570 Biowissenschaften; Biologie
Refine
Has Fulltext
- no (157) (remove)
Year of publication
- 2021 (157) (remove)
Document Type
- Article (134)
- Doctoral Thesis (12)
- Part of Periodical (7)
- Conference Proceeding (4)
Is part of the Bibliography
- yes (157)
Keywords
- Arabidopsis thaliana (3)
- conservation (3)
- dispersal (3)
- evolution (3)
- machine learning (3)
- Bombina bombina (2)
- Dictyostelium (2)
- Lepus europaeus (2)
- Microcystis (2)
- Mitochondria (2)
Institute
- Institut für Biochemie und Biologie (95)
- Institut für Ernährungswissenschaft (16)
- Institut für Chemie (13)
- Institut für Physik und Astronomie (10)
- Institut für Geowissenschaften (7)
- Extern (6)
- Hasso-Plattner-Institut für Digital Engineering gGmbH (6)
- Institut für Umweltwissenschaften und Geographie (6)
- Fakultät für Gesundheitswissenschaften (5)
- Department Psychologie (2)
Genome-scale metabolic networks for model plants and crops in combination with approaches from the constraint-based modelling framework have been used to predict metabolic traits and design metabolic engineering strategies for their manipulation. With the advances in technologies to generate large-scale genotyping data from natural diversity panels and other populations, genome-wide association and genomic selection have emerged as statistical approaches to determine genetic variants associated with and predictive of traits. Here, we review recent advances in constraint-based approaches that integrate genetic variants in genome-scale metabolic models to characterize their effects on reaction fluxes. Since some of these approaches have been applied in organisms other than plants, we provide a critical assessment of their applicability particularly in crops. In addition, we further dissect the inferred effects of genetic variants with respect to reaction rate constants, abundances of enzymes, and concentrations of metabolites, as main determinants of reaction fluxes and relate them with their combined effects on complex traits, like growth. Through this systematic review, we also provide a roadmap for future research to increase the predictive power of statistical approaches by coupling them with mechanistic models of metabolism.
The objective of this work was to investigate the potential effect of cereal α-amylase/trypsin inhibitors (ATIs) on growth parameters and selective digestive enzymes of Tenebrio molitor L. larvae. The approach consisted of feeding the larvae with wheat, sorghum and rice meals containing different levels and composition of α-amylase/trypsin inhibitors. The developmental and biochemical characteristics of the larvae were assessed over feeding periods of 5 h, 5 days and 10 days, and the relative abundance of α-amylase and selected proteases in larvae were determined using liquid chromatography tandem mass spectrometry. Overall, weight gains ranged from 21% to 42% after five days of feeding. The larval death rate significantly increased in all groups after 10 days of feeding (p < 0.05), whereas the pupation rate was about 25% among larvae fed with rice (Oryza sativa L.) and Siyazan/Esperya wheat meals, and only 8% and 14% among those fed with Damougari and S35 sorghum meals. As determined using the Lowry method, the protein contents of the sodium phosphate extracts ranged from 7.80 ± 0.09 to 9.42 ± 0.19 mg/mL and those of the ammonium bicarbonate/urea reached 19.78 ± 0.16 to 37.47 ± 1.38 mg/mL. The total protein contents of the larvae according to the Kjeldahl method ranged from 44.0 and 49.9 g/100 g. The relative abundance of α-amylase, CLIP domain-containing serine protease, modular serine protease zymogen and C1 family cathepsin significantly decreased in the larvae, whereas dipeptidylpeptidase I and chymotrypsin increased within the first hours after feeding (p < 0.05). Trypsin content was found to be constant independently of time or feed material. Finally, based on the results we obtained, it was difficult to substantively draw conclusions on the likely effects of meal ATI composition on larval developmental characteristics, but their effects on the digestive enzyme expression remain relevant.
An amperometric trimethylamine N-oxide (TMAO) biosensor is reported, where TMAO reductase (TorA) and glucose oxidase (GOD) and catalase (Cat) were immobilized on the electrode surface, enabling measurements of mediated enzymatic TMAO reduction at low potential under ambient air conditions. The oxygen anti-interference membrane composed of GOD, Cat and polyvinyl alcohol (PVA) hydrogel, together with glucose concentration, was optimized until the O-2 reduction current of a Clark-type electrode was completely suppressed for at least 3 h. For the preparation of the TMAO biosensor, Escherichia coli TorA was purified under anaerobic conditions and immobilized on the surface of a carbon electrode and covered by the optimized O-2 scavenging membrane. The TMAO sensor operates at a potential of -0.8 V vs. Ag/AgCl (1 M KCl), where the reduction of methylviologen (MV) is recorded. The sensor signal depends linearly on TMAO concentrations between 2 mu M and 15 mM, with a sensitivity of 2.75 +/- 1.7 mu A/mM. The developed biosensor is characterized by a response time of about 33 s and an operational stability over 3 weeks. Furthermore, measurements of TMAO concentration were performed in 10% human serum, where the lowest detectable concentration is of 10 mu M TMAO.
Seed traits matter
(2021)
Although many plants are dispersed by wind and seeds can travel long distances across unsuitable matrix areas, a large proportion relies on co-evolved zoochorous seed dispersal to connect populations in isolated habitat islands. Particularly in agricultural landscapes, where remaining habitat patches are often very small and highly isolated, mobile linkers as zoochorous seed dispersers are critical for the population dynamics of numerous plant species. However, knowledge about the quali- or quantification of such mobile link processes, especially in agricultural landscapes, is still limited. In a controlled feeding experiment, we recorded the seed intake and germination success after complete digestion by the European brown hare (Lepus europaeus) and explored its mobile link potential as an endozoochoric seed disperser. Utilizing a suite of common, rare, and potentially invasive plant species, we disentangled the effects of seed morphological traits on germination success while controlling for phylogenetic relatedness. Further, we measured the landscape connectivity via hares in two contrasting agricultural landscapes (simple: few natural and semi-natural structures, large fields; complex: high amount of natural and semi-natural structures, small fields) using GPS-based movement data. With 34,710 seeds of 44 plant species fed, one of 200 seeds (0.51%) with seedlings of 33 species germinated from feces. Germination after complete digestion was positively related to denser seeds with comparatively small surface area and a relatively slender and elongated shape, suggesting that, for hares, the most critical seed characteristics for successful endozoochorous seed dispersal minimize exposure of the seed to the stomach and the associated digestive system. Furthermore, we could show that a hare's retention time is long enough to interconnect different habitats, especially grasslands and fields. Thus, besides other seed dispersal mechanisms, this most likely allows hares to act as effective mobile linkers contributing to ecosystem stability in times of agricultural intensification, not only in complex but also in simple landscapes.
