SEPE) factors as well as nutrition-infection interactions. Temperature has virtually no effect. Bergmann's rule is a "just-so" story and should be relegated to teaching and scholarship about the history of science. That "rule" is no longer acceptable science and has nothing to tell us about physiological anthropology.
Since the first reported case of COVID-19 in 2019 in China and the official declaration from the World Health Organization in March 2021 as a pandemic, fast and accurate diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has played a major role worldwide. For this reason, various methods have been developed, comprising reverse transcriptase-polymerase chain reaction (RT-PCR), immunoassays, clustered regularly interspaced short palindromic repeats (CRISPR), reverse transcription loop-mediated isothermal amplification (RT-LAMP), and bio(mimetic)sensors. Among the developed methods, RT-PCR is so far the gold standard. Herein, we give an overview of the MIP-based sensors utilized since the beginning of the pandemic.
Strain NGK35T is a motile, Gram-stain-negative, rod-shaped (1.0-2.1 mu m long and 0.6-0.8 mu m wide), aerobic bacterium that was isolated from plastic-polluted landfill soil. The strain grew at temperatures between 6 and 37 degrees C (optimum, 28 degrees C), in 0-10 % NaCl (optimum, 1 %) and at pH 6.0-9.5 (optimum, pH 7.5-8.5).
It was positive for cytochrome c oxidase, catalase as well as H2S production, and hydrolysed casein and urea. It used a variety of different carbon sources including citrate, lactate and pyruvate.
The predominant membrane fatty acids were C-16:1 cis9 and C-16:0, followed by C-17:0 cyclo and C-18:1 cis11. The major polar lipids were phosphatidylglycerol and phosphatidylethanolamine, followed by diphosphatidyglycerol. The only quinone was ubiquinone Q-8. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain NGK35(T) belongs to the genus Paenalcaligenes (family Alcaligenaceae), appearing most closely related to Paenalcaligenes hominis CCUG 53761A(T) (96.90 %) and Paenalcaligenes suwonensis ABC02-12(T) (96.94 %).
The genomic DNA G+C content of strain NGK35(T) was 52.1 mol%. Genome-based calculations (genome-to-genome distance, average nucleotide identity and DNA G+C content) clearly indicated that the isolate represents a novel species within the genus Paenalcaligenes.
Based on phenotypic and molecular characterization, strain NGK35(T) can clearly be differentiated from its phylogenetic neighbours establishing a novel species, for which the name Paenalcaligenes niemegkensis sp. nov. is proposed.
The type strain is NGK35T (=DSM 113270(T)=NCCB 100854(T)).
Background:
Polycystic ovary syndrome (PCOS) is an endocrine disease in which related to obesity, metabolic disorders and is considered as one of the main causes of infertility in women. This trial was investigated the effects of green cardamom on the expression of genes implicated in obesity and diabetes among obese women with PCOS.
Methods:
One hundred ninety-four PCOS women were randomly divided two groups: intervention (n = 99; 3 g/day green cardamom) and control groups (n = 95). All of them were given low calorie diet. Anthropometric, glycemic and androgen hormones were assessed before and after 16-week intervention. The reverse transcription-polymerase chain reaction (RT-PCR) method was used to measure fat mass and obesity-associated (FTO), peroxisome proliferative activating receptor- (PPAR-), carnitine palmitoyltransferase 1A (CPT1A), acetyl-CoA carboxylase beta (ACAB), leptin receptor (LEPR), ghrelin, and lamin A/C (LAMIN) genes expression in each group.
Results:
Anthropometric indices were significantly decreased after intervention in both two studied groups. Glycemic indices and androgen hormones were significantly improved in the intervention group compared to the control group. The expression levels of FTO, CPT1A, LEPR, and LAMIN were significantly downregulated compared to control group (P < 0.001), as well as, PPAR-y was significantly upregulated in the intervention group after intervention with green cardamom compared to control group (P < 0.001).
Conclusion:
This current study showed that the administration of green cardamom is a beneficial approach for improving anthropometric, glycemic, and androgen hormones, as well as obesity and diabetes genes expression in PCOS women under the low-calorie diet.
Photosynthetic activity in both algae and cyanobacteria changes in response to cues of predation
(2022)
A plethora of adaptive responses to predation has been described in microscopic aquatic producers.
Although the energetic costs of these responses are expected, with their consequences going far beyond an individual, their underlying molecular and metabolic mechanisms are not fully known.
One, so far hardly considered, is if and how the photosynthetic efficiency of phytoplankton might change in response to the predation cues. Our main aim was to identify such responses in phytoplankton and to detect if they are taxon-specific.
We exposed seven algae and seven cyanobacteria species to the chemical cues of an efficient consumer, Daphnia magna, which was fed either a green alga, Acutodesmus obliquus, or a cyanobacterium, Synechococcus elongatus (kairomone and alarm cues), or was not fed (kairomone alone).
In most algal and cyanobacterial species studied, the quantum yield of photosystem II increased in response to predator fed cyanobacterium, whereas in most of these species the yield did not change in response to predator fed alga.
Also, cyanobacteria tended not to respond to a non-feeding predator. The modal qualitative responses of the electron transport rate were similar to those of the quantum yield.
To our best knowledge, the results presented here are the broadest scan of photosystem II responses in the predation context so far.
Forage supply of savanna grasslands plays a crucial role for local food security and consequently, a reliable monitoring system could help to better manage vital forage resources. To help installing such a monitoring system, we investigated whether in-situ hyperspectral data could be resampled to match the spectral resolution of multi- and hyperspectral satellites; if the type of sensor affected model transfer; and if spatio-temporal patterns of forage characteristics could be related to environmental drivers. We established models for forage quantity (green biomass) and five forage quality proxies (metabolisable energy, acid/neutral detergent fibre, ash, phosphorus). Hyperspectral resolution of the Hyperion satellite mostly resulted in higher accuracies (i.e. higher R-2, lower RMSE). When applied to satellite data, though, the greater quality of the multispectral Sentinel-2 satellite data leads to more realistic forage maps. By analysing a three-year time series, we found plant phenology and cumulated precipitation to be the most important environmental drivers of forage supply. We conclude that none of the investigated satellites provide optimal conditions for monitoring purposes. Future hyperspectral satellite missions like EnMAP, combining the high information level of Hyperion with the good data quality and resolution of Sentinel-2, will provide the prerequisites for installing a regular monitoring service.
Temperature is an important factor governing microbe-mediated carbon feedback from permafrost soils. The link between taxonomic and functional microbial responses to temperature change remains elusive due to the lack of studies assessing both aspects of microbial ecology. Our previous study reported microbial metabolic and trophic shifts in response to short-term temperature increases in Arctic peat soil, and linked these shifts to higher CH4 and CO2 production rates (Proceedings of the National Academy of Sciences of the United States of America, 112, E2507-E2516). Here, we studied the taxonomic composition and functional potential of samples from the same experiment. We see that along a high-resolution temperature gradient (1-30 degrees C), microbial communities change discretely, but not continuously or stochastically, in response to rising temperatures. The taxonomic variability may thus in part reflect the varied temperature responses of individual taxa and the competition between these taxa for resources. These taxonomic responses contrast the stable functional potential (metagenomic-based) across all temperatures or the previously observed metabolic or trophic shifts at key temperatures. Furthermore, with rising temperatures we observed a progressive decrease in species diversity (Shannon Index) and increased dispersion of greenhouse gas (GHG) production rates. We conclude that the taxonomic variation is decoupled from both the functional potential of the community and the previously observed temperature-dependent changes in microbial function. However, the reduced diversity at higher temperatures might help explain the higher variability in GHG production at higher temperatures.
Trade-offs between traits are present across different levels of biological systems and ultimately reflect constraints imposed by physicochemical laws and the structure of underlying biochemical networks. Yet, mechanistic explanation of how trade-offs between molecular traits arise and how they relate to optimization of fitness-related traits remains elusive. Here, we introduce the concept of relative flux trade-offs and propose a constraint-based approach, termed FluTOr, to identify metabolic reactions whose fluxes are in relative trade-off with respect to an optimized fitness-related cellular task, like growth. We then employed FluTOr to identify relative flux trade-offs in the genome-scale metabolic networks of Escherichia coli, Saccharomyces cerevisiae, and Arabidopsis thaliana. For the metabolic models of E. coli and S. cerevisiae we showed that: (i) the identified relative flux trade-offs depend on the carbon source used and that (ii) reactions that participated in relative trade-offs in both species were implicated in cofactor biosynthesis. In contrast to the two microorganisms, the relative flux trade-offs for the metabolic model of A. thaliana did not depend on the available nitrogen sources, reflecting the differences in the underlying metabolic network as well as the considered environments. Lastly, the established connection between relative flux trade-offs allowed us to identify overexpression targets that can be used to optimize fitness-related traits. Altogether, our computational approach and findings demonstrate how relative flux trade-offs can shape optimization of metabolic tasks, important in biotechnological applications.
Microbiomes have an immense potential to enhance plant resilience to various biotic and abiotic stresses. However, intrinsic microbial communities respond to changes in their host's physiology and environment during plant's life cycle. The potential of the inherent plant microbiome has been neglected for a long time, especially for the postharvest period. Currently, close to 50% of all produced fruits and vegetables are lost either during production or storage. Biological control of spoilage and storage diseases is still lacking sufficiency. Today, novel multiomics technologies allow us to study the microbiome and its responses on a community level, which will help to advance current classic approaches and develop more effective and robust microbiome-based solutions for fruit and vegetable storability, quality, and safety.
Otter shrew mitogenomes (Afrotheria, Potamogalidae) reconstructed from historical museum skins
(2022)
African otter shrews (Potamogalidae) are Afrotherian mammals adapted to a semi-aquatic lifestyle. Given their rareness, genetic data on otter shrews are limited. By applying laboratory methods tuned for the recovery of archival DNA and an iterative mapping approach, we reconstructed whole mitochondrial genomes of the Giant (Potamogale velox) and Ruwenzori pygmy otter shrew (Micropotamogale ruwenzorii) from historical museum skins. Phylogenetic analyses are consistent with previous reports in recovering a sister relationship between African otter shrews and Malagasy tenrecs. The long branches separating both lineages, however, support their recognition as separate families.
Critical role of parasite-mediated energy pathway on community response to nutrient enrichment
(2022)
Parasites form an integral part of food webs, however, they are often ignored in classic food web theory or limited to the investigation of trophic transmission pathways. Specifically, direct consumption of parasites by nonhost predators is rarely considered, while it can contribute substantially to energy flow in food webs. In aquatic systems, chytrids constitute a major group of fungal parasites whose free-living infective stages (zoospores) form a highly nutritional food source to zooplankton. Thereby, the consumption of zoospores can create an energy pathway from otherwise inedible phytoplankton to zooplankton ( "mycoloop "). This parasite-mediated energy pathway might be of special importance during phytoplankton blooms dominated by inedible or toxic primary producers like cyanobacteria, which are on the rise with eutrophication and global warming. We theoretically investigated community dynamics and energy transfer in a food web consisting of an edible nonhost and an inedible host phytoplankton species, a parasitic fungus, and a zooplankton species grazing on edible phytoplankton and fungi. Food web dynamics were investigated along a nutrient gradient contrasting nonadaptive zooplankton species representative for filter feeders like cladocerans and zooplankton with the ability to actively adapt their feeding preferences like many copepod species. Overall, the importance of the mycoloop for zooplankton increases with nutrient availability. This increase is smooth for nonadaptive consumers. For adaptive consumers, we observe an abrupt shift from an almost exclusive preference for edible phytoplankton at low nutrient levels to a strong preference for parasitic fungi at high nutrient levels. The model predicts that parasitic fungi could contribute up to 50% of the zooplankton diet in nutrient-rich environments, which agrees with empirical observations on zooplankton gut content from eutrophic systems during blooms of inedible diatoms or cyanobacteria. Our findings highlight the role of parasite-mediated energy pathways for predictions of energy flow and community composition under current and future environmental change.
Multi-species biofilms are more resistant against stress compared to single-species biofilms. However, the mechanisms underlying this common observation remain elusive. Therefore, we studied biofilm formation of well-known opportunistic pathogens (Acinetobacter baumanii, Enterococcus faecium, Escherichia coli, Staphylococcus haemolyticus and Stenotrophomonas maltophilia) in various approaches. Synergistic effects in their multi species biofilms were observed. Using metatranscriptomics, changes in the gene expression of the involved members became evident, and provided explanations for the improved survivability under nutrient limitation and exposure to disinfectants. Genes encoding proteins for vitamin B6 synthesis and iron uptake were linked to synergism in the multi-species biofilm under nutrient-limited conditions. Our study indicates that sub-lethal concentrations of an alcohol-based disinfectant enhance biofilm yields in multi-species assemblages. A reduction of the dominant taxa in the multi-species biofilm under disinfectant pressure allowed minor taxa to bloom. The findings underline the importance of minor but antimicrobial-resistant species that serve as "protectors" for the whole assemblage due to upregulation of genes involved in defence mechanisms and biofilm formation. This ultimately results in an increase in the total yield of the multi-species biofilm. We conclude that inter-species interactions may be crucial for the survival of opportunistic pathogens; especially under conditions that are typically found under hospital settings.
Soil microbial communities are crucial for plant growth and are already depleted by anthropogenic activities.
The application of microbial transplants provides a strategy to restore beneficial soil traits, but less is known about the microbiota of traditional inoculants used in biodynamic agriculture.
In this study, we used amplicon sequencing and quantitative PCR to decipher microbial communities of composts, biodynamic manures, and plant preparations from Austria and France.
In addition, we investigated the effect of extracts derived from biodynamic manure and compost on the rhizosphere microbiome of apple trees. Microbiota abundance, composition, and diversity of biodynamic manures, plant preparations, and composts were distinct. Microbial abundances ranged between 1010-1011 (bacterial 16S rRNA genes) and 109-1011 (fungal ITS genes). The bacterial diversity was significantly higher in biodynamic manures compared to compost without discernible differences in abundance. Fungal diversity was not significantly different while abundance was increased in biodynamic manures. The microbial communities of biodynamic manures and plant preparations were specific for each production site, but all contain potentially plant-beneficial bacterial genera.
When applied in apple orchards, biodynamic preparations (extracts) had the non-significant effect of reducing bacterial and fungal abundance in apple rhizosphere (4 months post-application), while increasing fungal and lowering bacterial Shannon diversity.
One to four months after inoculation, individual taxa indicated differential abundance. We observed the reduction of the pathogenic fungus Alternaria, and the enrichment of potentially beneficial bacterial genera such as Pseudomonas.
Our study paves way for the science-based adaptation of empirically developed biodynamic formulations under different farming practices to restore the vitality of agricultural soils.
Understanding the assembly mechanism and function of membrane proteins is a fundamental problem in biochemical research. Among the membrane proteins, G protein-coupled receptors (GPCRs) represent the largest class in the human body and have long been considered to function as monomers.
Nowadays, the oligomeric assembly of GPCRs is widely accepted, although the functional importance and therapeutic intervention remain largely unexplored. This is partly due to difficulties in the heterologous production of membrane proteins.