Seed traits matter
(2021)
Although many plants are dispersed by wind and seeds can travel long distances across unsuitable matrix areas, a large proportion relies on co-evolved zoochorous seed dispersal to connect populations in isolated habitat islands. Particularly in agricultural landscapes, where remaining habitat patches are often very small and highly isolated, mobile linkers as zoochorous seed dispersers are critical for the population dynamics of numerous plant species. However, knowledge about the quali- or quantification of such mobile link processes, especially in agricultural landscapes, is still limited. In a controlled feeding experiment, we recorded the seed intake and germination success after complete digestion by the European brown hare (Lepus europaeus) and explored its mobile link potential as an endozoochoric seed disperser. Utilizing a suite of common, rare, and potentially invasive plant species, we disentangled the effects of seed morphological traits on germination success while controlling for phylogenetic relatedness. Further, we measured the landscape connectivity via hares in two contrasting agricultural landscapes (simple: few natural and semi-natural structures, large fields; complex: high amount of natural and semi-natural structures, small fields) using GPS-based movement data. With 34,710 seeds of 44 plant species fed, one of 200 seeds (0.51%) with seedlings of 33 species germinated from feces. Germination after complete digestion was positively related to denser seeds with comparatively small surface area and a relatively slender and elongated shape, suggesting that, for hares, the most critical seed characteristics for successful endozoochorous seed dispersal minimize exposure of the seed to the stomach and the associated digestive system. Furthermore, we could show that a hare's retention time is long enough to interconnect different habitats, especially grasslands and fields. Thus, besides other seed dispersal mechanisms, this most likely allows hares to act as effective mobile linkers contributing to ecosystem stability in times of agricultural intensification, not only in complex but also in simple landscapes.
Rapid screening of infected people plays a crucial role in interrupting infection chains. However, the current methods for identification of bacteria are very tedious and labor intense. Fast on-site screening for pathogens based on volatile organic compounds (VOCs) by ion mobility spectrometry (IMS) could help to differentiate between healthy and potentially infected subjects. As a first step towards this, the feasibility of differentiating between seven different bacteria including resistant strains was assessed using IMS coupled to multicapillary columns (MCC-IMS). The headspace above bacterial cultures was directly drawn and analyzed by MCC-IMS after 90 min of incubation. A cluster analysis software and statistical methods were applied to select discriminative VOC clusters. As a result, 63 VOC clusters were identified, enabling the differentiation between all investigated bacterial strains using canonical discriminant analysis. These 63 clusters were reduced to 7 discriminative VOC clusters by constructing a hierarchical classification tree. Using this tree, all bacteria including resistant strains could be classified with an AUC of 1.0 by receiver-operating characteristic analysis. In conclusion, MCC-IMS is able to differentiate the tested bacterial species, even the non-resistant and their corresponding resistant strains, based on VOC patterns after 90 min of cultivation. Although this result is very promising, in vivo studies need to be performed to investigate if this technology is able to also classify clinical samples. With a short analysis time of 5 min, MCC-IMS is quite attractive for a rapid screening for possible infections in various locations from hospitals to airports. Key Points center dot Differentiation of bacteria by MCC-IMS is shown after 90-min cultivation. center dot Non-resistant and resistant strains can be distinguished. center dot Classification of bacteria is possible based on metabolic features.
While habitat loss is a known key driver of biodiversity decline, the impact of other landscape properties, such as patch isolation, is far less clear. When patch isolation is low, species may benefit from a broader range of foraging opportunities, but are at the same time adversely affected by higher predation pressure from mobile predators. Although previous approaches have successfully linked such effects to biodiversity, their impact on local and metapopulation dynamics has largely been ignored. Since population dynamics may also be affected by environmental disturbances that temporally change the degree of patch isolation, such as periodic changes in habitat availability, accurate assessment of its link with isolation is highly challenging. To analyze the effect of patch isolation on the population dynamics on different spatial scales, we simulate a three-species meta-food chain on complex networks of habitat patches and assess the average variability of local populations and metapopulations, as well as the level of synchronization among patches. To evaluate the impact of periodic environmental disturbances, we contrast simulations of static landscapes with simulations of dynamic landscapes in which 30 percent of the patches periodically become unavailable as habitat. We find that increasing mean patch isolation often leads to more asynchronous population dynamics, depending on the parameterization of the food chain. However, local population variability also increases due to indirect effects of increased dispersal mortality at high mean patch isolation, consequently destabilizing metapopulation dynamics and increasing extinction risk. In dynamic landscapes, periodic changes of patch availability on a timescale much slower than ecological interactions often fully synchronize the dynamics. Further, these changes not only increase the variability of local populations and metapopulations, but also mostly overrule the effects of mean patch isolation. This may explain the often small and inconclusive impact of mean patch isolation in natural ecosystems.
Objective
The Caribbean is an important global biodiversity hotspot. Adaptive radiations there lead to many speciation events within a limited period and hence are particularly prominent biodiversity generators. A prime example are freshwater fish of the genus Limia, endemic to the Greater Antilles. Within Hispaniola, nine species have been described from a single isolated site, Lake Miragoâne, pointing towards extraordinary sympatric speciation. This study examines the evolutionary history of the Limia species in Lake Miragoâne, relative to their congeners throughout the Caribbean.
Results
For 12 Limia species, we obtained almost complete sequences of the mitochondrial cytochrome b gene, a well-established marker for lower-level taxonomic relationships. We included sequences of six further Limia species from GenBank (total N = 18 species). Our phylogenies are in concordance with other published phylogenies of Limia. There is strong support that the species found in Lake Miragoâne in Haiti are monophyletic, confirming a recent local radiation. Within Lake Miragoâne, speciation is likely extremely recent, leading to incomplete lineage sorting in the mtDNA. Future studies using multiple unlinked genetic markers are needed to disentangle the relationships within the Lake Miragoâne clade.
Indolactam alkaloids are activators of protein kinase C (PKC) and are of pharmacological interest for the treatment of pathologies involving PKC dysregulation. The marine cyanobacterial nonribosomal peptide synthetase (NRPS) pathway for lyngbyatoxin biosynthesis, which we previously expressed in E. coli, was studied for its amenability towards the biosynthesis of indolactam variants. Modification of culture conditions for our E. coli heterologous expression host and analysis of pathway products suggested the native lyngbyatoxin pathway NRPS does possess a degree of relaxed specificity. Site-directed mutagenesis of two positions within the adenylation domain (A-domain) substrate-binding pocket was performed, resulting in an alteration of substrate preference between valine, isoleucine, and leucine. We observed relative congruence of in vitro substrate activation by the LtxA NRPS to in vivo product formation. While there was a preference for isoleucine over leucine, the substitution of alternative tailoring domains may unveil the true in vivo effects of the mutations introduced herein.
The Upper Indus Basin (UIB), which covers a wide range of climatic and topographic settings, provides an ideal venue to explore the relationship between climate and topography. While the distribution of snow and glaciers is spatially and temporally heterogeneous, there exist regions with similar elevation-snow relationships. In this work, we construct elevation-binned snow-cover statistics to analyze 3415 watersheds and 7357 glaciers in the UIB region. We group both glaciers and watersheds using a hierarchical clustering approach and find that (1) watershed clusters mirror large-scale moisture transport patterns and (2) are highly dependent on median watershed elevation. (3) Glacier clusters are spatially heterogeneous and are less strongly controlled by elevation, but rather by local topographic parameters that modify solar insolation. Our clustering approach allows us to clearly define self-similar snow-topographic regions. Eastern watersheds in the UIB show a steep snow cover-elevation relationship whereas watersheds in the central and western UIB have moderately sloped relationships, but cluster in distinct groups. We highlight this snow-cover-topographic transition zone and argue that these watersheds have different hydrologic responses than other regions. Our hierarchical clustering approach provides a potential new framework to use in defining climatic zones in the cyrosphere based on empirical data.
We consider an array of nonlocally coupled oscillators on a ring, which for equally spaced units possesses a Kuramoto-Battogtokh chimera regime and a synchronous state. We demonstrate that disorder in oscillators positions leads to a transition from the synchronous to the chimera state. For a static (quenched) disorder we find that the probability of synchrony survival depends on the number of particles, from nearly zero at small populations to one in the thermodynamic limit. Furthermore, we demonstrate how the synchrony gets destroyed for randomly (ballistically or diffusively) moving oscillators. We show that, depending on the number of oscillators, there are different scalings of the transition time with this number and the velocity of the units.
Groundwater arsenic contamination in the Bengal Delta Plain is an important public health issue
(2021)
There is a close association between human biology, epidemiology and public health. Exposure to toxic elements is one area of such associations and global concerns. The Bengal Delta Plain (BDP) is a region where contamination of ground water by arsenic has assumed epidemic proportions. Apart from dermatological manifestations, chronic exposure to arsenic causes a heavy toll through several carcinogenic and non-carcinogenic disorders. This article provides a global overview of groundwater arsenic contamination in the BDP region, especially the sources, speciation, and mobility of arsenic, and critically reviews the effects of arsenic on human health. The present review also provides a summary of comprehensive knowledge on various measures required for mitigation and social consequences of the problem of arsenic contaminated groundwater in the BDP region.
Combining high hydrophilicity with charge neutrality, polyzwitterions are intensely explored for their high biocompatibility and low-fouling properties. Recent reports indicated that in addition to charge neutrality, the zwitterion's segmental dipole orientation is an important factor for interacting with the environment. Accordingly, a series of polysulfobetaines with a novel architecture was designed, in which the cationic and anionic groups of the zwitterionic moiety are placed at equal distances from the backbone. They were investigated by in vitro biofouling assays, covering proteins of different charges and model marine organisms. All polyzwitterion coatings reduced the fouling effectively compared to model polymer surfaces of poly(butyl methacrylate), with a nearly equally good performance as the reference polybetaine poly(3-(N-(2-(methacryloyloxy)ethyl)-N,N-dimethylammonio)propanesulfonate). The specific fouling resistance depended on the detailed chemical structure of the polyzwitterions. Still, while clearly affecting the performance, the precise dipole orientation of the sulfobetaine group in the polyzwitterions seems overall to be only of secondary importance for their antifouling behavior.
Evidence of female preference for odor of distant over local males in a bat with female dispersal
(2021)
Geographic variation of sexually selected male traits is common in animals. Female choice also varies geographically and several studies found female preference for local males, which is assumed to lead to local adaptation and, therefore, increases fitness. As females are the nondispersing sex in most mammalian taxa, this preference for local males might be explained by the learning of male characteristics. Studies on the preference of females in female-dispersing species are lacking so far. To find out whether such females would also show preferences for local males, we conducted a study on greater sac-winged bats (Saccopteryx bilineata), a species where females disperse and males stay in their natal colony. Male greater sac-winged bats possess a wing pouch that is filled with odoriferous secretion and fanned toward females during courtship display. In a combination of chemical analysis and behavioral preference tests, we analyzed whether the composition of wing sac secretion varies between two geographically distinct populations (300 km), and whether females show a preference for local or distant male scent. Using gas chromatography, we found significant differences in the composition of the wing sac odors between the two geographically distinct populations. In addition, the behavioral preference experiments revealed that females of both populations preferred the scent of geographically distant males over local males. The wing sac odor might thus be used to guarantee optimal outbreeding when dispersing to a new colony. This is-to our knowledge-the first study on odor preference of females of a species with female-biased dispersal.
Stripe rust (Pst) is a major disease of wheat crops leading untreated to severe yield losses. The use of fungicides is often essential to control Pst when sudden outbreaks are imminent. Sensors capable of detecting Pst in wheat crops could optimize the use of fungicides and improve disease monitoring in high-throughput field phenotyping. Now, deep learning provides new tools for image recognition and may pave the way for new camera based sensors that can identify symptoms in early stages of a disease outbreak within the field. The aim of this study was to teach an image classifier to detect Pst symptoms in winter wheat canopies based on a deep residual neural network (ResNet). For this purpose, a large annotation database was created from images taken by a standard RGB camera that was mounted on a platform at a height of 2 m. Images were acquired while the platform was moved over a randomized field experiment with Pst-inoculated and Pst-free plots of winter wheat. The image classifier was trained with 224 x 224 px patches tiled from the original, unprocessed camera images. The image classifier was tested on different stages of the disease outbreak. At patch level the image classifier reached a total accuracy of 90%. To test the image classifier on image level, the image classifier was evaluated with a sliding window using a large striding length of 224 px allowing for fast test performance. At image level, the image classifier reached a total accuracy of 77%. Even in a stage with very low disease spreading (0.5%) at the very beginning of the Pst outbreak, a detection accuracy of 57% was obtained. Still in the initial phase of the Pst outbreak with 2 to 4% of Pst disease spreading, detection accuracy with 76% could be attained. With further optimizations, the image classifier could be implemented in embedded systems and deployed on drones, vehicles or scanning systems for fast mapping of Pst outbreaks.
Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows
(2021)
Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automated and reproducible approaches to extract quantitative morphological features from image sequences. Here, we introduce a theoretical framework and a computational method for obtaining smooth representations of the spatiotemporal contour dynamics from stacks of segmented microscopy images. Based on a Gaussian process regression we propose a one-parameter family of regularized contour flows that allows us to continuously track reference points (virtual markers) between successive cell contours. We use this approach to define a coordinate system on the moving cell boundary and to represent different local geometric quantities in this frame of reference. In particular, we introduce the local marker dispersion as a measure to identify localized membrane expansions and provide a fully automated way to extract the properties of such expansions, including their area and growth time. The methods are available as an open-source software package called AmoePy, a Python-based toolbox for analyzing amoeboid cell motility (based on time-lapse microscopy data), including a graphical user interface and detailed documentation. Due to the mathematical rigor of our framework, we envision it to be of use for the development of novel cell motility models. We mainly use experimental data of the social amoeba Dictyostelium discoideum to illustrate and validate our approach. <br /> Author summary Amoeboid motion is a crawling-like cell migration that plays an important key role in multiple biological processes such as wound healing and cancer metastasis. This type of cell motility results from expanding and simultaneously contracting parts of the cell membrane. From fluorescence images, we obtain a sequence of points, representing the cell membrane, for each time step. By using regression analysis on these sequences, we derive smooth representations, so-called contours, of the membrane. Since the number of measurements is discrete and often limited, the question is raised of how to link consecutive contours with each other. In this work, we present a novel mathematical framework in which these links are described by regularized flows allowing a certain degree of concentration or stretching of neighboring reference points on the same contour. This stretching rate, the so-called local dispersion, is used to identify expansions and contractions of the cell membrane providing a fully automated way of extracting properties of these cell shape changes. We applied our methods to time-lapse microscopy data of the social amoeba Dictyostelium discoideum.