Cell-free protein synthesis (CFPS) with its endogenous endoplasmic reticulum-derived structures has proven as a technique to address this issue.
In this study, we investigate for the first time the conceptual CFPS of a heteromeric GPCR, the gamma-aminobutyric acid receptor type B (GABA(B)), from its protomers BR1 and BR2 using a eukaryotic cell-free lysate. Using a fluorescence-based proximity ligation assay, we provide evidence for colocalization and thus suggesting heterodimerization.
We prove the heterodimeric assembly by a bioluminescence resonance energy transfer saturation assay providing the manufacturability of a heterodimeric GPCR by CFPS. Additionally, we show the binding of a fluorescent orthosteric antagonist, demonstrating the feasibility of combining the CFPS of GPCRs with pharmacological applications.
These results provide a simple and powerful experimental platform for the synthesis of heteromeric GPCRs and open new perspectives for the modelling of protein-protein interactions.
Accordingly, the presented technology enables the targeting of protein assemblies as a new interface for pharmacological intervention in disease-relevant dimers.
Theoretical and empirical studies show increased diversity in crops, supply chains, and markets helps stabilize food systems. At the same time global commodity markets and industrial agriculture have driven homogenization of local and regional production systems, and consolidated power in fewer larger specialized farms and distributers. This is a global challenge, with no obvious global solutions. An important question therefore, is how individual countries can build their own resilience through maintaining or increasing diversity within their borders. Here we show, using farm level data from Germany, that spreading production risk by growing the same crops across different farms carries stabilizing benefits by allowing for increased spatiotemporal asynchrony within crops. We also find that increasing asynchrony between the year-to-year production of different crops has stabilizing effects on food supply. Importantly, the benefits of increasing crop diversity are lower in specialized landscapes growing the same crop on large patches. Our results illustrate clear benefits of diversified crops, producers, and agricultural landscapes to buffer supply side shocks, and for incorporation in subsidies and other regulatory measures aimed at stabilizing food systems.
Riverine ecosystems provide various ecosystem services. One of these services is the biological control of eutrophication by grazing macroinvertebrates.
However, riverine ecosystems are subject to numerous stressors that affect community structure, functions, and stability properties. To manage rivers in response to these stressors, a better understanding of the ecological functions underlying services is needed.
This requires consideration of local and regional processes, which requires a metacommunity approach that links local food webs through drift and dispersal. This takes into account long-distance interactions that can compensate for local effects of stressors.
Our modular model MASTIFF (Multiple Aquatic STressors In Flowing Food webs) is stage-structured, spatially explicit, and includes coupled food webs consisting of benthic resource-consumer interactions between biofilm and three competing macroinvertebrate functional types. River segments are unidirectionally connected through organismal drift and bidirectionally connected through dispersal. Climate and land use stressors along the river can be accounted for. Biocontrol of biofilm eutrophication is used as an exemplary functional indicator.
We present the model and the underlying considerations, and show in an exemplary application that explicit consideration of drift and dispersal is essential for understanding the spatiotemporal biocontrol of eutrophication.
The combination of drift and dispersal reduced eutrophication events. While dispersal events were linked to specific periods in the species life cycles and therefore had limited potential to control, drift was ubiquitous and thus responded more readily to changing habitat conditions.
This indicates that drift is an important factor for coping with stress situations.
Finally, we outline and discuss the potential and possibilities of MASTIFF as a tool for mechanistic, cross-scale analyses of multiple stressors to advance knowledge of riverine ecosystem functioning.
Paleogenomes reveal a complex evolutionary history of late Pleistocene bison in Northeastern China
(2022)
Steppe bison are a typical representative of the Mid-Late Pleistocene steppes of the northern hemisphere.
Despite the abundance of fossil remains, many questions related to their genetic diversity, population structure and dispersal route are still elusive.
Here, we present both near-complete and partial mitochondrial genomes, as well as a partial nuclear genome from fossil bison samples excavated from Late Pleistocene strata in northeastern China.
Maximum-likelihood and Bayesian trees both suggest the bison clade are divided into three maternal haplogroups (A, B and C), and Chinese individuals fall in two of them. Bayesian analysis shows that the split between haplogroup C and the ancestor of haplogroups A and B dates at 326 ky BP (95% HPD: 397-264 ky BP).
In addition, our nuclear phylogenomic tree also supports a basal position for the individual carrying haplogroup C. Admixture analyses suggest that CADG467 (haplogroup C) has a similar genetic structure to steppe bison from Siberia (haplogroup B).
Our new findings indicate that the genetic diversity of Pleistocene bison was probably even higher than previously thought and that northeastern Chinese populations of several mammalian species, including Pleistocene bison, were genetically distinct.
Plant cell walls are versatile materials that can adopt a wide range of mechanical properties through controlled deposition of cellulose fibrils. Wall integrity requires a sufficiently homogeneous fibril distribution to cope effectively with wall stresses. Additionally, specific conditions, such as the negative pressure in water transporting xylem vessels, may require more complex wall patterns, e.g., bands in protoxylem.
The orientation and patterning of cellulose fibrils are guided by dynamic cortical microtubules.
New microtubules are predominantly nucleated from parent microtubules causing positive feedback on local microtubule density with the potential to yield highly inhomogeneous patterns. Inhomogeneity indeed appears in all current cortical array simulations that include microtubule-based nucleation, suggesting that plant cells must possess an as-yet unknown balancing mechanism to prevent it.
Here, in a combined simulation and experimental approach, we show that a limited local recruitment of nucleation complexes to microtubules can counter the positive feedback, whereas local tubulin depletion cannot.
We observe that nucleation complexes preferentially appear at the plasma membrane near microtubules. By incorporating our experimental findings in stochastic simulations, we find that the spatial behavior of nucleation complexes delicately balances the positive feedback, such that differences in local microtubule dynamics-as in developing protoxylem-can quickly turn a homogeneous array into a banded one. Our results provide insight into how the plant cytoskeleton has evolved to meet diverse mechanical requirements and greatly increase the predictive power of computational cell biology studies.
During a survey of aquatic fungi from Anzali Lagoon in Iran, several fungal specimens were isolated from freshwater habitats. Morphological evidence and comparing sequencing based on rDNA (ITS and LSU) and protein-coding genes (TEF1 and TUB2) showed that some isolates belong to undescribed fungal species.
These isolates belong to Arthrobotrys and Sarocladium, two ascomycetes genera. Arthrobotrys hyrcanus, sp. nov., differs from closely related species such as A. dianchiensis by its larger conidia and septation of primary conidia. Sarocladium pseudokiliense, sp. nov., was similar to S. kiliense, but distinguished by its conidial shape and the absence of adelophialides and chlamydospores.
Morphological descriptions, illustrations and multilocus phylogenetic analysis for both new species are provided.
Meropenem is one of the most frequently used antibiotics to treat life-threatening infections in critically ill patients.
This study aimed to develop a meropenem dosing algorithm for the treatment of Gram-negative infections based on intensive care unit (ICU)-specific resistance data. Antimicrobial susceptibility testing of Gram-negative bacteria obtained from critically ill patients was carried out from 2016 to 2020 at a tertiary care hospital.
Based on the observed MIC distribution, stochastic simulations (n = 1,000) of an evaluated pharmacokinetic meropenem model, and a defined pharmacokinetic/pharmacodynamic target (100%T->4xMIC while minimum concentrations were <44.5 mg/L), dosing recommendations for patients with varying renal function were derived.
Pathogen-specific MIC distributions were used to calculate the cumulative fraction of response (CFR), and the overall MIC distribution was used to calculate the local pathogen-independent mean fraction of response (LPIFR) for the investigated dosing regimens.
A CFR/LPIFR of >90% was considered adequate. The observed MIC distribution significantly differed from the EUCAST database. Based on the 6,520 MIC values included, a three-level dosing algorithm was developed.
If the pathogen causing the infection is unknown (level 1), known (level 2), known to be neither Pseudomonas aeruginosa nor Acinetobacrer baumannii, or classified as susceptible (level 3), a continuous infusion of 1.5 g daily reached sufficient target attainment independent of renal function.
In all other cases, dosing needs to be adjusted based on renal function. ICU-specific susceptibility data should be assessed regularly and integrated into dosing decisions. The presented workflow may serve as a blueprint for other antimicrobial settings.
Quantifying the influence of pollen aging on the adhesive
properties of Hypochaeris radicata pollen
(2022)
Simple Summary Pollination is the transfer of pollen from a plant's male part (anther) to the corresponding female part (stigma). It is a fundamental biological process that ensures plant reproduction. Most studies investigate pollination from a biological perspective, but the underlying physical processes are poorly understood. Many plants rely on insects to transport pollen and the forces with which pollen adhere to insects and floral surfaces are fundamental for successful pollination.
We quantified pollen adhesion by measuring the forces necessary to detach Hypochaeris radicata (catsear, a common insect-pollinated plant) pollen from glass and studied for the first time how the adhesion forces change with pollen aging.
Our results show that newly formed adhesion bonds between H. radicata pollen and glass are stronger for fresh pollen than for old ones. On the other hand, when H. radicata pollen age in contact with glass, the adhesion between pollen and glass strengthens over time. These effects are probably caused by the viscous liquid covering most pollen (pollenkitt) changing its viscoelastic properties as it dries.
Although pollination is one of the most crucial biological processes that ensures plant reproduction, its mechanisms are poorly understood. Especially in insect-mediated pollination, a pollen undergoes several attachment and detachment cycles when being transferred from anther to insect and from insect to stigma. The influence of the properties of pollen, insect and floral surfaces on the adhesion forces that mediate pollen transfer have been poorly studied.
Here, we investigate the adhesive properties of Hypochaeris radicata pollen and their dependence on pollen aging by quantifying the pull-off forces from glass slides using centrifugation and atomic force microscopy. We found that the properties of the pollenkitt-the viscous, lipid liquid on the surface of most pollen grains-influences the forces necessary to detach a pollen from hydrophilic surfaces.
Our results show that aged H. radicata pollen form weaker adhesions to hydrophilic glass than fresh ones. On the other hand, when a pollen grain ages in contact with glass, the adhesion between the two surfaces increases over time.
This study shows for the first time the pollen aging effect on the pollination mechanism.
Volatile organic compounds (VOCs) are involved in microbial interspecies communication and in the mode of action of various antagonistic interactions. They are important for balancing host-microbe interactions and provide the basis for developing biological control strategies to control plant pathogens.
We studied the interactions between the bacterial antagonist Serratia plymuthica HRO-C48 and three fungal plant pathogens Rhizoctonia solani, Leptosphaeria maculans and Verticillium longisporum. Significant differences in fungal growth inhibition by the Serratia-emitted VOCs in pairwise dual culture assays and changes in the transcriptome of the bacterium and in the volatilomes of both interacting partners were observed. Even though the rate of fungal growth inhibition by Serratia was variable, the confrontation of the bacterium with the VOCs of all three fungi changed the levels of expression of the genes involved in stress response, biofilm formation, and the production of antimicrobial VOCs. Pairwise interacting microorganisms switched between defense (downregulation of gene expression) and attack (upregulation of gene expression and metabolism followed by growth inhibition of the interacting partner) modes, subject to the combinations of microorganisms that were interacting.
In the attack mode HRO-C48 significantly inhibited the growth of R. solani while simultaneously boosting its own metabolism; by contrast, its metabolism was downregulated when HRO-C48 went into a defense mode that was induced by the L. maculans and V. longisporum VOCs. L. maculans growth was slightly reduced by the one bacterial VOC methyl acetate that induced a strong downregulation of expression of genes involved in almost all metabolic functions in S. plymuthica.
Similarly, the interaction between S. plymuthica and V. longisporum resulted in an insignificant growth reduction of the fungus and repressed the rate of bacterial metabolism on the transcriptional level, accompanied by an intense volatile dialogue. Overall, our results indicate that VOCs substantially contribute to the highly break species-specific interactions between pathogens and their natural antagonists and thus deserving of increased consideration for pathogen control.
Ciliates represent a crucial link between phytoplankton and bacteria and mesozooplankton in pelagic food webs, but little is known about the processes influencing the dynamics of individual species.
Using long-term, high-frequency observations, we compared the diversity and the temporal variability in biomass and species composition of the ciliate community in large, deep, mesotrophic Lake Constance to that of the phytoplankton and rotifer communities in the same lake.
Furthermore, we used boosted regression trees to evaluate possible environmental predictors (temperature, three prey groups, four predator/competitor groups) influencing ciliate net growth.
The biomass of all ciliate species showed a common, recurrent seasonal pattern, often with peaks in spring and summer.
The ciliate community was more diverse than the rotifer community, exhibited highly synchronous dynamics and its species were regularly encountered during the season. The top-down control by copepods likely contributes to the ciliates' synchronized decline prior to the clear-water phase when food concentration is still high.
The high temporal autocorrelation of the ciliate biomasses together with the inter-annual recurrent seasonal patterns and the low explanatory power of the environmental predictors suggest that the dynamics of individual ciliate species are strictly controlled, yet it remains difficult to determine the responsible factors.
Current evidence suggests that migratory animals extract map information from the geomagnetic field for true navigation. The sensory basis underlying this feat is elusive, but presumably involves magnetic particles.
A common experimental manipulation procedure consists of pre-treating animals with a magnetic pulse, with the aim of re-magnetising particles to alter the internal representation of the external field prior to a navigation task.
Although pulsing provoked deflected bearings in caged songbirds, analogous studies with free-flying songbirds yielded inconsistent results.
Here, we pulsed European robins (Erithacus rubecula) at an offshore stopover site during spring migration and monitored their free-flight behaviour with a regional-scale network of radio-receiving stations.
We found no pulse effect on departure probability, nocturnal departure timing departure direction or consistency of flight direction.
This suggests either no use of the geomagnetic map by our birds, or that magnetic pulses do not affect the sensory system underlying geomagnetic map detection.
Carbohydrates play a vital role in all living organisms; serving as a cornerstone in primary metabolism through the release of energy from their hydrolysis and subsequent re-utilization (Apriyanto et al., 2022). Starch is the principal carbohydrate reserve in plants, providing essential energy for plant growth. Furthermore, starch serves as a significant carbohydrate source in the human diet. Beyond its nutritional value, starch has extensive industrial application associated with many aspects of human society, such as feed, pharmacy, textiles, and the production of biodegradable plastics. Understanding the mechanisms underlying starch metabolism in plants carries multifaceted benefits. Not only does it contribute to increasing crop yield and refining grain quality, but also can improve the efficiency of industrial applications.
Starch in plants is categorized into two classes based on their location and function: transitory starch and storage starch. Transitory starch is produced in chloroplasts of autotrophic tissues/organs, such as leaves. It is synthesized during the day and degraded during the night. Storage starch is synthesized in heterotrophic tissues/organs, such as endosperm, roots and tubers, which is utilized for plant reproduction and industrial application in human life. Most studies aiming to comprehend starch metabolism of Arabidopsis thaliana primarily focus on transitory starch.