Fatty acids are widely used to study trophic interactions in food web assemblages. Generally, it is assumed that there is a very small modification of fatty acids from one trophic step to another, making them suitable as trophic biomarkers. However, recent literature provides evidence that many fishes possess genes encoding enzymes with a role in bioconversion, thus the capability for bioconversion might be more widespread than previously assumed. Nonetheless, empirical evidence for biosynthesis occurring in natural populations remains scarce. In this study, we investigated different feeding types of perch (Perca fluviatilis) that are specialized on specific resources with different levels of highly unsaturated fatty acids (HUFAs), and analyzed the change between HUFA proportions in perch muscle tissue compared to their resources. Perch showed matching levels to their resources for EPA, but ARA and especially DHA were accumulated. Compound-specific stable isotope analyses helped us to identify the origin of HUFA carbon. Our results suggest that perch obtain a substantial amount of DHA via bioconversion when feeding on DHA-poor benthic resources. Thus, our data indicate the capability of bioconversion of HUFAs in a natural freshwater fish population.
Stable isotopes represent a unique approach to provide insights into the ecology of organisms. δ13C and δ15N have specifically been used to obtain information on the trophic ecology and food-web interactions. Trophic discrimination factors (TDF, Δ13C and Δ15N) describe the isotopic fractionation occurring from diet to consumer tissue, and these factors are critical for obtaining precise estimates within any application of δ13C and δ15N values. It is widely acknowledged that metabolism influences TDF, being responsible for different TDF between tissues of variable metabolic activity (e.g., liver vs. muscle tissue) or species body size (small vs. large). However, the connection between the variation of metabolism occurring within a single species during its ontogeny and TDF has rarely been considered. Here, we conducted a 9-month feeding experiment to report Δ13C and Δ15N of muscle and liver tissues for several weight classes of Eurasian perch (Perca fluviatilis), a widespread teleost often studied using stable isotopes, but without established TDF for feeding on a natural diet. In addition, we assessed the relationship between the standard metabolic rate (SMR) and TDF by measuring the oxygen consumption of the individuals. Our results showed a significant negative relationship of SMR with Δ13C, and a significant positive relationship of SMR with Δ15N of muscle tissue, but not with TDF of liver tissue. SMR varies inversely with size, which translated into a significantly different TDF of muscle tissue between size classes. In summary, our results emphasize the role of metabolism in shaping-specific TDF (i.e., Δ13C and Δ15N of muscle tissue) and especially highlight the substantial differences between individuals of different ontogenetic stages within a species. Our findings thus have direct implications for the use of stable isotope data and the applications of stable isotopes in food-web studies.
Plant cell biology
(2021)
PIN-FORMED (PIN) polar protein localization directs transport of the growth and developmental regulator auxin in plants. Once established after cytokinesis, PIN polarity requires maintenance. Now, direct interactions between PIN, MAB4/MEL and PID proteins suggest self-reinforced maintenance of PIN polarity through limiting lateral diffusion.
The Altiplano-Puna Plateau holds several shallow lakes, which are very sensitive to climate changes. This work is focused on a high-altitude lake system called Lagunas de Vilama (LVS), located in a complex climatic transition area with scarcity of continuous and homogeneous instrumental records. The objective of this study is to determine the regional spatial-temporal variability of precipitation and evaluate the seasonal and interannual lake responses. We use a lake-surfaces record derived from Landsat images to investigate links with regional precipitations and different climatic forcings. The results reveal that austral summer and autumn precipitations control the variability of the annual lake-surfaces. Also, we found intra-annual and interannual lags in the lake responses to precipitations, and identified several wet and dry stages. Our results show negative trends in precipitations and lake-surfaces, whose were strengthened by a shift to a warm phase of the Atlantic Multidecadal Oscillation in the 1990s. The El Nino Southern Oscillation, Pacific Decadal Oscillation, and Southern Annular Mode also exert a strong influence in the region. This study demonstrates that the variability of LVS lakes is strongly related to the South American Monsoon System dynamics and large-scale climate fordngs from the Pacific and Atlantic Oceans. This work provides novel indices which demonstrated to be good indicators of regional hydroclimatological variability for this region of South America.
Nature conservation and restoration in terrestrial ecosystems is often focused on increasing the numbers of megafauna, expecting them to have positive impacts on ecological self-regulation processes and biodiversity. In sub-Saharan Africa, conservation efforts also aspire to protect and enhance biodiversity with particular focus on elephants. However, elephant browsing carries the risk of woody biomass losses. In this context, little is known about how increasing elephant numbers affects carbon stocks in soils, including the subsoils. We hypothesized that (1) increasing numbers of elephants reduce tree biomass, and thus the amount of C stored therein, resulting (2) in a loss of soil organic carbon (SOC). If true, a negative carbon footprint could limit the sustainability of elephant conservation from a global carbon perspective. To test these hypotheses, we selected plots of low, medium, and high elephant densities in two national parks and adjacent conservancies in the Namibian component of the Kavango Zambezi Transfrontier Area (KAZA), and quantified carbon storage in both woody vegetation and soils (1 m). Analyses were supplemented by the assessment of soil carbon isotopic composition. We found that increasing elephant densities resulted in a loss of tree carbon storage by 6.4 t ha(-1). However, and in contrast to our second hypothesis, SOC stocks increased by 4.7 t ha(-1) with increasing elephant densities. These higher SOC stocks were mainly found in the topsoil (0-30 cm) and were largely due to the formation of SOC from woody biomass. A second carbon input source into the soils was megaherbivore dung, which contributed with 0.02-0.323 t C ha(-1) year(-1) to ecosystem carbon storage in the low and high elephant density plots, respectively. Consequently, increasing elephant density does not necessarily lead to a negative C footprint, as soil carbon sequestration and transient C storage in dung almost compensate for losses in tree biomass.
Three mitochondrial genomes of early-winged insects (Ephemeroptera: Baetidae and Leptophlebiidae)
(2021)
Mayflies (Ephemeroptera) are a semi-aquatic insect order with comparatively few genomic data available despite their phylogenetic position at the root of the winged-insects and possession of ancestral traits.
Here, we provide three mitochondrial genomes (mtgenomes) from representatives of the two most species-rich families, Baetis rutilocylindratus and Cloeon dipterum (Baetidae), and Habrophlebiodes zijinensis (Leptophlebiidae).
All mtgenomes had a complete set of 13 protein-coding genes and a conserved orientation except for two inverted tRNAs in H. zijinensis.
Phylogenetic reconstructions using 21 mayfly mtgenomes and representatives of seven additional orders recovered both Baetidae and Leptophlebiidae as well supported monophyletic clades, with Ephemeroptera as the sister-taxon to all other winged insects (i.e. Odonata and Neoptera).
Hydro Explorer
(2021)
Climatic changes and anthropogenic modifications of the river basin or river network have the potential to fundamentally alter river runoff. In the framework of this study, we aim to analyze and present historic changes in runoff timing and runoff seasonality observed at river gauges all over the world. In this regard, we develop the Hydro Explorer, an interactive web app, which enables the investigation of >7,000 daily resolution discharge time series from the Global Runoff Data Centre (GRDC). The interactive nature of the developed web app allows for a quick comparison of gauges, regions, methods, and time frames. We illustrate the available analytical tools by investigating changes in runoff timing and runoff seasonality in the Rhine River Basin. Since we provide the source code of the application, existing analytical approaches can be modified, new methods added, and the tool framework can be re-used to visualize other data sets.
Populations adapt to novel environmental conditions by genetic changes or phenotypic plasticity. Plastic responses are generally faster and can buffer fitness losses under variable conditions. Plasticity is typically modeled as random noise and linear reaction norms that assume simple one-to- one genotype–phenotype maps and no limits to the phenotypic response. Most studies on plasticity have focused on its effect on population viability. However, it is not clear, whether the advantage of plasticity depends solely on environmental fluctuations or also on the genetic and demographic properties (life histories) of populations. Here we present an individual-based model and study the relative importance of adaptive and nonadaptive plasticity for populations of sexual species with different life histories experiencing directional stochastic climate change. Environmental fluctuations were simulated using differentially autocorrelated climatic stochasticity or noise color, and scenarios of directiona
climate change. Nonadaptive plasticity was simulated as a random environmental effect on trait development, while adaptive plasticity as a linear, saturating, or sinusoidal reaction norm. The last two imposed limits to the plastic response and emphasized flexible interactions of the genotype with the environment. Interestingly, this assumption led to (a) smaller phenotypic than genotypic variance in the population (many-to- one genotype–phenotype map) and the coexistence of polymorphisms, and (b) the maintenance of higher genetic variation—compared to linear reaction norms and genetic determinism—even when the population was exposed to a constant environment for several generations. Limits to plasticity led to genetic accommodation, when costs were negligible, and to the appearance of cryptic variation when limits were exceeded. We found that adaptive plasticity promoted population persistence under red environmental noise and was particularly important for life histories with low fecundity. Populations produing more offspring could cope with environmental fluctuations solely by genetic changes or random plasticity, unless environmental change was too fast.
Settings Perspective
(2021)
Land-based climate mitigation measures have gained significant attention and importance in public and private sector climate policies. Building on previous studies, we refine and update the mitigation potentials for 20 land-based measures in >200 countries and five regions, comparing “bottom-up” sectoral estimates with integrated assessment models (IAMs). We also assess implementation feasibility at the country level. Cost-effective (available up to $100/tCO2eq) land-based mitigation is 8–13.8 GtCO2eq yr−1 between 2020 and 2050, with the bottom end of this range representing the IAM median and the upper end representing the sectoral estimate. The cost-effective sectoral estimate is about 40% of available technical potential and is in line with achieving a 1.5°C pathway in 2050. Compared to technical potentials, cost-effective estimates represent a more realistic and actionable target for policy. The cost-effective potential is approximately 50% from forests and other ecosystems, 35% from agriculture, and 15% from demand-side measures. The potential varies sixfold across the five regions assessed (0.75–4.8 GtCO2eq yr−1) and the top 15 countries account for about 60% of the global potential. Protection of forests and other ecosystems and demand-side measures present particularly high mitigation efficiency, high provision of co-benefits, and relatively lower costs. The feasibility assessment suggests that governance, economic investment, and socio-cultural conditions influence the likelihood that land-based mitigation potentials are realized. A substantial portion of potential (80%) is in developing countries and LDCs, where feasibility barriers are of greatest concern. Assisting countries to overcome barriers may result in significant quantities of near-term, low-cost mitigation while locally achieving important climate adaptation and development benefits. Opportunities among countries vary widely depending on types of land-based measures available, their potential co-benefits and risks, and their feasibility. Enhanced investments and country-specific plans that accommodate this complexity are urgently needed to realize the large global potential from improved land stewardship.
Background
Nicotine consumption during pregnancy and advanced maternal age are well known independent risk factors for poor pregnancy outcome and therefore serious public health problems.
Objectives
Considering the ongoing trend of delaying childbirth in our society, this study investigates potential additive effects of nicotine consumption during pregnancy and advanced maternal age on foetal growth.
Sample and Methods
In a medical record-based study, we analysed the impact of maternal age and smoking behaviour before and during pregnancy on newborn size among 4142 singleton births that took place in Vienna, Austria between 1990 and 1995.
Results
Birth weight (H=82.176, p<0.001), birth length (H=91.525, p<0.001) and head circumference (H=42.097, p<0.001) differed significantly according to maternal smoking behaviour. For birth weight, the adjusted mean differences between smokers and non-smokers increased from 101.8g for the < 18-year-old mothers to 254.8g for >35 year olds, with the respective values for birth length being 0.6 cm to 0.7cm, for head circumference from 0.3 cm to 0.6 cm.
Conclusion
Increasing maternal age amplified the negative effects of smoking during pregnancy on newborn parameters. Our findings identify older smoking mothers as a high-risk group which should be of special interest for public health systems.
Background
Over the last 20 years, a decreasing trend in external skeletal robusticity and an increasing trend in overweight and obesity was observed worldwide in adults and children as modern lifestyles in nutritional and activity behavior have changed. However, body mass index (BMI) as a measure for overweight is not an ideal predictor of % body fat (%BF) either in children and adolescents or in adults. On the contrary, it disguises a phenomenon called “hidden obesity”.
Objectives
We aim to approximate %BF by combining skeletal robusticity and BMI and develop an estimation-based tool to identify normal weight obese children and adolescents.
Sample and Methods
We analyzed cross-sectional data on height, weight, elbow breadth, and skinfold thickness (triceps and subscapular) of German children aged 6 to 18 years (N=15,034). We used modified Hattori charts and multiple linear regression to develop a tool, the “%BF estimator”, to estimate %BF by using BMI and skeletal robusticity measured as Frame Index.
Results
Independent of sex and age an increase in BMI is associated with an increase in %BF, an increase in Frame Index is associated with a decrease in %BF. The developed tool “%BF estimator” allows the estimation of %BF per sex and age group after calculation of BMI and Frame Index.
Conclusion
The “%BF estimator” is an easily applicable tool for the estimation of %BF in respect of body composition for clinical practice, screening, and public health research. It is non-invasive and has high accuracy. Further, it allows the identification of normal weight obese children and adolescents.