Starch is stored as granular form in chloroplast and amyloplast. The parameters of starch granules, including size, morphology, and quantity per chloroplast serve as indicators of starch metabolism status. However, the understanding of their regulatory mechanism is still incomplete. In this research, I initially employed a simple and adapted method based on laser confocal scanning microscopy (LCSM) to observe size, morphology and quantity of starch granules within chloroplasts in Arabidopsis thaliana in vivo. This method facilitated a rapid and versatile analysis of starch granule parameters across numerous samples. Utilizing this approach, I compared starch granule number per chloroplast between mesophyll cells and guard cells in both wild type plants (Col-0) and several starch related mutants. The results revealed that the granule number is distinct between mesophyll cells and guard cells, even within the same genetic background, suggesting that guard cells operate a unique regulatory mechanism of starch granule number.
Subsequently, I redirected my attention toward examining starch morphology. Through microscopy analyses, I observed a gradual alteration in starch granule morphology in certain mutants during leaf aging. Specifically, in mutants such as sex1-8 and dpe2phs1ss4, there was a progressive alteration in starch granule morphology over time. Conversely, in Col-0 and ss4 mutant, these morphological alterations were not evident. This discovery suggests a new perspective to understand the development of starch morphology.
Further investigation revealed that mutants lacking either Disproportionating enzyme 2 (DPE2) or MALTOSE-EXCESS 1 (MEX1) exhibited gradual alterations in starch morphology with leaf aging. Notably, the most severe effects on starch morphology occurred in double mutants lacking either DPE2 or MEX1 in conjunction with a lack of starch synthase 4 (SS4). In these mutations, a transformation of the starch granule morphology from the typical discoid morphology to oval and eventually to a spherical shape.
To investigate the changes in the internal structure of starch during this alteration, I analyzed the chain length distribution (CLD) of the amylopectin of young, intermediate and old leaves of the mutants. Throughout starch granule development, I found an increased presence of short glucan chains within the granules, particularly evident in dpe2ss4 and mex1ss4 mutants, as well as their parental single mutants. Notably, the single mutant ss4 also showed an affected granule morphology, albeit not influenced by leaf aging..
The CLD pattern of the amylopectin reflects an integrative regulation involving several participants in starch synthesis, including starch synthases (SSs), starch branching/debranching enzymes (SBEs/DBEs). Therefore, I further detected the expression of related genes on transcription level and the enzymatic activity of their respective proteins. Results indicated altered gene expression of several regulators in these mutants, particularly demonstrating dramatic alterations in dpe2 and dpe2ss4 with leaf aging. These changes corresponded with the observed alterations in starch granule morphology.
Taken together, I have identified and characterized a progressive alteration in starch granule morphology primarily resulting from the deficiencies in DPE2 and MEX1. Furthermore, I have associated the CLD pattern with the granule morphogenesis, as well as the gene expression and enzymatic activity of proteins involved in starch synthesis. Unlike SS4, which is implicated in starch initiation, MEX1 and DPE2 are involved into starch degradation. MEX1 is located in chloroplast envelope and DPE2 is situated in the cytosol. Considering the locations and known functions of DPE2/MEX1 and SS4, I infer that there might be two pathways influencing starch morphology: an initiation-affected pathway via SS4 and a degradation-affected pathway via DPE2/MEX1.
Nature conservation is currently shaping many terrestrial ecosystems in Africa.
This is particularly evident in Sub-Saharan Africa (SSA), where conservation is intended to recover wildlife populations, with special focus on elephants.
Rising numbers of elephants induce woody biomass losses but increase soil organic carbon (SOC) stocks from decaying wood and dung.
We hypothesized that these increases under wildlife conservation in SSA go along with rising contents of plant residues in SOC, traceable by the molecular markers lignin and n-alkanes.
In contrast, agricultural intensification would reduce them due to lower C input and faster SOC turnover through tillage.
To test this, we analyzed lignin by the CuO oxidation method and n-alkanes by fast pressurized solvent extraction in topsoils (0-10 cm) of Arenosols and corresponding plant samples (trees, grasses and crops).
Sampling sites followed conservation gradients with low, medium and high elephant densities and intensification gradients with rangeland and cropland in the woodland savanna of the Namibian Zambezi Region.
Patterns of lignin-derived phenols were retained in the soil, whereas n-alkanes showed shifts in chain lengths. n-Alkanes also showed no clear increase or decrease under conservation or intensification, respectively.
Differently, lignin-derived phenols showed lower values under intensification than under conservation. Confirming our hypothesis, rising SOC contents with rising elephant densities (from 4.4 at low to 5.7 g kg(-1) SOC at high elephant densities) went along with an increasing accumulation of lignin-derived phenols (24.4-34.8 g kg(-1) VSCOC).
This increase is associated with the input of woody debris to the soil, as indicated by V-units and carbon isotopes, modulated by clay and woody biomass.
We conclude, that increasing input of woody residues into soil by browsing behaviour of elephants is an important mechanism for controlling SOC supply in the context of wildlife conservation and is traceable with lignin-derived phenols, but not with n-alkanes.
Rhizophagus irregularis is one of the most extensively studied arbuscular mycorrhizal fungi (AMF) that forms symbioses with and improves the performance of many crops. Lack of transformation protocol for R. irregularis renders it challenging to investigate molecular mechanisms that shape the physiology and interactions of this AMF with plants.
Here, we used all published genomics, transcriptomics, and metabolomics resources to gain insights into the metabolic functionalities of R. irregularis by reconstructing its high-quality genome-scale metabolic network that considers enzyme constraints. Extensive validation tests with the enzyme-constrained metabolic model demonstrated that it can be used to (i) accurately predict increased growth of R. irregularis on myristate with minimal medium; (ii) integrate enzyme abundances and carbon source concentrations that yield growth predictions with high and significant Spearman correlation (rS = 0.74) to measured hyphal dry weight; and (iii) simulate growth rate increases with tighter association of this AMF with the host plant across three fungal structures.
Based on the validated model and system-level analyses that integrate data from transcriptomics studies, we predicted that differences in flux distributions between intraradical mycelium and arbuscles are linked to changes in amino acid and cofactor biosynthesis.
Therefore, our results demonstrated that the enzyme-constrained metabolic model can be employed to pinpoint mechanisms driving developmental and physiological responses of R. irregularis to different environmental cues.
In conclusion, this model can serve as a template for other AMF and paves the way to identify metabolic engineering strategies to modulate fungal metabolic traits that directly affect plant performance.
IMPORTANCE Mounting evidence points to the benefits of the symbiotic interactions between the arbuscular mycorrhiza fungus Rhizophagus irregularis and crops; however, the molecular mechanisms underlying the physiological responses of this fungus to different host plants and environments remain largely unknown.
We present a manually curated, enzyme-constrained, genome-scale metabolic model of R. irregularis that can accurately predict experimentally observed phenotypes.
We show that this high-quality model provides an entry point into better understanding the metabolic and physiological responses of this fungus to changing environments due to the availability of different nutrients.
The model can be used to design metabolic engineering strategies to tailor R. irregularis metabolism toward improving the performance of host plants.
The inclusion of exotic germplasm serves as a crucial means to enhance allelic and
consequently phenotypic diversity in inbred crop species. Such species have experienced a reduction in diversity due to artificial selection focused on a limited set of traits. The natural biodiversity within ecosystems presents an opportunity to explore various traits influencing plant survival, reproductive fitness and yield potential. In agricultural research, the study of wild species closely related to cultivated plants serves as a means to comprehend the genetic foundations of past domestication events and the polymorphisms essential for future breeding efforts to develop superior varieties. In order to examine the metabolic composition, pinpoint quantitative trait loci (QTL) and facilitate their resolution an extensive large-scale analysis of metabolic QTL (mQTL) was conducted on tomato backcross inbred lines (BILs) derived from a cross between the wild species S. pennellii (5240) incorporated into the background of S. lycopersicum cv. LEA determinate inbred which can be grown in open fields and cv. TOP indeterminate which can be grown in greenhouse conditions. A large number of mQTL associated with primary secondary and lipid metabolism in fruit were identified across the two BIL populations. Epistasis, the interactions between genes at different loci, has been an interest in molecular and quantitative genetics for many decades. The study of epistasis requires the analysis of very large populations with multiple independent genotypes that carry specific genomic regions. In order to understand the genetic basis of tomato fruit metabolism, I extended the work to investigate epistatic interactions of the genomic regions. In addition, two candidate genes were identified through quantitative trait loci underlying fruit-specific sucrose and jasmonic acid derivatives. Finally, in this study, I assessed the genetic framework of fruit metabolic traits with a high level of detail, utilizing the newly created Solanum pennellii (5240) backcrossed introgression lines (n=3000). This investigation resulted in the discovery of promising candidate loci associated with significant fruit quality traits, including those to the abundance of glutamic acid and aspartic acid crucial elements contributing to the development of acidity and flavors.
Cell division and the resulting changes to the cell organization affect the shape and functionality of all tissues.
Thus, understanding the determinants of the tissue-wide changes imposed by cell division is a key question in developmental biology.
Here, we use a network representation of live cell imaging data from shoot apical meristems (SAMs) in Arabidopsis thaliana to predict cell division events and their consequences at the tissue level.
We show that a support vector machine classifier based on the SAM network properties is predictive of cell division events, with test accuracy of 76%, which matches that based on cell size alone.
Furthermore, we demonstrate that the combination of topological and biological properties, including cell size, perimeter, distance and shared cell wall between cells, can further boost the prediction accuracy of resulting changes in topology triggered by cell division.
Using our classifiers, we demonstrate the importance of microtubule-mediated cell-to-cell growth coordination in influencing tissue-level topology.
Together, the results from our network-based analysis demonstrate a feedback mechanism between tissue topology and cell division in A. thaliana SAMs.
In plants, the trehalose biosynthetic pathway plays key roles in the regulation of carbon allocation and stress adaptation.
Engineering of the pathway holds great promise to increase the stress resilience of crop plants.
The synthesis of trehalose proceeds by a two-step pathway in which a trehalose-phosphate synthase (TPS) uses UDP-glucose and glucose-6-phosphate to produce trehalose-6 phosphate (T6P) that is subsequently dephosphorylated by trehalose-6 phosphate phosphatase (TPP).
While plants usually do not accumulate high amounts of trehalose, their genome encodes large families of putative trehalose biosynthesis genes, with many members lacking obvious enzymatic activity.
Thus, the function of putative trehalose biosynthetic proteins in plants is only vaguely understood. To gain a deeper insight into the role of trehalose biosynthetic proteins in crops, we assessed the enzymatic activity of the TPS/TPP family from tomato (Solanum lycopersicum L.) and investigated their expression pattern in different tissues as well as in response to temperature shifts. From the 10 TPS isoforms tested, only the 2 proteins belonging to class I showed enzymatic activity, while all 5 TPP isoforms investigated were catalytically active.
Most of the TPS/TPP family members showed the highest expression in mature leaves, and promoter-reporter gene studies suggest that the two class I TPS genes have largely overlapping expression patterns within the vasculature, with only subtle differences in expression in fruits and flowers.
The majority of tomato TPS/TPP genes were induced by heat stress, and individual family members also responded to cold.
This suggests that trehalose biosynthetic pathway genes could play an important role during temperature stress adaptation.
In summary, our study represents a further step toward the exploitation of the TPS and TPP gene families for the improvement of tomato stress resistance.
Pichia pastoris (syn. Komagataella phaffii) represents a commonly used expression system in the biotech industry. High clonal variation of transformants, however, typically results in a broad range of specific productivities for secreted proteins. To isolate rare clones with exceedingly high product titers, an extensive number of clones need to be screened.
In contrast to high-throughput screenings of P. pastoris clones in microtiter plates, secrete-and -capture methodologies have the potential to efficiently isolate high-producer clones among millions of cells through fluorescence-activated cell sorting (FACS).Here, we describe a novel approach for the non-covalent binding of fragment antigen-binding (Fab) proteins to the cell surface for the isolation of high-producing clones.
Eight different single-chain variable fragment (scFv)-based capture matrices specific for the constant part of the Fabs were fused to the Saccharomyces cerevisiae alpha -agglutinin (SAG1) anchor protein for surface display in P. pastoris. By encoding the capture matrix on an episomal plasmid harboring inherently unstable autonomously replicating sequences (ARS), this secrete-and -capture system offers a switchable scFv display.
Efficient plasmid clearance upon removal of selective pres-sure enabled the direct use of isolated clones for subsequent Fab production. Flow-sorted clones (n = 276) displaying high amounts of Fabs showed a significant increase in median Fab titers detected in the cell-free supernatant (CFS) compared to unsorted clones (n = 276) when cells were cultivated in microtiter plates (fac-tor in the range of-21-49). Fab titers of clones exhibiting the highest product titer observed for each of the two approaches were increased by up to 8-fold for the sorted clone.
Improved Fab yields of sorted cells vs. unsorted cells were confirmed in an upscaled shake flask cultivation of selected candidates (factor in the range of-2-3). Hence, the developed display-based selection method proved to be a valuable tool for efficient clone screening in the early stages of our bioprocess development.
Many proteins are anchored to the cell surface of eukaryotes using a unique family of glycolipids called glycosylphosphatidylinositol (GPI) anchors.
These glycolipids also exist without a covalently bound protein, in particular on the cell surfaces of protozoan parasites where they are densely populated.
GPIs and GPI-anchored proteins participate in multiple cellular processes such as signal transduction, cell adhesion, protein trafficking and pathogenesis of Malaria, Toxoplasmosis, Trypanosomiasis and prion diseases, among others.
All GPIs share a common conserved glycan core modified in a cell-dependent manner with additional side glycans or phosphoethanolamine residues. Here, we use atomistic molecular dynamic simulations and perform a systematic study to evaluate the structural properties of GPIs with different side chains inserted in lipid bilayers.
Our results show a flop-down orientation of GPIs with respect to the membrane surface and the presentation of the side chain residues to the solvent.
This finding agrees well with experiments showing the role of the side residues as active epitopes for recognition of GPIs by macrophages and induction of GPI-glycan-specific immune responses.
Protein-GPI interactions were investigated by attaching parasitic GPIs to Green Fluorescent Protein. GPIs are observed to recline on the membrane surface and pull down the attached protein close to the membrane facilitating mutual contacts between protein, GPI and the lipid bilayer.
This model is efficient in evaluating the interaction of GPIs and GPI-anchored proteins with membranes and can be extended to study other parasitic GPIs and proteins and develop GPI-based immunoprophylaxis to treat infectious diseases.
The debate whether single large or several small (SLOSS) patches benefit biodiversity has existed for decades, but recent literature provides increasing evidence for the importance of small habitats.
Possible beneficial mechanisms include reduced presence of preda-tors and competitors in small habitat areas or specific functions such as stepping stones for dispersal.
Given the increasing amount of studies highlighting individual behavioral differences that may influence these functions, we hypothesize that the advantage of small versus large habitat patches not only depends on patch functionality but also on the presence of animal personalities (i.e., risk-tolerant vs. risk-averse). Using an individual-based, spatially-explicit community model, we analyzed the diversity of mammal communities in landscapes consisting of a few large habitat islands interspersed with different amounts and sizes of small habitat patches.