Mycotoxins and pesticides regularly co-occur in agricultural products worldwide. Thus, humans can be exposed to both toxic contaminants and pesticides simultaneously, and multi-methods assessing the occurrence of various food contaminants and residues in a single method are necessary. A two-dimensional high performance liquid chromatography tandem mass spectrometry method for the analysis of 40 (modified) mycotoxins, two plant growth regulators, two tropane alkaloids, and 334 pesticides in cereals was developed. After an acetonitrile/water/formic acid (79:20:1, v/v/v) multi-analyte extraction procedure, extracts were injected into the two-dimensional setup, and an online clean-up was performed. The method was validated according to Commission Decision (EC) no. 657/2002 and document N° SANTE/12682/2019. Good linearity (R2 > 0.96), recovery data between 70-120%, repeatability and reproducibility values < 20%, and expanded measurement uncertainties < 50% were obtained for a wide range of analytes, including very polar substances like deoxynivalenol-3-glucoside and methamidophos. However, results for fumonisins, zearalenone-14,16-disulfate, acid-labile pesticides, and carbamates were unsatisfying. Limits of quantification meeting maximum (residue) limits were achieved for most analytes. Matrix effects varied highly (−85 to +1574%) and were mainly observed for analytes eluting in the first dimension and early-eluting analytes in the second dimension. The application of the method demonstrated the co-occurrence of different types of cereals with 28 toxins and pesticides. Overall, 86% of the samples showed positive findings with at least one mycotoxin, plant growth regulator, or pesticide.
Janus droplets were prepared by vortex mixing of three non-mixable liquids, i.e., olive oil, silicone oil and water, in the presence of gold nanoparticles (AuNPs) in the aqueous phase and magnetite nanoparticles (MNPs) in the olive oil. The resulting Pickering emulsions were stabilized by a red-colored AuNP layer at the olive oil/water interface and MNPs at the oil/oil interface. The core–shell droplets can be stimulated by an external magnetic field. Surprisingly, an inner rotation of the silicon droplet is observed when MNPs are fixed at the inner silicon droplet interface. This is the first example of a controlled movement of the inner parts of complex double emulsions by magnetic manipulation via interfacially confined magnetic nanoparticles.
Rising temperatures in the Arctic affect soil microorganisms, herbivores, and peatland vegetation, thus directly and indirectly influencing microbial CH4 production. It is not currently known how methanotrophs in Arctic peat respond to combined changes in temperature, CH4 concentration, and vegetation. We studied methanotroph responses to temperature and CH4 concentration in peat exposed to herbivory and protected by exclosures. The methanotroph activity was assessed by CH4 oxidation rate measurements using peat soil microcosms and a pure culture of Methylobacter tundripaludum SV96, qPCR, and sequencing of pmoA transcripts. Elevated CH4 concentrations led to higher CH4 oxidation rates both in grazed and exclosed peat soils, but the strongest response was observed in grazed peat soils. Furthermore, the relative transcriptional activities of different methanotroph community members were affected by the CH4 concentrations. While transcriptional responses to low CH4 concentrations were more prevalent in grazed peat soils, responses to high CH4 concentrations were more prevalent in exclosed peat soils. We observed no significant methanotroph responses to increasing temperatures. We conclude that methanotroph communities in these peat soils respond to changes in the CH4 concentration depending on their previous exposure to grazing. This "conditioning " influences which strains will thrive and, therefore, determines the function of the methanotroph community.
Semi-natural habitats (SNHs) are becoming increasingly scarce in modern agricultural landscapes. This may reduce natural ecosystem services such as pest control with its putatively positive effect on crop production. In agreement with other studies, we recently reported wheat yield reductions at field borders which were linked to the type of SNH and the distance to the border. In this experimental landscape-wide study, we asked whether these yield losses have a biotic origin while analyzing fungal seed and fungal leaf pathogens, herbivory of cereal leaf beetles, and weed cover as hypothesized mediators between SNHs and yield. We established experimental winter wheat plots of a single variety within conventionally managed wheat fields at fixed distances either to a hedgerow or to an in-field kettle hole. For each plot, we recorded the fungal infection rate on seeds, fungal infection and herbivory rates on leaves, and weed cover. Using several generalized linear mixed-effects models as well as a structural equation model, we tested the effects of SNHs at a field scale (SNH type and distance to SNH) and at a landscape scale (percentage and diversity of SNHs within a 1000-m radius). In the dry year of 2016, we detected one putative biotic culprit: Weed cover was negatively associated with yield values at a 1-m and 5-m distance from the field border with a SNH. None of the fungal and insect pests, however, significantly affected yield, neither solely nor depending on type of or distance to a SNH. However, the pest groups themselves responded differently to SNH at the field scale and at the landscape scale. Our findings highlight that crop losses at field borders may be caused by biotic culprits; however, their negative impact seems weak and is putatively reduced by conventional farming practices.
A core operator of evolutionary algorithms (EAs) is the mutation. Recently, much attention has been devoted to the study of mutation operators with dynamic and non-uniform mutation rates. Following up on this area of work, we propose a new mutation operator and analyze its performance on the (1 + 1) Evolutionary Algorithm (EA). Our analyses show that this mutation operator competes with pre-existing ones, when used by the (1 + 1) EA on classes of problems for which results on the other mutation operators are available. We show that the (1 + 1) EA using our mutation operator finds a (1/3)-approximation ratio on any non-negative submodular function in polynomial time. We also consider the problem of maximizing a symmetric submodular function under a single matroid constraint and show that the (1 + 1) EA using our operator finds a (1/3)-approximation within polynomial time. This performance matches that of combinatorial local search algorithms specifically designed to solve these problems and outperforms them with constant probability. Finally, we evaluate the performance of the (1 + 1) EA using our operator experimentally by considering two applications: (a) the maximum directed cut problem on real-world graphs of different origins, with up to 6.6 million vertices and 56 million edges and (b) the symmetric mutual information problem using a four month period air pollution data set. In comparison with uniform mutation and a recently proposed dynamic scheme, our operator comes out on top on these instances.
Cep192, a novel missing link between the centrosomal core and corona in Dictyostelium amoebae
(2021)
The Dictyostelium centrosome is a nucleus-associated body with a diameter of approx. 500 nm. It contains no centrioles but consists of a cylindrical layered core structure surrounded by a microtubule-nucleating corona. At the onset of mitosis, the corona disassembles and the core structure duplicates through growth, splitting, and reorganization of the outer core layers. During the last decades our research group has characterized the majority of the 42 known centrosomal proteins. In this work we focus on the conserved, previously uncharacterized Cep192 protein. We use superresolution expansion microscopy (ExM) to show that Cep192 is a component of the outer core layers. Furthermore, ExM with centrosomal marker proteins nicely mirrored all ultrastructurally known centrosomal substructures. Furthermore, we improved the proximity-dependent biotin identification assay (BioID) by adapting the biotinylase BioID2 for expression in Dictyostelium and applying a knock-in strategy for the expression of BioID2-tagged centrosomal fusion proteins. Thus, we were able to identify various centrosomal Cep192 interaction partners, including CDK5RAP2, which was previously allocated to the inner corona structure, and several core components. Studies employing overexpression of GFP-Cep192 as well as depletion of endogenous Cep192 revealed that Cep192 is a key protein for the recruitment of corona components during centrosome biogenesis and is required to maintain a stable corona structure.