Within these heterogeneous environments, individuals compete for resources and form home-ranges, with only risk-tolerant individuals using habitat edges. Results show that when risk-tolerant individuals exist, small patches increase species diversity. A strong peak occurs at approximately 20% habitat cover in small patches when those small habitats are only used for foraging but not for breeding and home-range core position. Additional usage as stepping stones for juvenile dispersal further increases species persistence. Over-all, our results reveal that a combination of a few large and several small habitat patches promotes biodiversity by enhancing land-scape heterogeneity.
Here, heterogeneity is created by pronounced differences in habitat functionality, increasing edge density, and variability in habitat use by different behavioral types. The finding that a combination of single large AND several small (SLASS) patches is needed for effective biodiversity preservation has implications for advancing landscape conservation.
Particularly in struc-turally poor agricultural areas, modern technology enables precise management with the opportunity to create small foraging habitats by excluding less profitable agricultural land from cultivation.
The deficiency of a (bio)chemical reaction network can be conceptually interpreted as a measure of its ability to support exotic dynamical behavior and/or multistationarity. The classical definition of deficiency relates to the capacity of a network to permit variations of the complex formation rate vector at steady state, irrespective of the network kinetics. However, the deficiency is by definition completely insensitive to the fine details of the directionality of reactions as well as bounds on reaction fluxes. While the classical definition of deficiency can be readily applied in the analysis of unconstrained, weakly reversible networks, it only provides an upper bound in the cases where relevant constraints on reaction fluxes are imposed. Here we propose the concept of effective deficiency, which provides a more accurate assessment of the network’s capacity to permit steady state variations at the complex level for constrained networks of any reversibility patterns. The effective deficiency relies on the concept of nonstoichiometric balanced complexes, which we have already shown to be present in real-world biochemical networks operating under flux constraints. Our results demonstrate that the effective deficiency of real-world biochemical networks is smaller than the classical deficiency, indicating the effects of reaction directionality and flux bounds on the variation of the complex formation rate vector at steady state.
Introduction Flux phenotypes from different organisms and growth conditions allow better understanding of differential metabolic networks functions. Fluxes of metabolic reactions represent the integrated outcome of transcription, translation, and post-translational modifications, and directly affect growth and fitness. However, fluxes of intracellular metabolic reactions cannot be directly measured, but are estimated via metabolic flux analysis (MFA) that integrates data on isotope labeling patterns of metabolites with metabolic models. While the application of metabolomics technologies in photosynthetic organisms have resulted in unprecedented data from 13CO2-labeling experiments, the bottleneck in flux estimation remains the application of isotopically nonstationary MFA (INST-MFA). INST-MFA entails fitting a (large) system of coupled ordinary differential equations, with metabolite pools and reaction fluxes as parameters. Here, we focus on the Calvin-Benson cycle (CBC) as a key pathway for carbon fixation in photosynthesizing organisms and ask if approaches other than classical INST-MFA can provide reliable estimation of fluxes for reactions comprising this pathway.
Methods First, we show that flux estimation with the labeling patterns of all CBC intermediates can be formulated as a single constrained regression problem, avoiding the need for repeated simulation of time-resolved labeling patterns.
Results We then compare the flux estimates of the simulation-free constrained regression approach with those obtained from the classical INST-MFA based on labeling patterns of metabolites from the microalgae Chlamydomonas reinhardtii, Chlorella sorokiniana and Chlorella ohadii under different growth conditions.
Discussion Our findings indicate that, in data-rich scenarios, simulation-free regression-based approaches provide a suitable alternative for flux estimation from classical INST-MFA since we observe a high qualitative agreement (rs=0.89) to predictions obtained from INCA, a state-of-the-art tool for INST-MFA.
The European Union is highly dependent on soybean imports from overseas to meet its protein demands. Individual Member States have been quick to declare self-sufficiency targets for plant-based proteins, but detailed strategies are still lacking. Rising global temperatures have painted an image of a bright future for soybean production in Europe, but emerging climatic risks such as drought have so far not been included in any of those outlooks.
Here, we present simulations of future soybean production and the most prominent risk factors across Europe using an ensemble of climate and soybean growth models. Projections suggest a substantial increase in potential soybean production area and productivity in Central Europe, while southern European production would become increasingly dependent on supplementary irrigation. Average productivity would rise by 8.3% (RCP 4.5) to 8.7% (RCP 8.5) as a result of improved growing conditions (plant physiology benefiting from rising temperature and CO2 levels) and farmers adapting to them by using cultivars with longer phenological cycles. Suitable production area would rise by 31.4% (RCP 4.5) to 37.7% (RCP 8.5) by the mid-century, contributing considerably more than productivity increase to the production potential for closing the protein gap in Europe.
While wet conditions at harvest and incidental cold spells are the current key challenges for extending soybean production, the models and climate data analysis anticipate that drought and heat will become the dominant limitations in the future. Breeding for heat-tolerant and water-efficient genotypes is needed to further improve soybean adaptation to changing climatic conditions.
Woody plants provide natural archives of climatic variation which can be investigated by applying dendroclimatological methods. Such studies are limited in Southern Africa but have great potential of improving our understanding of past climates and plant functional adaptations in the region. This study therefore investigated the responsiveness of Dichrostachys cinerea to seasonal variations in temperature and rainfall at two sites in central Namibia, Waterberg and Kuzikus. Dichrostachys cinerea is one of the encroacher species thriving well in Namibia. A moving correlation and response function analysis were used to test its responsiveness to seasonal climatic variations over time. Dichrostachys cinerea growth rings showed relationships to late summer warming, lasting up to half of the rainy season. The results also revealed that past temperatures had been fluctuating and their influence on growth rings had been intensifying over the years, but to varying extents between the two sites. Temperature was a more important determinant of ring growth at the drier site (Kuzikus), while rainfall was more important at the wetter site (Waterberg). Growth ring responsiveness to rainfall was not immediate but showed a rather lagged pattern. We conclude that D. cinerea differentially responds to variations in rainfall and temperature across short climatic gradients. This study showed that the species, due to its somewhat wide ecological amplitude, has great potential for dendroclimatological studies in tropical regions.
Crop rotation, fertilization and residue management affect the water balance and crop production and can lead to different sensitivities to climate change. To assess the impacts of climate change on crop rotations (CRs), the crop model ensemble (APSIM,AQUACROP, CROPSYST, DAISY, DSSAT, HERMES, MONICA) was used. The yields and water balance of two CRs with the same set of crops (winter wheat, silage maize, spring barley and winter rape) in a continuous transient run from 1961 to 2080 were simulated. CR1 was without cover crops and without manure application. Straw after the harvest was exported from the fields. CR2 included cover crops, manure application and crop residue retention left on field. Simulations were performed using two soil types (Chernozem, Cambisol) within three sites in the Czech Republic, which represent temperature and precipitation gradients for crops in Central Europe. For the description of future climatic conditions, seven climate scenarios were used. Six of them had increasing CO & nbsp;concentrations according RCP 8.5, one had no CO2 increase in the future. The output of an ensemble expected higher productivity by 0.82 t/ha/year and 2.04 t/ha/year for yields and aboveground biomass in the future (2051-2080). However, if the direct effect of a CO2 increase is not considered, the average yields for lowlands will be lower. Compared to CR1, CR2 showed higher average yields of 1.26 t/ha/year for current climatic conditions and 1.41 t/ha/year for future climatic conditions. For the majority of climate change scenarios, the crop model ensemble agrees on the projected yield increase in C3 crops in the future for CR2 but not for CR1. Higher agreement for future yield increases was found for Chernozem, while for Cambisol, lower yields under dry climate scenarios are expected. For silage maize, changes in simulated yields depend on locality. If the same hybrid will be used in the future, then yield reductions should be expected within lower altitudes. The results indicate the potential for higher biomass production from cover crops, but CR2 is associated with almost 120 mm higher evapotranspiration compared to that of CR1 over a 5-year cycle for lowland stations in the future, which in the case of the rainfed agriculture could affect the long-term soil water balance. This could affect groundwater replenishment, especially for locations with fine textured soils, although the findings of this study highlight the potential for the soil water-holding capacity to buffer against the adverse weather conditions.
To better understand how climate change might influence global canola production, scientists from six countries have completed the first inter-comparison of eight crop models for simulating growth and seed yield of canola, based on experimental data from six sites across five countries. A sensitivity analysis was conducted with a combination of five levels of atmospheric CO2 concentrations, seven temperature changes, five precipitation changes, together with five nitrogen application rates. Our results were in several aspects different from those of previous model inter-comparison studies for wheat, maize, rice, and potato crops. A partial model calibration only on phenology led to very poor simulation of aboveground biomass and seed yield of canola, even from the ensemble median or mean. A full calibration with additional data of leaf area index, biomass, and yield from one treatment at each site reduced simulation error of seed yield from 43.8 to 18.0%, but the uncertainty in simulation results remained large. Such calibration (with data from one treatment) was not able to constrain model parameters to reduce simulation uncertainty across the wide range of environments. Using a multi-model ensemble mean or median reduced the uncertainty of yield simulations, but the simulation error remained much larger than observation errors, indicating no guarantee that the ensemble mean/median would predict the correct responses. Using multi-model ensemble median, canola yield was projected to decline with rising temperature (2.5-5.7% per degrees C), but to increase with increasing CO2 concentration (4.6-8.3% per 100-ppm), rainfall (2.1-6.1% per 10% increase), and nitrogen rates (1.3-6.0% per 10% increase) depending on locations. Due to the large uncertainty, these results need to be treated with caution. We further discuss the need to collect new data to improve modelling of several key physiological processes of canola for increased confidence in future climate impact assessments.
Bioenergetic approaches are increasingly used to understand how marine mammal populations could be affected by a changing and disturbed aquatic environment. There remain considerable gaps in our knowledge of marine mammal bioenergetics, which hinder the application of bioenergetic studies to inform policy decisions. We conducted a priority-setting exercise to identify high-priority unanswered questions in marine mammal bioenergetics, with an emphasis on questions relevant to conservation and management. Electronic communication and a virtual workshop were used to solicit and collate potential research questions from the marine mammal bioenergetic community. From a final list of 39 questions, 11 were identified as 'key'questions because they received votes from at least 50% of survey participants. Key questions included those related to energy intake (prey landscapes, exposure to human activities) and expenditure (field metabolic rate, exposure to human activities, lactation, time-activity budgets), energy allocation priorities, metrics of body condition and relationships with survival and reproductive success and extrapolation of data from one species to another. Existing tools to address key questions include labelled water, animal-borne sensors, mark-resight data from long-term research programs, environmental DNA and unmanned vehicles. Further validation of existing approaches and development of new methodologies are needed to comprehensively address some key questions, particularly for cetaceans. The identification of these key questions can provide a guiding framework to set research priorities, which ultimately may yield more accurate information to inform policies and better conserve marine mammal populations.
Phenology has emerged as key indicator of the biological impacts of climate change, yet the role of functional traits constraining variation in herbaceous species' phenology has received little attention. Botanical gardens are ideal places in which to investigate large numbers of species growing under common climate conditions. We ask whether interspecific variation in plant phenology is influenced by differences in functional traits. We recorded onset, end, duration and intensity of initial growth, leafing out, leaf senescence, flowering and fruiting for 212 species across five botanical gardens in Germany. We measured functional traits, including plant height, absolute and specific leaf area, leaf dry matter content, leaf carbon and nitrogen content and seed mass and accounted for species' relatedness. Closely related species showed greater similarities in timing of phenological events than expected by chance, but species' traits had a high degree of explanatory power, pointing to paramount importance of species' life-history strategies. Taller plants showed later timing of initial growth, and flowered, fruited and underwent leaf senescence later. Large-leaved species had shorter flowering and fruiting durations. Taller, large-leaved species differ in their phenology and are more competitive than smaller, small-leaved species. We assume climate warming will change plant communities' competitive hierarchies with consequences for biodiversity.
The subgenus Laurentomantis in the genus Gephyromantis contains some of the least known amphibian species of Madagascar. The six currently valid nominal species are rainforest frogs known from few individuals, hampering a full understanding of the species diversity of the clade. We assembled data on specimens collected during field surveys over the past 30 years and integrated analysis of mitochondrial and nuclear-encoded genes of 88 individuals, a comprehensive bioacoustic analysis, and morphological comparisons to delimit a minimum of nine species-level lineages in the subgenus. To clarify the identity of the species Gephyromantis malagasius, we applied a target-enrichment approach to a sample of the 110 year old holotype of Microphryne malagasia Methuen and Hewitt, 1913 to assign this specimen to a lineage based on a mitochondrial DNA barcode. The holotype clustered unambiguously with specimens previously named G. ventrimaculatus. Consequently we propose to consider Trachymantis malagasia ventrimaculatus Angel, 1935 as a junior synonym of Gephyromantis malagasius. Due to this redefinition of G. malagasius, no scientific name is available for any of the four deep lineages of frogs previously subsumed under this name, all characterized by red color ventrally on the hindlimbs. These are here formally named as Gephyromantis fiharimpe sp. nov., G. matsilo sp. nov., G. oelkrugi sp. nov., and G. portonae sp. nov. The new species are distinguishable from each other by genetic divergences of >4% uncorrected pairwise distance in a fragment of the 16S rRNA marker and a combination of morphological and bioacoustic characters. Gephyromantis fiharimpe and G. matsilo occur, respectively, at mid-elevations and lower elevations along a wide stretch of Madagascar's eastern rainforest band, while G. oelkrugi and G. portonae appear to be more range-restricted in parts of Madagascar's North East and Northern Central East regions. Open taxonomic questions surround G. horridus, to which we here assign specimens from Montagne d'Ambre and the type locality Nosy Be; and G. ranjomavo, which contains genetically divergent populations from Marojejy, Tsaratanana, and Ampotsidy.
Notwithstanding their 3 to 5% mortality, the 2.7 million envenomation-related injuries occurring annually-predominantly across Africa, Asia, and Latin America-are also major causes of morbidity. Venom toxin-damaged tissue will develop infections in some 75% of envenomation victims, with E. faecalis being a common culprit of disease; however, such infections are generally considered to be independent of envenomation.
Animal venoms are considered sterile sources of antimicrobial compounds with strong membrane-disrupting activity against multidrug-resistant bacteria.
However, venomous bite wound infections are common in developing nations. Investigating the envenomation organ and venom microbiota of five snake and two spider species, we observed venom community structures that depend on the host venomous animal species and evidenced recovery of viable microorganisms from black-necked spitting cobra (Naja nigricollis) and Indian ornamental tarantula (Poecilotheria regalis) venoms. Among the bacterial isolates recovered from N. nigricollis, we identified two venom-resistant, novel sequence types of Enterococcus faecalis whose genomes feature 16 virulence genes, indicating infectious potential, and 45 additional genes, nearly half of which improve bacterial membrane integrity.
Our findings challenge the dogma of venom sterility and indicate an increased primary infection risk in the clinical management of venomous animal bite wounds. IMPORTANCE Notwithstanding their 3 to 5% mortality, the 2.7 million envenomation-related injuries occurring annually-predominantly across Africa, Asia, and Latin America-are also major causes of morbidity. Venom toxin-damaged tissue will develop infections in some 75% of envenomation victims, with E. faecalis being a common culprit of disease; however, such infections are generally considered to be independent of envenomation. Here, we provide evidence on venom microbiota across snakes and arachnida and report on the convergent evolution mechanisms that can facilitate adaptation to black-necked cobra venom in two independent E. faecalis strains, easily misidentified by biochemical diagnostics.
Therefore, since inoculation with viable and virulence gene-harboring bacteria can occur during envenomation, acute infection risk management following envenomation is warranted, particularly for immunocompromised and malnourished victims in resource-limited settings.
These results shed light on how bacteria evolve for survival in one of the most extreme environments on Earth and how venomous bites must be also treated for infections.
Biological dinitrogen (N-2) fixation is performed solely by specialized bacteria and archaea termed diazotrophs, introducing new reactive nitrogen into aquatic environments.
Conventionally, phototrophic cyanobacteria are considered the major diazotrophs in aquatic environments. However, accumulating evidence indicates that diverse non-cyanobacterial diazotrophs (NCDs) inhabit a wide range of aquatic ecosystems, including temperate and polar latitudes, coastal environments and the deep ocean. NCDs are thus suspected to impact global nitrogen cycling decisively, yet their ecological and quantitative importance remain unknown. Here we review recent molecular and biogeochemical evidence demonstrating that pelagic NCDs inhabit and thrive especially on aggregates in diverse aquatic ecosystems. Aggregates are characterized by reduced-oxygen microzones, high C:N ratio (above Redfield) and high availability of labile carbon as compared to the ambient water.
We argue that planktonic aggregates are important loci for energetically-expensive N-2 fixation by NCDs and propose a conceptual framework for aggregate-associated N-2 fixation. Future studies on aggregate-associated diazotrophy, using novel methodological approaches, are encouraged to address the ecological relevance of NCDs for nitrogen cycling in aquatic environments.
Larix species range dynamics in Siberia since the Last Glacial captured from sedimentary ancient DNA
(2022)
Climate change is expected to cause major shifts in boreal forests which are in vast areas of Siberia dominated by two species of the deciduous needle tree larch (Larix). The species differ markedly in their ecosystem functions, thus shifts in their respective ranges are of global relevance.
However, drivers of species distribution are not well understood, in part because paleoecological data at species level are lacking. This study tracks Larix species distribution in time and space using target enrichment on sedimentary ancient DNA extracts from eight lakes across Siberia. We discovered that Larix sibirica, presently dominating in western Siberia, likely migrated to its northern distribution area only in the Holocene at around 10,000 years before present (ka BP), and had a much wider eastern distribution around 33 ka BP. Samples dated to the Last Glacial Maximum (around 21 ka BP), consistently show genotypes of L. gmelinii.
Our results suggest climate as a strong determinant of species distribution in Larix and provide temporal and spatial data for species projection in a changing climate.
Using ancient sedimentary DNA from up to 50 kya, dramatic distributional shifts are documented in two dominant boreal larch species, likely guided by environmental changes suggesting climate as a strong determinant of species distribution.
Mediterranean oak woodlands are currently facing unprecedented degradation threats from oak decline. The Iberian oak decline "Seca", related to Phytophthora infection, causes crown defoliation that may adversely affect ecosystem services (ESs). We aim to improve our understanding of how Seca-induced declines in crown foliation affect the provision of multiple ecosystem services from understory vegetation. We selected holm (Quercus ilex) and cork oak (Q. suber) trees in a Spanish oak woodland and evaluated three proxies of canopy effects. One proxy (crown defoliation) solely captured Seca-dependent effects, one proxy solely captured Seca-independent effects (tree dimensions such as diameter and height), while the third proxy (tree vigor) captured overall canopy effects. We then used the best-performing proxies to assess canopy effects on key ecosystem services (ESs) such as aboveground net primary production (ANPP), grass and legume biomass, species diversity, litter decomposition rates, and a combined index of ecosystem multifunctionality. <br /> We found that both types of canopy effects (i.e. Seca-dependent and Seca-independent effects) were related, indicating that ANPP was disproportionally more affected by Seca when defoliated trees were large. Responses of other ESs were mostly not significant, although lower species diversity was found under trees with intermediate vigor. Our results underline that a Seca-related decline in canopy density triggered a homogenization of ecosystem service delivery on the ecosystem scale. The ecosystem functions (EFs) under trees of low vigor are similar to that in adjacent open microsites indicating that the presence of vigorous (i.e. old and vital) trees is critical for maintaining EFs at a landscape level. Our results also highlight the importance of quantifying not only defoliation but also tree dimensions as both factors jointly and interactively modify canopy effects on ecosystem multifunctionality.
Environmental monitoring involves the quantification of microscopic cells and particles such as algae, plant cells, pollen, or fungal spores. Traditional methods using conventional microscopy require expert knowledge, are time-intensive and not well-suited for automated high throughput. Multispectral imaging flow cytometry (MIFC) allows measurement of up to 5000 particles per second from a fluid suspension and can simultaneously capture up to 12 images of every single particle for brightfield and different spectral ranges, with up to 60x magnification. The high throughput of MIFC has high potential for increasing the amount and accuracy of environmental monitoring, such as for plant-pollinator interactions, fossil samples, air, water or food quality that currently rely on manual microscopic methods. Automated recognition of particles and cells is also possible, when MIFC is combined with deep-learning computational techniques. Furthermore, various fluorescence dyes can be used to stain specific parts of the cell to highlight physiological and chemical features including: vitality of pollen or algae, allergen content of individual pollen, surface chemical composition (carbohydrate coating) of cells, DNA- or enzyme-activity staining. Here, we outline the great potential for MIFC in environmental research for a variety of research fields and focal organisms. In addition, we provide best practice recommendations.
Crop model intercomparison studies have mostly focused on the assessment of predictive capabilities for crop development using weather and basic soil data from the same location. Still challenging is the model performance when considering complex interrelations between soil and crop dynamics under a changing climate. The objective of this study was to test the agronomic crop and environmental flux-related performance of a set of crop models. The aim was to predict weighing lysimeter-based crop (i.e., agronomic) and water-related flux or state data (i.e., environmental) obtained for the same soil monoliths that were taken from their original environment and translocated to regions with different climatic conditions, after model calibration at the original site. Eleven models were deployed in the study. The lysimeter data (2014-2018) were from the Dedelow (Dd), Bad Lauchstadt (BL), and Selhausen (Se) sites of the TERENO (TERrestrial ENvironmental Observatories) SOILCan network. Soil monoliths from Dd were transferred to the drier and warmer BL site and the wetter and warmer Se site, which allowed a comparison of similar soil and crop under varying climatic conditions. The model parameters were calibrated using an identical set of crop- and soil-related data from Dd. Environmental fluxes and crop growth of Dd soil were predicted for conditions at BL and Se sites using the calibrated models. The comparison of predicted and measured data of Dd lysimeters at BL and Se revealed differences among models. At site BL, the crop models predicted agronomic and environmental components similarly well. Model performance values indicate that the environmental components at site Se were better predicted than agronomic ones. The multi-model mean was for most observations the better predictor compared with those of individual models. For Se site conditions, crop models failed to predict site-specific crop development indicating that climatic conditions (i.e., heat stress) were outside the range of variation in the data sets considered for model calibration. For improving predictive ability of crop models (i.e., productivity and fluxes), more attention should be paid to soil-related data (i.e., water fluxes and system states) when simulating soil-crop-climate interrelations in changing climatic conditions.
Moderate and temporary heat stresses prime plants to tolerate, and survive, a subsequent severe heat stress. Such acquired thermotolerance can be maintained for several days under normal growth conditions, and can create a heat stress memory. We recently demonstrated that plastid-localized small heat shock protein 21 ( HSP21) is a key component of heat stress memory in Arabidopsis thaliana. A sustained high abundance of HSP21 during the heat stress recovery phase extends heat stress memory. The level of HSP21 is negatively controlled by plastid-localized metalloprotease FtsH6 during heat stress recovery. Here, we demonstrate that autophagy, a cellular recycling mechanism, exerts additional control over HSP21 degradation. Genetic and chemical disruption of both metalloprotease activity and autophagy trigger superior HSP21 accumulation, thereby improving memory. Furthermore, we provide evidence that autophagy cargo receptor ATG8-INTERACTING PROTEIN1 (ATI1) is associated with heat stress memory. ATI1 bodies co-localize with both autophagosomes and HSP21, and their abundance and transport to the vacuole increase during heat stress recovery. Together, our results provide new insights into the module for control of the regulation of heat stress memory, in which two distinct protein degradation pathways act in concert to degrade HSP21, thereby enabling cells to recover from the heat stress effect at the cost of reducing the heat stress memory.
Zoosporic fungi of the phylum Chytridiomycota (chytrids) regularly dominate pelagic fungal communities in freshwater and marine environments. Their lifestyles range from obligate parasites to saprophytes. Yet, linking the scarce available sequence data to specific ecological traits or their host ranges constitutes currently a major challenge. We combined 28 S rRNA gene amplicon sequencing with targeted isolation and sequencing approaches, along with cross-infection assays and analysis of chytrid infection prevalence to obtain new insights into chytrid diversity, ecology, and seasonal dynamics in a temperate lake. Parasitic phytoplankton-chytrid and saprotrophic pollen-chytrid interactions made up the majority of zoosporic fungal reads. We explicitly demonstrate the recurrent dominance of parasitic chytrids during frequent diatom blooms and saprotrophic chytrids during pollen rains. Distinct temporal dynamics of diatom-specific parasitic clades suggest mechanisms of coexistence based on niche differentiation and competitive strategies. The molecular and ecological information on chytrids generated in this study will aid further exploration of their spatial and temporal distribution patterns worldwide. To fully exploit the power of environmental sequencing for studies on chytrid ecology and evolution, we emphasize the need to intensify current isolation efforts of chytrids and integrate taxonomic and autecological data into long-term studies and experiments.
The genus Microhyla Tschudi, 1838 includes 52 species and is one of the most diverse genera of the family Microhylidae, being the most species-rich taxon of the Asian subfamily Microhylinae. The recent, rapid description of numerous new species of Microhyla with complex phylogenetic relationships has made the taxonomy of the group especially challenging. Several recent phylogenetic studies suggested paraphyly of Microhyla with respect to Glyphoglossus Gunther, 1869, and revealed three major phylogenetic lineages of mid-Eocene origin within this assemblage. However, comprehensive works assessing morphological variation among and within these lineages are absent. In the present study we investigate the generic taxonomy of Microhyla-Glyphoglossus assemblage based on a new phylogeny including 57 species, comparative morphological analysis of skeletons from cleared-and-stained specimens for 23 species, and detailed descriptions of generalized osteology based on volume-rendered micro-CT scans for five speciesal-together representing all major lineages within the group. The results confirm three highly divergent and well-supported clades that correspond with external and osteological morphological characteristics, as well as respective geographic distribution. Accordingly, acknowledging ancient divergence between these lineages and their significant morphological differentiation, we propose to consider these three lineages as distinct genera: Microhyla sensu stricto, Glyphoglossus, and a newly described genus, Nanohyla gen. nov.
Tula orthohantavirus (TULV) is a rodent-borne hantavirus with broad geographical distribution in Europe. Its major reservoir is the common vole (Microtus arvalis), but TULV has also been detected in closely related vole species. Given the large distributional range and high amplitude population dynamics of common voles, this host-pathogen complex presents an ideal system to study the complex mechanisms of pathogen transmission in a wild rodent reservoir. We investigated the dynamics of TULV prevalence and the subsequent potential effects on the molecular evolution of TULV in common voles of the Central evolutionary lineage. Rodents were trapped for three years in four regions of Germany and samples were analyzed for the presence of TULV-reactive antibodies and TULV RNA with subsequent sequence determination. The results show that individual (sex) and population-level factors (abundance) of hosts were significant predictors of local TULV dynamics. At the large geographic scale, different phylogenetic TULV clades and an overall isolation-by-distance pattern in virus sequences were detected, while at the small scale (<4 km) this depended on the study area. In combination with an overall delayed density dependence, our results highlight that frequent, localized bottleneck events for the common vole and TULV do occur and can be offset by local recolonization dynamics.
The study of diamond frogs (genus Rhombophryne, endemic to Madagascar) has been historically hampered by the paucity of available specimens, because of their low detectability in the field. Over the last 10 years, 13 new taxa have been described, and 20 named species are currently recognized. Nevertheless, undescribed diversity within the genus is probably large, calling for a revision of the taxonomic identification of published records and an update of the known distribution of each lineage. Here we generate DNA sequences of the mitochondrial 16S rRNA gene of all specimens available to us, revise the genetic data from public databases, and report all deeply divergent mitochondrial lineages of Rhombophryne identifiable from these data. We also generate a multi-locus dataset (including five mitochondrial and eight nuclear markers; 9844 bp) to infer a species-level phylogenetic hypothesis for the diversification of this genus and revise the distribution of each lineage. We recognize a total of 10 candidate species, two of which are identified here for the first time. The genus Rhombophryne is here proposed to be divided into six main species groups, and phylogenetic relationships among some of them are not fully resolved. These frogs are primarily distributed in northern Madagascar, and most species are known from only few localities. A previous record of this genus from the Tsingy de Bemaraha (western Madagascar) is interpreted as probably due to a mislabelling and should not be considered further unless confirmed by new data. By generating this phylogenetic hypothesis and providing an updated distribution of each lineage, our findings will facilitate future species descriptions, pave the way for evolutionary studies, and provide valuable information for the urgent conservation of diamond frogs.
Simple Summary Gliomas are heterogenous types of cancer, therefore the therapy should be personalized and targeted toward specific pathways. We developed a methodology that corrected strong batch effects from The Cancer Genome Atlas datasets and estimated glioma grade-specific co-enrichment mechanisms using machine learning. Our findings created hypotheses for annotations, e.g., pathways, that should be considered as therapeutic targets. Gliomas develop and grow in the brain and central nervous system. Examining glioma grading processes is valuable for improving therapeutic challenges. One of the most extensive repositories storing transcriptomics data for gliomas is The Cancer Genome Atlas (TCGA). However, such big cohorts should be processed with caution and evaluated thoroughly as they can contain batch and other effects. Furthermore, biological mechanisms of cancer contain interactions among biomarkers. Thus, we applied an interpretable machine learning approach to discover such relationships. This type of transparent learning provides not only good predictability, but also reveals co-predictive mechanisms among features. In this study, we corrected the strong and confounded batch effect in the TCGA glioma data. We further used the corrected datasets to perform comprehensive machine learning analysis applied on single-sample gene set enrichment scores using collections from the Molecular Signature Database. Furthermore, using rule-based classifiers, we displayed networks of co-enrichment related to glioma grades. Moreover, we validated our results using the external glioma cohorts. We believe that utilizing corrected glioma cohorts from TCGA may improve the application and validation of any future studies. Finally, the co-enrichment and survival analysis provided detailed explanations for glioma progression and consequently, it should support the targeted treatment.