The photoinduced nonadiabatic dynamics of the enol-keto isomerization of 10-hydroxybenzo[h]quinoline (HBQ) are studied computationally using high-dimensional quantum dynamics. The simulations are based on a diabatic vibronic coupling Hamiltonian, which includes the two lowest pi pi* excited states and a n pi* state, which has high energy in the Franck-Condon zone, but significantly stabilizes upon excited state intramolecular proton transfer. A procedure, applicable to large classes of excited state proton transfer reactions, is presented to parametrize this model using potential energies, forces and force constants, which, in this case, are obtained by time-dependent density functional theory. The wave packet calculations predict a time scale of 10-15 fs for the photoreaction, and reproduce the time constants and the coherent oscillations observed in time- resolved spectroscopic studies performed on HBQ. In contrast to the interpretation given to the most recent experiments, it is found that the reaction initiated by 1 pi pi* <- S-0 photoexcitation proceeds essentially on a single potential energy surface, and the observed coherences bear signatures of Duschinsky mode-mixing along the reaction path. The dynamics after the 2 pi pi* <- S-0 excitation are instead nonadiabatic, and the n pi* state plays a major role in the relaxation process. The simulations suggest a mainly active role of the proton in the isomerization, rather than a passive migration assisted by the vibrations of the benzoquinoline backbone. <br /> [GRAPHICS] <br /> .
AAA+ proteins (ATPases associated with various cellular activities) catalyze the energy-dependent movement or rearrangement of macromolecules. A new study addresses the important question of how to design a selective chemical inhibitor for specific proteins in this diverse superfamily. The powerful chemical genetics approach adds to a growing toolbox of applications that allow dissection of the functions of distinct AAA+ proteins in vivo, facilitating the first steps toward effective drug development.
Influenza A virus (IAV) is a respiratory pathogen that causes seasonal epidemics with significant mortality. One of the most abundant proteins in IAV particles is the matrix protein 1 (M1), which is essential for the virus structural stability. M1 organizes virion assembly and budding at the plasma membrane (PM), where it interacts with other viral components. The recruitment of M1 to the PM as well as its interaction with the other viral envelope proteins (hemagglutinin [HA], neuraminidase, matrix protein 2 [M2]) is controversially discussed in previous studies. Therefore, we used fluorescence fluctuation microscopy techniques (i.e., scanning fluorescence cross-correlation spectroscopy and number and brightness) to quantify the oligomeric state of M1 and its interactions with other viral proteins in co-transfected as well as infected cells. Our results indicate that M1 is recruited to the PM by M2, as a consequence of the strong interaction between the two proteins. In contrast, only a weak interaction between M1 and HA was observed. M1-HA interaction occurred only in the event that M1 was already bound to the PM. We therefore conclude that M2 initiates the assembly of IAV by recruiting M1 to the PM, possibly allowing its further interaction with other viral proteins.
Hantaviruses are emerging pathogens that occasionally cause deadly outbreaks in the human population. While the structure of the viral envelope has been characterized with high precision, protein-protein interactions leading to the formation of new virions in infected cells are not fully understood. We used quantitative fluorescence microscopy (i.e., number and brightness analysis and fluorescence fluctuation spectroscopy) to monitor the interactions that lead to oligomeric spike complex formation in the physiological context of living cells. To this aim, we quantified protein-protein interactions for the glycoproteins Gn and Gc from Puumala and Hantaan orthohantaviruses in several cellular models. The oligomerization of each protein was analyzed in relation to subcellular localization, concentration, and the concentration of its interaction partner. Our results indicate that, when expressed separately, Gn and Gc form, respectively, homo-tetrameric and homo-dimeric complexes, in a concentration-dependent manner. Site-directed mutations or deletion mutants showed the specificity of their homotypic interactions. When both glycoproteins were coexpressed, we observed in the Golgi apparatus clear indication of GnGc interactions and the formation of Gn-Gc multimeric protein complexes of different sizes, while using various labeling schemes to minimize the influence of the fluorescent tags. Such large glycoprotein multimers may be identified as multiple Gn viral spikes interconnected via Gc-Gc contacts. This observation provides the possible first evidence for the initial assembly steps of the viral envelope within this organelle, and does so directly in living cells. <br /> IMPORTANCE In this work, we investigate protein-protein interactions that drive the assembly of the hantavirus envelope. These emerging pathogens have the potential to cause deadly outbreaks in the human population. Therefore, it is important to improve our quantitative understanding of the viral assembly process in infected cells, from a molecular point of view. By applying advanced fluorescence microscopy methods, we monitored the formation of viral spike complexes in different cell types. Our data support a model for hantavirus assembly according to which viral spikes are formed via the clustering of hetero-dimers of the two viral glycoproteins Gn and Gc. Furthermore, the observation of large Gn-Gc hetero-multimers provide the possible first evidence for the initial assembly steps of the viral envelope, directly in the Golgi apparatus of living cells.
Gene expression data provide the expression levels of tens of thousands of genes from several hundred samples. These data are analyzed to detect biomarkers that can be of prognostic or diagnostic use. Traditionally, biomarker detection for gene expression data is the task of gene selection. The vast number of genes is reduced to a few relevant ones that achieve the best performance for the respective use case. Traditional approaches select genes based on their statistical significance in the data set. This results in issues of robustness, redundancy and true biological relevance of the selected genes. Integrative analyses typically address these shortcomings by integrating multiple data artifacts from the same objects, e.g. gene expression and methylation data. When only gene expression data are available, integrative analyses instead use curated information on biological processes from public knowledge bases. With knowledge bases providing an ever-increasing amount of curated biological knowledge, such prior knowledge approaches become more powerful. This paper provides a thorough overview on the status quo of biomarker detection on gene expression data with prior biological knowledge. We discuss current shortcomings of traditional approaches, review recent external knowledge bases, provide a classification and qualitative comparison of existing prior knowledge approaches and discuss open challenges for this kind of gene selection.
Comprior
(2021)
Background
Reproducible benchmarking is important for assessing the effectiveness of novel feature selection approaches applied on gene expression data, especially for prior knowledge approaches that incorporate biological information from online knowledge bases. However, no full-fledged benchmarking system exists that is extensible, provides built-in feature selection approaches, and a comprehensive result assessment encompassing classification performance, robustness, and biological relevance. Moreover, the particular needs of prior knowledge feature selection approaches, i.e. uniform access to knowledge bases, are not addressed. As a consequence, prior knowledge approaches are not evaluated amongst each other, leaving open questions regarding their effectiveness.
Results
We present the Comprior benchmark tool, which facilitates the rapid development and effortless benchmarking of feature selection approaches, with a special focus on prior knowledge approaches. Comprior is extensible by custom approaches, offers built-in standard feature selection approaches, enables uniform access to multiple knowledge bases, and provides a customizable evaluation infrastructure to compare multiple feature selection approaches regarding their classification performance, robustness, runtime, and biological relevance.