This study focuses on three key aspects: (a) crude throat swab samples in a viral transport medium (VTM) as templates for RT-LAMP reactions; (b) a biotinylated DNA probe with enhanced specificity for LFA readouts; and (c) a digital semi-quantification of LFA readouts. Throat swab samples from SARS-CoV-2 positive and negative patients were used in their crude (no cleaning or pre-treatment) forms for the RT-LAMP reaction. The samples were heat-inactivated but not treated for any kind of nucleic acid extraction or purification. The RT-LAMP (20 min processing time) product was read out by an LFA approach using two labels: FITC and biotin. FITC was enzymatically incorporated into the RT-LAMP amplicon with the LF-LAMP primer, and biotin was introduced using biotinylated DNA probes, specifically for the amplicon region after RT-LAMP amplification. This assay setup with biotinylated DNA probe-based LFA readouts of the RT-LAMP amplicon was 98.11% sensitive and 96.15% specific. The LFA result was further analysed by a smartphone-based IVD device, wherein the T-line intensity was recorded. The LFA T-line intensity was then correlated with the qRT-PCR Ct value of the positive swab samples. A digital semi-quantification of RT-LAMP-LFA was reported with a correlation coefficient of R2 = 0.702. The overall RT-LAMP-LFA assay time was recorded to be 35 min with a LoD of three RNA copies/µL (Ct-33). With these three advancements, the nucleic acid testing-point of care technique (NAT-POCT) is exemplified as a versatile biosensor platform with great potential and applicability for the detection of pathogens without the need for sample storage, transportation, or pre-processing.
Urbanization promotes specific bacteria in freshwater microbiomes including potential pathogens
(2022)
Freshwater ecosystems are characterized by complex and highly dynamic microbial communities that are strongly structured by their local environment and biota. Accelerating urbanization and growing city populations detrimentally alter freshwater environments. To determine differences in freshwater microbial communities associated with urban-ization, full-length 16S rRNA gene PacBio sequencing was performed in a case study from surface waters and sedi-ments from a wastewater treatment plant, urban and rural lakes in the Berlin-Brandenburg region, Northeast Germany. Water samples exhibited highly habitat specific bacterial communities with multiple genera showing clear urban signatures. We identified potentially harmful bacterial groups associated with environmental parameters specific to urban habitats such as Alistipes, Escherichia/Shigella, Rickettsia and Streptococcus. We demonstrate that urban-ization alters natural microbial communities in lakes and, via simultaneous warming and eutrophication and creates favourable conditions that promote specific bacterial genera including potential pathogens. Our findings are evidence to suggest an increased potential for long-term health risk in urbanized waterbodies, at a time of rapidly expanding global urbanization. The results highlight the urgency for undertaking mitigation measures such as targeted lake restoration projects and sustainable water management efforts.
The physiological dependence of animals on dietary intake of vitamins, amino acids, and fatty acids is ubiquitous. Sharp differences in the availability of these vital dietary biomolecules among different resources mean that consumers must adopt a range of strategies to meet their physiological needs. We review the emerging work on omega-3 long-chain polyunsaturated fatty acids, focusing predominantly on predator-prey interactions, to illustrate that trade-off between capacities to consume resources rich in vital biomolecules and internal synthesis capacity drives differences in phenotype and fitness of consumers. This can then feedback to impact ecosystem functioning. We outline how focus on vital dietary biomolecules in eco-eco-devo dynamics can improve our understanding of anthropogenic changes across multiple levels of biological organization.
The capillary-venous pathology cerebral cavernous malformation (CCM) is caused by loss of CCM1/Krev interaction trapped protein 1 (KRIT1), CCM2/MGC4607, or CCM3/PDCD10 in some endothelial cells. Mutations of CCM genes within the brain vasculature can lead to recurrent cerebral hemorrhages. Pharmacological treatment options are urgently needed when lesions are located in deeply-seated and in-operable regions of the central nervous system. Previous pharmacological suppression screens in disease models of CCM led to the discovery that treatment with retinoic acid improved CCM phenotypes. This finding raised a need to investigate the involvement of retinoic acid in CCM and test whether it has a curative effect in preclinical mouse models. Here, we show that components of the retinoic acid synthesis and degradation pathway are transcriptionally misregulated across disease models of CCM. We complemented this analysis by pharmacologically modifying retinoic acid levels in zebrafish and human endothelial cell models of CCM, and in acute and chronic mouse models of CCM. Our pharmacological intervention studies in CCM2-depleted human umbilical vein endothelial cells (HUVECs) and krit1 mutant zebrafish showed positive effects when retinoic acid levels were increased. However, therapeutic approaches to prevent the development of vascular lesions in adult chronic murine models of CCM were drug regiment-sensitive, possibly due to adverse developmental effects of this hormone. A treatment with high doses of retinoic acid even worsened CCM lesions in an adult chronic murine model of CCM. This study provides evidence that retinoic acid signaling is impaired in the CCM pathophysiology and suggests that modification of retinoic acid levels can alleviate CCM phenotypes.
Cell-level systems biology model to study inflammatory bowel diseases and their treatment options
(2023)
To help understand the complex and therapeutically challenging inflammatory bowel diseases (IBDs), we developed a systems biology model of the intestinal immune system that is able to describe main aspects of IBD and different treatment modalities thereof. The model, including key cell types and processes of the mucosal immune response, compiles a large amount of isolated experimental findings from literature into a larger context and allows for simulations of different inflammation scenarios based on the underlying data and assumptions. In the context of a large and diverse virtual IBD population, we characterized the patients based on their phenotype (in contrast to healthy individuals, they developed persistent inflammation after a trigger event) rather than on a priori assumptions on parameter differences to a healthy individual. This allowed to reproduce the enormous diversity of predispositions known to lead to IBD. Analyzing different treatment effects, the model provides insight into characteristics of individual drug therapy. We illustrate for anti-TNF-alpha therapy, how the model can be used (i) to decide for alternative treatments with best prospects in the case of nonresponse, and (ii) to identify promising combination therapies with other available treatment options.
Species of the mustelid subfamily Guloninae inhabit diverse habitats on multiple continents, and occupy a variety of ecological niches. They differ in feeding ecologies, reproductive strategies and morphological adaptations. To identify candidate loci associated with adaptations to their respective environments, we generated a de novo assembly of the tayra (Eira barbara), the earliest diverging species in the subfamily, and compared this with the genomes available for the wolverine (Gulo gulo) and the sable (Martes zibellina). Our comparative genomic analyses included searching for signs of positive selection, examining changes in gene family sizes and searching for species-specific structural variants. Among candidate loci associated with phenotypic traits, we observed many related to diet, body condition and reproduction. For example, for the tayra, which has an atypical gulonine reproductive strategy of aseasonal breeding, we observed species-specific changes in many pregnancy-related genes. For the wolverine, a circumpolar hypercarnivore that must cope with seasonal food scarcity, we observed many changes in genes associated with diet and body condition. All types of genomic variation examined (single nucleotide polymorphisms, gene family expansions, structural variants) contributed substantially to the identification of candidate loci. This argues strongly for consideration of variation other than single nucleotide polymorphisms in comparative genomics studies aiming to identify loci of adaptive significance.
Understanding the history and regional singularities of human impact on vegetation is key to developing strategies for sustainable ecosystem management. In this study, fossil and modern pollen datasets from China are employed to investigate temporal changes in pollen composition, analogue quality, and pollen diversity during the Holocene. Anthropogenic disturbance and vegetation's responses are also assessed. Results reveal that pollen assemblages from non-forest communities fail to provide evidence of human impact for the western part of China (annual precipitation less than 400 mm and/or elevation more than 3000 m.a.s.l.), as inferred from the stable quality of modern analogues, principal components, and diversity of species and communities throughout the Holocene. For the eastern part of China, the proportion of fossil pollen spectra with good modern analogues increases from ca. 50% to ca. 80% during the last 2 millennia, indicating an enhanced intensity of anthropogenic disturbance on vegetation. This disturbance has caused the pollen spectra to become taxonomically less diverse over space (reduced abundances of arboreal taxa and increased abundances of herbaceous taxa), highlighting a reduced south-north differentiation and divergence from past vegetation between regions in the eastern part of China. We recommend that care is taken in eastern China when basing the development of ecosystem management strategies on vegetation changes in the region during the last 2000 years, since humans have significantly disturbed the vegetation during this period.
The plant cell wall plays several crucial roles during plant development with its integrity acting as key signalling component for growth regulation during biotic and abiotic stresses. Cellulose microfibrils, the principal load-bearing components is the major component of the primary cell wall, whose synthesis is mediated by microtubule-associated CELLULOSE SYNTHASE (CESA) COMPLEXES (CSC). Previous studies have shown that CSC interacting proteins COMPANION OF CELLULOSE SYNTHASE (CC) facilitate sustained cellulose synthesis during salt stress by promoting repolymerization of cortical microtubules. However, our understanding of cellulose synthesis during salt stress remains incomplete.
In this study, a pull-down of CC1 protein led to the identification of a novel interactor, termed LEA-like. Phylogenetic analysis revealed that LEA-like belongs to the LATE EMBRYOGENESIS ABUNDANT (LEA) protein family, specifically to the LEA_2 subgroup, showing a close relationship with the CC proteins. Roots of the double mutants lea-like and its closest homolog emb3135 exhibited hypersensitivity when grown on cellulose synthesis inhibitors. Further analysis of higher-order mutants of lea-like, emb3135, and cesa6 demonstrated a genetic interaction between them indicating a significant role in cellulose synthesis.
Live-cell imaging revealed that both LEA-like and EMB3135 migrated with the CSC at the plasma membrane along microtubule tracks in control and oryzalin-treated conditions which destabilize microtubules, suggesting a tight interaction. Investigation of fluorescently labeled lines of different domains of the LEA-like protein revealed that the N-terminal cytosolic domain of LEA-like colocalizes with microtubules, suggesting a physical association between the two.
Considering the established role of LEA proteins in abiotic stress tolerance, we performed phenotypic analysis of the mutant under various stresses. Growth of double mutants of lea-like and emb3135 on NaCl containing media resulted in swelling of root cell indicating a putative role in salt stress tolerance. Supportive of this the quadruple mutant, lacking LEA-like, EMB3135, CC1, and CC2 proteins, exhibited a severe root growth defect on NaCl media compared to control conditions. Live-cell imaging revealed that under salt stress, the LEA-like protein forms aggregates in the plasma membrane.
In conclusion, this study has unveiled two novel interactors of the CSC that act with the CC proteins that regulate plant growth in response to salt stress providing new insights into the intricate regulation of cellulose synthesis, particularly under such conditions.
Leaves exhibit cells with varying degrees of shape complexity along the proximodistal axis. Heterogeneities in growth directions within individual cells bring about such complexity in cell shape. Highly complex and interconnected gene regulatory networks and signaling pathways have been identified to govern these processes. In addition, the organization of cytoskeletal networks and cell wall mechanical properties greatly influences the regulation of cell shape. Research has shown that microtubules are involved in regulating cellulose deposition and direc-tion of cell growth. However, comprehensive analysis of the regulation of the actin cytoskele-ton in cell shape regulation has not been well studied.
This thesis provides evidence that actin regulates aspects of cell growth, division, and direction-al expansion that impacts morphogenesis of developing leaves. The jigsaw puzzle piece mor-phology of epidermal pavement cells further serves as an ideal system to investigate the com-plex process of morphogenetic processes occurring at the cellular level. Here we have em-ployed live cell based imaging studies to track the development of pavement cells in actin com-promised conditions. Genetic perturbation of two predominantly expressed vegetative actin genes ACTIN2 and ACTIN7 results in delayed emergence of the cellular protrusions in pave-ment cells. Perturbation of actin also impacted the organization of microtubule in these cells that is known to promote emergence of cellular protrusions. Further, live-cell imaging of actin or-ganization revealed a correlation with cell shape, suggesting that actin plays a role in influencing pavement cell morphogenesis.
In addition, disruption of actin leads to an increase in cell size along the leaf midrib, with cells being highly anisotropic due to reduced cell division. The reduction of cell division further im-pacted the morphology of the entire leaf, with the mutant leaves being more curved. These re-sults suggests that actin plays a pivotal role in regulating morphogenesis at the cellular and tis-sue scales thereby providing valuable insights into the role of the actin cytoskeleton in plant morphogenesis.
The use of automated tools to reconstruct lipid metabolic pathways is not warranted in plants. Here, the authors construct Plant Lipid Module for Arabidopsis rosette using constraint-based modeling, demonstrate its integration in other plant metabolic models, and use it to dissect the genetic architecture of lipid metabolism.
Lipids play fundamental roles in regulating agronomically important traits. Advances in plant lipid metabolism have until recently largely been based on reductionist approaches, although modulation of its components can have system-wide effects. However, existing models of plant lipid metabolism provide lumped representations, hindering detailed study of component modulation. Here, we present the Plant Lipid Module (PLM) which provides a mechanistic description of lipid metabolism in the Arabidopsis thaliana rosette. We demonstrate that the PLM can be readily integrated in models of A. thaliana Col-0 metabolism, yielding accurate predictions (83%) of single lethal knock-outs and 75% concordance between measured transcript and predicted flux changes under extended darkness. Genome-wide associations with fluxes obtained by integrating the PLM in diel condition- and accession-specific models identify up to 65 candidate genes modulating A. thaliana lipid metabolism. Using mutant lines, we validate up to 40% of the candidates, paving the way for identification of metabolic gene function based on models capturing natural variability in metabolism.
Background
Teleost fishes comprise more than half of the vertebrate species. Within teleosts, most phylogenies consider the split between Osteoglossomorpha and Euteleosteomorpha/Otomorpha as basal, preceded only by the derivation of the most primitive group of teleosts, the Elopomorpha. While Osteoglossomorpha are generally species poor, the taxon contains the African weakly electric fish (Mormyroidei), which have radiated into numerous species. Within the mormyrids, the genus Campylomormyrus is mostly endemic to the Congo Basin. Campylomormyrus serves as a model to understand mechanisms of adaptive radiation and ecological speciation, especially with regard to its highly diverse species-specific electric organ discharges (EOD). Currently, there are few well-annotated genomes available for electric fish in general and mormyrids in particular. Our study aims at producing a high-quality genome assembly and to use this to examine genome evolution in relation to other teleosts. This will facilitate further understanding of the evolution of the osteoglossomorpha fish in general and of electric fish in particular.
Results
A high-quality weakly electric fish (C. compressirostris) genome was produced from a single individual with a genome size of 862 Mb, consisting of 1,497 contigs with an N50 of 1,399 kb and a GC-content of 43.69%. Gene predictions identified 34,492 protein-coding genes, which is a higher number than in the two other available Osteoglossomorpha genomes of Paramormyrops kingsleyae and Scleropages formosus. A Computational Analysis of gene Family Evolution (CAFE5) comparing 33 teleost fish genomes suggests an overall faster gene family turnover rate in Osteoglossomorpha than in Otomorpha and Euteleosteomorpha. Moreover, the ratios of expanded/contracted gene family numbers in Osteoglossomorpha are significantly higher than in the other two taxa, except for species that had undergone an additional genome duplication (Cyprinus carpio and Oncorhynchus mykiss). As potassium channel proteins are hypothesized to play a key role in EOD diversity among species, we put a special focus on them, and manually curated 16 Kv1 genes. We identified a tandem duplication in the KCNA7a gene in the genome of C. compressirostris.
Conclusions
We present the fourth genome of an electric fish and the third well-annotated genome for Osteoglossomorpha, enabling us to compare gene family evolution among major teleost lineages. Osteoglossomorpha appear to exhibit rapid gene family evolution, with more gene family expansions than contractions. The curated Kv1 gene family showed seven gene clusters, which is more than in other analyzed fish genomes outside Osteoglossomorpha. The KCNA7a, encoding for a potassium channel central for EOD production and modulation, is tandemly duplicated which may related to the diverse EOD observed among Campylomormyrus species.
Solid organ transplant (SOT) recipients receive therapeutic immunosuppression that compromises their immune response to infections and vaccines. For this reason, SOT patients have a high risk of developing severe coronavirus disease 2019 (COVID-19) and an increased risk of death from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Moreover, the efficiency of immunotherapies and vaccines is reduced due to the constant immunosuppression in this patient group. Here, we propose adoptive transfer of SARS-CoV-2-specific T cells made resistant to a common immunosuppressant, tacrolimus, for optimized performance in the immunosuppressed patient. Using a ribonucleoprotein approach of CRISPR-Cas9 technology, we have generated tacrolimus-resistant SARS-CoV-2-specific T cell products from convalescent donors and demonstrate their specificity and function through characterizations at the single-cell level, including flow cytometry, single-cell RNA (scRNA) Cellular Indexing of Transcriptomes and Epitopes (CITE), and T cell receptor (TCR) sequencing analyses. Based on the promising results, we aim for clinical validation of this approach in transplant recipients. Additionally, we propose a combinatory approach with tacrolimus, to prevent an overshooting immune response manifested as bystander T cell activation in the setting of severe COVID-19 immunopathology, and tacrolimus-resistant SARS-CoV-2-specific T cell products, allowing for efficient clearance of viral infection. Our strategy has the potential to prevent severe COVID-19 courses in SOT or autoimmunity settings and to prevent immunopathology while providing viral clearance in severe non-transplant COVID-19 cases.
Progressive habitat fragmentation threatens plant species with narrow habitat requirements. While local environmental conditions define population growth rates and recruitment success at the patch level, dispersal is critical for population viability at the landscape scale. Identifying the dynamics of plant meta-populations is often confounded by the uncertainty about soil-stored population compartments. We combined a landscape-scale assessment of an amphibious plant's population structure with measurements of dispersal complexity in time to track dispersal and putative shifts in functional connectivity. Using 13 microsatellite markers, we analyzed the genetic structure of extant Oenanthe aquatica populations and their soil seed banks in a kettle hole system to uncover hidden connectivity among populations in time and space. Considerable spatial genetic structure and isolation-by-distance suggest limited gene flow between sites. Spatial isolation and patch size showed minor effects on genetic diversity. Genetic similarity found among extant populations and their seed banks suggests increased local recruitment, despite some evidence of migration and recent colonization. Results indicate stepping-stone dispersal across adjacent populations. Among permanent and ephemeral demes the resulting meta-population demography could be determined by source-sink dynamics. Overall, these spatiotemporal connectivity patterns support mainland-island dynamics in our system, highlighting the importance of persistent seed banks as enduring sources of genetic diversity.
Metabolic engineering of microalgae offers a promising solution for sustainable biofuel production, and rational design of engineering strategies can be improved by employing metabolic models that integrate enzyme turnover numbers. However, the coverage of turnover numbers for Chlamydomonas reinhardtii, a model eukaryotic microalga accessible to metabolic engineering, is 17-fold smaller compared to the heterotrophic cell factory Saccharomyces cerevisiae. Here we generate quantitative protein abundance data of Chlamydomonas covering 2337 to 3708 proteins in various growth conditions to estimate in vivo maximum apparent turnover numbers. Using constrained-based modeling we provide proxies for in vivo turnover numbers of 568 reactions, representing a 10-fold increase over the in vitro data for Chlamydomonas. Integration of the in vivo estimates instead of in vitro values in a metabolic model of Chlamydomonas improved the accuracy of enzyme usage predictions. Our results help in extending the knowledge on uncharacterized enzymes and improve biotechnological applications of Chlamydomonas.
Spatial and temporal variation in perceived predation risk is an important determinant of movement and foraging activity of animals. Foraging in this landscape of fear, individuals need to decide where and when to move, and what resources to choose. Foraging theory predicts the outcome of these decisions based on energetic trade-offs, but complex interactions between perceived predation risk and preferences of foragers for certain functional traits of their resources are rarely considered. Here, we studied the interactive effects of perceived predation risk on food trait preferences and foraging behavior in bank voles (Myodes glareolus) in experimental landscapes. Individuals (n = 19) were subjected for periods of 24 h to two extreme, risk-uniform landscapes (either risky or safe), containing 25 discrete food patches, filled with seeds of four plant species in even amounts. Seeds varied in functional traits: size, nutrients, and shape. We evaluated whether and how risk modifies forager preference for functional traits. We also investigated whether perceived risk and distance from shelter affected giving-up density (GUD), time in patches, and number of patch visits. In safe landscapes, individuals increased time spent in patches, lowered GUD and visited distant patches more often compared to risky landscapes. Individuals preferred bigger seeds independent of risk, but in the safe treatment they preferred fat-rich over carb-rich seeds. Thus, higher densities of resource levels remained in risky landscapes, while in safe landscapes resource density was lower and less diverse due to selective foraging. Our results suggest that the interaction of perceived risk and dietary preference adds an additional layer to the cascading effects of a landscape of fear which affects biodiversity at resource level.
Protein-protein-interactions play an important role in many cellular functions. Quantitative non-invasive techniques are applied in living cells to evaluate such interactions, thereby providing a broader understanding of complex biological processes. Fluorescence fluctuation spectroscopy describes a group of quantitative microscopy approaches for the characterization of molecular interactions at single cell resolution. Through the obtained molecular brightness, it is possible to determine the oligomeric state of proteins. This is usually achieved by fusing fluorescent proteins (FPs) to the protein of interest. Recently, the number of novel green FPs has increased, with consequent improvements to the quality of fluctuation-based measurements. The photophysical behavior of FPs is influenced by multiple factors (including photobleaching, protonation-induced "blinking" and long-lived dark states). Assessing these factors is critical for selecting the appropriate fluorescent tag for live cell imaging applications. In this work, we focus on novel green FPs that are extensively used in live cell imaging. A systematic performance comparison of several green FPs in living cells under different pH conditions using Number & Brightness (N & B) analysis and scanning fluorescence correlation spectroscopy was performed. Our results show that the new FP Gamillus exhibits higher brightness at the cost of lower photostability and fluorescence probability (pf), especially at lower pH. mGreenLantern, on the other hand, thanks to a very high pf, is best suited for multimerization quantification at neutral pH. At lower pH, mEGFP remains apparently the best choice for multimerization investigation. These guidelines provide the information needed to plan quantitative fluorescence microscopy involving these FPs, both for general imaging or for protein-protein-interactions quantification via fluorescence fluctuation-based methods.
All plant cells are encased in primary cell walls that determine plant morphology, but also protect the cells against the environment. Certain cells also produce a secondary wall that supports mechanically demanding processes, such as maintaining plant body stature and water transport inside plants. Both these walls are primarily composed of polysaccharides that are arranged in certain patterns to support cell functions. A key requisite for patterned cell walls is the arrangement of cortical microtubules that may direct the delivery of wall polymers and/or cell wall producing enzymes to certain plasma membrane locations. Microtubules also steer the synthesis of cellulose-the load-bearing structure in cell walls-at the plasma membrane. The organization and behaviour of the microtubule array are thus of fundamental importance to cell wall patterns. These aspects are controlled by the coordinated effort of small GTPases that probably coordinate a Turing's reaction-diffusion mechanism to drive microtubule patterns. Here, we give an overview on how wall patterns form in the water-transporting xylem vessels of plants. We discuss systems that have been used to dissect mechanisms that underpin the xylem wall patterns, emphasizing the VND6 and VND7 inducible systems, and outline challenges that lay ahead in this field.
The oil palm (Elaeis guineensis Jacq.) produces a large amount of oil from the fruit. However, increasing the oil production in this fruit is still challenging. A recent study has shown that starch metabolism is essential for oil synthesis in fruit-producing species. Therefore, the transcriptomic analysis by RNA-seq was performed to observe gene expression alteration related to starch metabolism genes throughout the maturity stages of oil palm fruit with different oil yields. Gene expression profiles were examined with three different oil yields group (low, medium, and high) at six fruit development phases (4, 8, 12, 16, 20, and 22 weeks after pollination). We successfully identified and analyzed differentially expressed genes in oil palm mesocarps during development. The results showed that the transcriptome profile for each developmental phase was unique. Sucrose flux to the mesocarp tissue, rapid starch turnover, and high glycolytic activity have been identified as critical factors for oil production in oil palms. For starch metabolism and the glycolytic pathway, we identified specific gene expressions of enzyme isoforms (isozymes) that correlated with oil production, which may determine the oil content. This study provides valuable information for creating new high-oil-yielding palm varieties via breeding programs or genome editing approaches.
Keeping cool on hot days
(2023)
Long-lived organisms are likely to respond to a rapidly changing climate with behavioral flexibility. Animals inhabiting the arid parts of southern Africa face a particularly rapid rise in temperature which in combination with food and water scarcity places substantial constraints on the ability of animals to tolerate heat. We investigated how three species of African antelope-springbok Antidorcas marsupialis, kudu Tragelaphus strepsiceros and eland T. oryx-differing in body size, habitat preference and movement ecology, change their activity in response to extreme heat in an arid savanna. Serving as a proxy for activity, dynamic body acceleration data recorded every five minutes were analyzed for seven to eight individuals per species for the three hottest months of the year. Activity responses to heat during the hottest time of day (the afternoons) were investigated and diel activity patterns were compared between hot and cool days. Springbok, which prefer open habitat, are highly mobile and the smallest of the species studied, showed the greatest decrease in activity with rising temperature. Furthermore, springbok showed reduced mean activity over the 24 h cycle on hot days compared to cool days. Large-bodied eland seemed less affected by afternoon heat than springbok. While eland also reduced diurnal activity on hot days compared to cool days, they compensated for this by increasing nocturnal activity, possibly because their predation risk is lower. Kudu, which are comparatively sedentary and typically occupy shady habitat, seemed least affected during the hottest time of day and showed no appreciable difference in diel activity patterns between hot and cool days. The interplay between habitat preference, body size, movement patterns, and other factors seems complex and even sub-lethal levels of heat stress have been shown to impact an animal's long-term survival and reproduction. Thus, differing heat tolerances among species could result in a shift in the composition of African herbivore communities as temperatures continue to rise, with significant implications for economically important wildlife-based land use and conservation.
Starch has been a convenient, economically important polymer with substantial applications in the food and processing industry. However, native starches present restricted applications, which hinder their industrial usage. Therefore, modification of starch is carried out to augment the positive characteristics and eliminate the limitations of the native starches. Modifications of starch can result in generating novel polymers with numerous functional and value-added properties that suit the needs of the industry. Here, we summarize the possible starch modifications in planta and outside the plant system (physical, chemical, and enzymatic) and their corresponding applications. In addition, this review will highlight the implications of each starch property adjustment.
Genomic and epigenomic determinants of heat stress-induced transcriptional memory in Arabidopsis
(2023)
Background
Transcriptional regulation is a key aspect of environmental stress responses. Heat stress induces transcriptional memory, i.e., sustained induction or enhanced re-induction of transcription, that allows plants to respond more efficiently to a recurrent HS. In light of more frequent temperature extremes due to climate change, improving heat tolerance in crop plants is an important breeding goal. However, not all heat stress-inducible genes show transcriptional memory, and it is unclear what distinguishes memory from non-memory genes. To address this issue and understand the genome and epigenome architecture of transcriptional memory after heat stress, we identify the global target genes of two key memory heat shock transcription factors, HSFA2 and HSFA3, using time course ChIP-seq.
Results
HSFA2 and HSFA3 show near identical binding patterns. In vitro and in vivo binding strength is highly correlated, indicating the importance of DNA sequence elements. In particular, genes with transcriptional memory are strongly enriched for a tripartite heat shock element, and are hallmarked by several features: low expression levels in the absence of heat stress, accessible chromatin environment, and heat stress-induced enrichment of H3K4 trimethylation. These results are confirmed by an orthogonal transcriptomic data set using both de novo clustering and an established definition of memory genes.
Conclusions
Our findings provide an integrated view of HSF-dependent transcriptional memory and shed light on its sequence and chromatin determinants, enabling the prediction and engineering of genes with transcriptional memory behavior.
Quinoa (Chenopodium quinoa Willd.) is an herbaceous annual crop of the amaranth family (Amaranthaceae). It is increasingly cultivated for its nutritious grains, which are rich in protein and essential amino acids, lipids, and minerals. Quinoa exhibits a high tolerance towards various abiotic stresses including drought and salinity, which supports its agricultural cultivation under climate change conditions. The use of quinoa grains is compromised by anti-nutritional saponins, a terpenoid class of secondary metabolites deposited in the seed coat; their removal before consumption requires extensive washing, an economically and environmentally unfavorable process; or their accumulation can be reduced through breeding. In this study, we analyzed the seed metabolomes, including amino acids, fatty acids, and saponins, from 471 quinoa cultivars, including two related species, by liquid chromatography - mass spectrometry. Additionally, we determined a large number of agronomic traits including biomass, flowering time, and seed yield. The results revealed considerable diversity between genotypes and provide a knowledge base for future breeding or genome editing of quinoa.
The heat is on
(2023)
Climate conditions severely impact the activity and, consequently, the fitness of wildlife species across the globe. Wildlife can respond to new climatic conditions, but the pace of human-induced change limits opportunities for adaptation or migration. Thus, how these changes affect behavior, movement patterns, and activity levels remains unclear. In this study, we investigate how extreme weather conditions affect the activity of European hares (Lepus europaeus) during their peak reproduction period. When hares must additionally invest energy in mating, prevailing against competitors, or lactating, we investigated their sensitivities to rising temperatures, wind speed, and humidity. To quantify their activity, we used the overall dynamic body acceleration (ODBA) calculated from tri-axial acceleration measurements of 33 GPS-collared hares. Our analysis revealed that temperature, humidity, and wind speed are important in explaining changes in activity, with a strong response for high temperatures above 25 & DEG;C and the highest change in activity during temperature extremes of over 35 & DEG;C during their inactive period. Further, we found a non-linear relationship between temperature and activity and an interaction of activity changes between day and night. Activity increased at higher temperatures during the inactive period (day) and decreased during the active period (night). This decrease was strongest during hot tropical nights. At a stage of life when mammals such as hares must substantially invest in reproduction, the sensitivity of females to extreme temperatures was particularly pronounced. Similarly, both sexes increased their activity at high humidity levels during the day and low wind speeds, irrespective of the time of day, while the effect of humidity was stronger for males. Our findings highlight the importance of understanding the complex relationships between extreme weather conditions and mammal behavior, critical for conservation and management. With ongoing climate change, extreme weather events such as heat waves and heavy rainfall are predicted to occur more often and last longer. These events will directly impact the fitness of hares and other wildlife species and hence the population dynamics of already declining populations across Europe.