Conclusion
Comprior allows reproducible benchmarking especially of prior knowledge approaches, which facilitates their applicability and for the first time enables a comprehensive assessment of their effectiveness
Cellulose and chitin are the most abundant polymeric, organic carbon source globally. Thus, microbes degrading these polymers significantly influence global carbon cycling and greenhouse gas production. Fungi are recognized as important for cellulose decomposition in terrestrial environments, but are far less studied in marine environments, where bacterial organic matter degradation pathways tend to receive more attention. In this study, we investigated the potential of fungi to degrade kelp detritus, which is a major source of cellulose in marine systems. Given that kelp detritus can be transported considerable distances in the marine environment, we were specifically interested in the capability of endophytic fungi, which are transported with detritus, to ultimately contribute to kelp detritus degradation. We isolated 10 species and two strains of endophytic fungi from the kelp Ecklonia radiata. We then used a dye decolorization assay to assess their ability to degrade organic polymers (lignin, cellulose, and hemicellulose) under both oxic and anoxic conditions and compared their degradation ability with common terrestrial fungi. Under oxic conditions, there was evidence that Ascomycota isolates produced cellulose-degrading extracellular enzymes (associated with manganese peroxidase and sulfur-containing lignin peroxidase), while Mucoromycota isolates appeared to produce both lignin and cellulose-degrading extracellular enzymes, and all Basidiomycota isolates produced lignin-degrading enzymes (associated with laccase and lignin peroxidase). Under anoxic conditions, only three kelp endophytes degraded cellulose. We concluded that kelp fungal endophytes can contribute to cellulose degradation in both oxic and anoxic environments. Thus, endophytic kelp fungi may play a significant role in marine carbon cycling via polymeric organic matter degradation.
In the zebrafish embryo, the onset of blood flow generates fluid shear stress on endocardial cells, which are specialized endothelial cells that line the interior of the heart. High levels of fluid shear stress activate both Notch and Klf2 signaling, which play crucial roles in atrioventricular valvulogenesis. However, it remains unclear why only individual endocardial cells ingress into the cardiac jelly and initiate valvulogenesis. Here, we show that lateral inhibition between endocardial cells, mediated by Notch, singles out Delta-like-4-positive endocardial cells. These cells ingress into the cardiac jelly, where they form an abluminal cell population. Delta-like-4-positive cells ingress in response to Wnt9a, which is produced in parallel through an Erk5Klf2-Wnt9a signaling cascade also activated by blood flow. Hence, mechanical stimulation activates parallel mechanosensitive signaling pathways that produce binary effects by driving endocardial cells toward either luminal or abluminal fates. Ultimately, these cell fate decisions sculpt cardiac valve leaflets.
Plants are often challenged by an array of unfavorable environmental conditions. During cold exposure, many changes occur that include, for example, the stabilization of cell membranes, alterations in gene expression and enzyme activities, as well as the accumulation of metabolites. In the presented study, the carbohydrate metabolism was analyzed in the very early response of plants to a low temperature (2 degrees C) in the leaves of 5-week-old potato plants of the Russet Burbank cultivar during the first 12 h of cold treatment (2 h dark and 10 h light). First, some plant stress indicators were examined and it was shown that short-term cold exposure did not significantly affect the relative water content and chlorophyll content (only after 12 h), but caused an increase in malondialdehyde concentration and a decrease in the expression of NDA1, a homolog of the NADH dehydrogenase gene. In addition, it was shown that the content of transitory starch increased transiently in the very early phase of the plant response (3-6 h) to cold treatment, and then its decrease was observed after 12 h. In contrast, soluble sugars such as glucose and fructose were significantly increased only at the end of the light period, where a decrease in sucrose content was observed. The availability of the monosaccharides at constitutively high levels, regardless of the temperature, may delay the response to cold, involving amylolytic starch degradation in chloroplasts. The decrease in starch content, observed in leaves after 12 h of cold exposure, was preceded by a dramatic increase in the transcript levels of the key enzymes of starch degradation initiation, the alpha-glucan, water dikinase (GWD-EC 2.7.9.4) and the phosphoglucan, water dikinase (PWD-EC 2.7.9.5). The gene expression of both dikinases peaked at 9 h of cold exposure, as analyzed by real-time PCR. Moreover, enhanced activities of the acid invertase as well as of both glucan phosphorylases during exposure to a chilling temperature were observed. However, it was also noticed that during the light phase, there was a general increase in glucan phosphorylase activities for both control and cold-stressed plants irrespective of the temperature. In conclusion, a short-term cold treatment alters the carbohydrate metabolism in the leaves of potato, which leads to an increase in the content of soluble sugars.
PC2P
(2021)
Motivation:
Prediction of protein complexes from protein-protein interaction (PPI) networks is an important problem in systems biology, as they control different cellular functions. The existing solutions employ algorithms for network community detection that identify dense subgraphs in PPI networks. However, gold standards in yeast and human indicate that protein complexes can also induce sparse subgraphs, introducing further challenges in protein complex prediction.
Results:
To address this issue, we formalize protein complexes as biclique spanned subgraphs, which include both sparse and dense subgraphs. We then cast the problem of protein complex prediction as a network partitioning into biclique spanned subgraphs with removal of minimum number of edges, called coherent partition. Since finding a coherent partition is a computationally intractable problem, we devise a parameter-free greedy approximation algorithm, termed Protein Complexes from Coherent Partition (PC2P), based on key properties of biclique spanned subgraphs. Through comparison with nine contenders, we demonstrate that PC2P: (i) successfully identifies modular structure in networks, as a prerequisite for protein complex prediction, (ii) outperforms the existing solutions with respect to a composite score of five performance measures on 75% and 100% of the analyzed PPI networks and gold standards in yeast and human, respectively, and (iii,iv) does not compromise GO semantic similarity and enrichment score of the predicted protein complexes. Therefore, our study demonstrates that clustering of networks in terms of biclique spanned subgraphs is a promising framework for detection of complexes in PPI networks.
Identification of protein complexes from protein-protein interaction (PPI) networks is a key problem in PPI mining, solved by parameter-dependent approaches that suffer from small recall rates. Here we introduce GCC-v, a family of efficient, parameter-free algorithms to accurately predict protein complexes using the (weighted) clustering coefficient of proteins in PPI networks. Through comparative analyses with gold standards and PPI networks from Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens, we demonstrate that GCC-v outperforms twelve state-of-the-art approaches for identification of protein complexes with respect to twelve performance measures in at least 85.71% of scenarios. We also show that GCC-v results in the exact recovery of similar to 35% of protein complexes in a pan-plant PPI network and discover 144 new protein complexes in Arabidopsis thaliana, with high support from GO semantic similarity. Our results indicate that findings from GCC-v are robust to network perturbations, which has direct implications to assess the impact of the PPI network quality on the predicted protein complexes. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
A symmetry-breaking mechanism is investigated that creates bistability between fully and partially synchronized states in oscillator networks. Two populations of oscillators with unimodal frequency distribution and different amplitudes, in the presence of weak global coupling, are shown to simplify to a modular network with asymmetrical coupling. With increasing the coupling strength, a synchronization transition is observed with an isolated fully synchronized state. The results are interpreted theoretically in the thermodynamic limit and confirmed in experiments with chemical oscillators.