Spatially explicit knowledge on grassland extent and management is critical to understand and monitor the impact of grassland use intensity on ecosystem services and biodiversity. While regional studies allow detailed insights into land use and ecosystem service interactions, information on a national scale can aid biodiversity assessments. However, for most European countries this information is not yet widely available. We used an analysis-ready-data cube that contains dense time series of co-registered Sentinel-2 and Landsat 8 data, covering the extent of Germany. We propose an algorithm that detects mowing events in the time series based on residuals from an assumed undisturbed phenology, as an indicator of grassland use intensity. A self-adaptive ruleset enabled to account for regional variations in land surface phenology and non-stationary time series on a pixelbasis. We mapped mowing events for the years from 2017 to 2020 for permanent grassland areas in Germany. The results were validated on a pixel level in four of the main natural regions in Germany based on reported mowing events for a total of 92 (2018) and 78 (2019) grassland parcels. Results for 2020 were evaluated with combined time series of Landsat, Sentinel-2 and PlanetScope data. The mean absolute percentage error between detected and reported mowing events was on average 40% (2018), 36% (2019) and 35% (2020). Mowing events were on average detected 11 days (2018), 7 days (2019) and 6 days (2020) after the reported mowing. Performance measures varied between the different regions of Germany, and lower accuracies were found in areas that are revisited less frequently by Sentinel-2. Thus, we assessed the influence of data availability and found that the detection of mowing events was less influenced by data availability when at least 16 cloud-free observations were available in the grassland season. Still, the distribution of available observations throughout the season appeared to be critical. On a national scale our results revealed overall higher shares of less intensively mown grasslands and smaller shares of highly intensively managed grasslands. Hotspots of the latter were identified in the alpine foreland in Southern Germany as well as in the lowlands in the Northwest of Germany. While these patterns were stable throughout the years, the results revealed a tendency to lower management intensity in the extremely dry year 2018. Our results emphasize the ability of the approach to map the intensity of grassland management throughout large areas despite variations in data availability and environmental conditions.
Pre-exposing (priming) plants to mild, non-lethal elevated temperature improves their tolerance to a later higher-temperature stress (triggering stimulus), which is of great ecological importance. 'Thermomemory' is maintaining this tolerance for an extended period of time. NAM/ATAF1/2/ CUC2 (NAC) proteins are plant-specific transcription factors (TFs) that modulate responses to abiotic stresses, including heat stress (HS). Here, we investigated the potential role of NACs for thermomemory. We determined the expression of 104 Ara bidopsis NAC genes after priming and triggering heat stimuli, and found ATAF1 expression is strongly induced right after priming and declines below control levels thereafter during thermorecovery. Knockout mutants of ATAF1 show better thermomemory than wild type, revealing a negative regulatory role. Differential expression analyses of RNA-seq data from ATAF1 overexpressor, ataf1 mutant and wild-type plants after heat priming revealed five genes that might be priming-associated direct targets of ATAF1: AT2G31260 (ATG9), AT2G41640 (GT61), AT3G44990 (XTH31), AT4G27720 and AT3G23540. Based on co-expression analyses applied to the aforementioned RNA-seq profiles, we identified ANAC055 to be transcriptionally co-regulated with ATAF1. Like atafl, anac055 mutants show improved thermomemory, revealing a potential co-control of both NACTFs over thermomemory. Our data reveals a core importance of two NAC transcription factors, ATAF1 and ANAC055, for thermomemory.
PRI: Re-analysis of a public mass cytometry dataset reveals patterns of effective tumor treatments
(2022)
Recently, mass cytometry has enabled quantification of up to 50 parameters for millions of cells per sample. It remains a challenge to analyze such high-dimensional data to exploit the richness of the inherent information, even though many valuable new analysis tools have already been developed. We propose a novel algorithm "pattern recognition of immune cells (PRI)" to tackle these high-dimensional protein combinations in the data. PRI is a tool for the analysis and visualization of cytometry data based on a three or more-parametric binning approach, feature engineering of bin properties of multivariate cell data, and a pseudo-multiparametric visualization. Using a publicly available mass cytometry dataset, we proved that reproducible feature engineering and intuitive understanding of the generated bin plots are helpful hallmarks for re-analysis with PRI. In the CD4(+)T cell population analyzed, PRI revealed two bin-plot patterns (CD90/CD44/CD86 and CD90/CD44/CD27) and 20 bin plot features for threshold-independent classification of mice concerning ineffective and effective tumor treatment. In addition, PRI mapped cell subsets regarding co-expression of the proliferation marker Ki67 with two major transcription factors and further delineated a specific Th1 cell subset. All these results demonstrate the added insights that can be obtained using the non-cluster-based tool PRI for re-analyses of high-dimensional cytometric data.
The terrestrial ecosystem in the Yellow River Source Area (YRSA) is sensitive to climate change and human impacts, although past vegetation change and the degree of human disturbance are still largely unknown. A 170-cm-long sediment core covering the last 7,400 years was collected from Lake Xingxinghai (XXH) in the YRSA. Pollen, together with a series of other environmental proxies (including grain size, total organic carbon (TOC) and carbonate content), were analysed to explore past vegetation and environmental changes for the YRSA. Dominant and common pollen components-Cyperaceae, Poaceae, Artemisia, Chenopodiaceae and Asteraceae-are stable throughout the last 7,400 years. Slight vegetation change is inferred from an increasing trend of Cyperaceae and decreasing trend of Poaceae, suggesting that alpine steppe was replaced by alpine meadow at ca. 3.5 ka cal bp. The vegetation transformation indicates a generally wetter climate during the middle and late Holocene, which is supported by increased amounts of TOC and Pediastrum (representing high water-level) and is consistent with previous past climate records from the north-eastern Tibetan Plateau. Our results find no evidence of human impact on the regional vegetation surrounding XXH, hence we conclude the vegetation change likely reflects the regional climate signal.
Wildfires play an essential role in the ecology of boreal forests.
In eastern Siberia, fire activity has been increasing in recent years, challenging the livelihoods of local communities. Intensifying fire regimes also increase disturbance pressure on the boreal forests, which currently protect the permafrost beneath from accelerated degradation.
However, long-term relationships between changes in fire regime and forest structure remain largely unknown.
We assess past fire-vegetation feedbacks using sedimentary proxy records from Lake Satagay, Central Yakutia, Siberia, covering the past c. 10,800 years.
Results from macroscopic and microscopic charcoal analyses indicate high amounts of burnt biomass during the Early Holocene, and that the present-day, low-severity surface fire regime has been in place since c. 4,500 years before present.
A pollen-based quantitative reconstruction of vegetation cover and a terrestrial plant record based on sedimentary ancient DNA metabarcoding suggest a pronounced shift in forest structure toward the Late Holocene.
Whereas the Early Holocene was characterized by postglacial open larch-birch woodlands, forest structure changed toward the modern, mixed larch-dominated closed-canopy forest during the Mid-Holocene.
We propose a potential relationship between open woodlands and high amounts of burnt biomass, as well as a mediating effect of dense larch forest on the climate-driven intensification of fire regimes.
Considering the anticipated increase in forest disturbances (droughts, insect invasions, and wildfires), higher tree mortality may force the modern state of the forest to shift toward an open woodland state comparable to the Early Holocene.
Such a shift in forest structure may result in a positive feedback on currently intensifying wildfires.
These new long-term data improve our understanding of millennial-scale fire regime changes and their relationships to changes of vegetation in Central Yakutia, where the local population is already being confronted with intensifying wildfire seasons.
Hantaviruses are enveloped viruses that possess a tri-segmented, negative-sense RNA genome.
The viral S-segment encodes the multifunctional nucleocapsid protein (N), which is involved in genome packaging, intracellular protein transport, immunoregulation, and several other crucial processes during hantavirus infection.
In this study, we generated fluorescently tagged N protein constructs derived from Puumalavirus (PUUV), the dominant hantavirus species in Central, Northern, and Eastern Europe.
We comprehensively characterized this protein in the rodent cell line CHO-K1, monitoring the dynamics of N protein complex formation and investigating co-localization with host proteins as well as the viral glycoproteins Gc and Gn.
We observed formation of large, fibrillar PUUV N protein aggregates, rapidly coalescing from early punctate and spike-like assemblies.
Moreover, we found significant spatial correlation of N with vimentin, actin, and P-bodies but not with microtubules. N constructs also co-localized with Gn and Gc albeit not as strongly as the glycoproteins associated with each other.
Finally, we assessed oligomerization of N constructs, observing efficient and concentration-dependent multimerization, with complexes comprising more than 10 individual proteins.
Assessing the risk of yield loss in African drought-affected regions is key to identify feasible solutions for stable crop production. Recent studies have demonstrated that Copula-based probabilistic methods are well suited for such assessment owing to reasonably inferring important properties in terms of exceedance probability and joint dependence of different characterization. However, insufficient attention has been given to quantifying the probability of yield loss and determining the contribution of climatic factors. This study applies the Copula theory to describe the dependence between drought and crop yield anomalies for rainfed maize, millet, and sorghum crops in sub-Saharan Africa (SSA). The environmental policy integrated climate model, calibrated with Food and Agriculture Organization country-level yield data, was used to simulate yields across SSA (1980-2012). The results showed that the severity of yield loss due to drought had a higher magnitude than the severity of drought itself. Sensitivity analysis to identify factors contributing to drought and high-temperature stresses for all crops showed that the amount of precipitation during vegetation and grain filling was the main driver of crop yield loss, and the effect of temperature was stronger for sorghum than for maize and millet. The results demonstrate the added value of probabilistic methods for drought-impact assessment. For future studies, we recommend looking into factors influencing drought and high-temperature stresses as individual/concurrent climatic extremes.
Uncertainty in climate change impact studies for irrigated maize cropping systems in southern Spain
(2022)
This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability.
Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields.
The water allocation strategies were derived from historical records of farmer's allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014-2017).
By considering combinations of allocation strategies, the adjusted R-2 values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%).
However, under temperature increase scenarios, the contribution of crop model and cultivar choice to uncertainty in simulated yields were as important as irrigation strategy. This was partially due to different model structure in processes related to the temperature responses.
Our study calls for including information on irrigation strategies conducted by farmers to reduce the uncertainty in simulated yields at field scale.
The contribution of dead zooplankton biomass to carbon cycle in aquatic ecosystems is practically unknown. Using abundance data of zooplankton in water column and dead zooplankton in sediment traps in Lake Stechlin, an ecological-mathematical model was developed to simulate the abundance and sinking of zooplankton carcasses and predict the related release of labile organic matter (LOM) into the water column. We found species-specific differences in mortality rate of the dominant zooplankton: Daphnia cucullata, Bosmina coregoni and Diaphanosoma brachyurum (0.008, 0.129 and 0.020 day(-1), respectively) and differences in their carcass sinking velocities in metalimnion (and hypolimnion): 2.1 (7.64), 14.0 (19.5) and 1.1 (5.9) m day(-1), respectively. Our model simulating formation and degradation processes of dead zooplankton predicted a bimodal distribution of the released LOM: epilimnic and metalimnic peaks of comparable intensity, ca. 1 mg DW m(-3) day(-1). Maximum degradation of carcasses up to ca. 1.7 mg DW m(-3) day(-1) occurred in the density gradient zone of metalimnion. LOM released from zooplankton carcasses into the surrounding water may stimulate microbial activity and facilitate microbial degradation of more refractory organic matter; therefore, dead zooplankton are expected to be an integral part of water column carbon source/sink dynamics in stratified lakes.
A bacterial effector counteracts host autophagy by promoting degradation of an autophagy component
(2022)
Beyond its role in cellular homeostasis, autophagy plays anti- and promicrobial roles in host-microbe interactions, both in animals and plants.
One prominent role of antimicrobial autophagy is to degrade intracellular pathogens or microbial molecules, in a process termed xenophagy.
Consequently, microbes evolved mechanisms to hijack or modulate autophagy to escape elimination.
Although well-described in animals, the extent to which xenophagy contributes to plant-bacteria interactions remains unknown.
Here, we provide evidence that Xanthomonas campestris pv. vesicatoria (Xcv) suppresses host autophagy by utilizing type-III effector XopL. XopL interacts with and degrades the autophagy component SH3P2 via its E3 ligase activity to promote infection.
Intriguingly, XopL is targeted for degradation by defense-related selective autophagy mediated by NBR1/Joka2, revealing a complex antagonistic interplay between XopL and the host autophagy machinery.
Our results implicate plant antimicrobial autophagy in the depletion of a bacterial virulence factor and unravel an unprecedented pathogen strategy to counteract defense-related autophagy in plant-bacteria interactions.
Etmopteridae (lantern sharks) is the most species-rich family of sharks, comprising more than 50 species.
Many species are described from few individuals, and re-collection of specimens is often hindered by the remoteness of their sampling sites.
For taxonomic studies, comparative morphological analysis of type specimens housed in natural history collections has been the main source of evidence.
In contrast, DNA sequence information has rarely been used.
Most lantern shark collection specimens, including the types, were formalin fixed before long-term storage in ethanol solutions.
The DNA damage caused by both fixation and preservation of specimens has excluded these specimens from DNA sequence-based phylogenetic analyses so far.
However, recent advances in the field of ancient DNA have allowed recovery of wet-collection specimen DNA sequence data.
Here we analyse archival mitochondrial DNA sequences, obtained using ancient DNA approaches, of two wet-collection lantern shark paratype specimens, namely Etmopterus litvinovi and E. pycnolepis, for which the type series represent the only known individuals.
Target capture of mitochondrial markers from single-stranded DNA libraries allows for phylogenetic placement of both species.
Our results suggest synonymy of E. benchleyi with E. litvinovi but support the species status of E. pycnolepis. This revised taxonomy is helpful for future conservation and management efforts, as our results indicate a larger distribution range of E. litvinovi. This study further demonstrates the importance of wet-collection type specimens as genetic resource for taxonomic research.
Air chemistry is affected by the emission of biogenic volatile organic compounds (BVOCs), which originate from almost all plants in varying qualities and quantities. They also vary widely among different crops, an aspect that has been largely neglected in emission inventories. In particular, bioenergy-related species can emit mixtures of highly reactive compounds that have received little attention so far. For such species, long-term field observations of BVOC exchange from relevant crops covering different phenological phases are scarcely available. Therefore, we measured and modeled the emission of three prominent European bioenergy crops (maize, ryegrass, and oil-seed rape) for full rotations in north-eastern Germany. Using a proton transfer reaction-mass spectrometer combined with automatically moving large canopy chambers, we were able to quantify the characteristic seasonal BVOC flux dynamics of each crop species. The measured BVOC fluxes were used to parameterize and evaluate the BVOC emission module (JJv) of the physiology-oriented LandscapeDNDC model, which was enhanced to cover de novo emissions as well as those from plant storage pools. Parameters are defined for each compound individually. The model is used for simulating total compound-specific reactivity over several years and also to evaluate the importance of these emissions for air chemistry. We can demonstrate substantial differences between the investigated crops with oil-seed rape having 37-fold higher total annual emissions than maize. However, due to a higher chemical reactivity of the emitted blend in maize, potential impacts on atmospheric OH-chemistry are only 6-fold higher.