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WRKY23 is a component of the transcriptional network mediating auxin feedback on PIN polarity
(2018)
Auxin is unique among plant hormones due to its directional transport that is mediated by the polarly distributed PIN auxin transporters at the plasma membrane. The canalization hypothesis proposes that the auxin feedback on its polar flow is a crucial, plant-specific mechanism mediating multiple self-organizing developmental processes. Here, we used the auxin effect on the PIN polar localization in Arabidopsis thaliana roots as a proxy for the auxin feedback on the PIN polarity during canalization. We performed microarray experiments to find regulators of this process that act downstream of auxin. We identified genes that were transcriptionally regulated by auxin in an AXR3/IAA17-and ARF7/ARF19-dependent manner. Besides the known components of the PIN polarity, such as PID and PIP5K kinases, a number of potential new regulators were detected, among which the WRKY23 transcription factor, which was characterized in more detail. Gain-and loss-of-function mutants confirmed a role for WRKY23 in mediating the auxin effect on the PIN polarity. Accordingly, processes requiring auxin-mediated PIN polarity rearrangements, such as vascular tissue development during leaf venation, showed a higher WRKY23 expression and required the WRKY23 activity. Our results provide initial insights into the auxin transcriptional network acting upstream of PIN polarization and, potentially, canalization-mediated plant development.
Wind influences the development, architecture and morphology of plant roots and may modify subsequent interactions between plants and soil (plant–soil feedbacks—PSFs). However, information on wind effects on fine root morphology is scarce and the extent to which wind changes plant–soil interactions remains unclear. Therefore, we investigated the effects of two wind intensity levels by manipulating surrounding vegetation height in a grassland PSF field experiment. We grew four common plant species (two grasses and two non-leguminous forbs) with soil biota either previously conditioned by these or other species and tested the effect of wind on root:shoot ratio, fine root morphological traits as well as the outcome for PSFs. Wind intensity did not affect biomass allocation (i.e. root:shoot ratio) in any species. However, fine-root morphology of all species changed under high wind intensity. High wind intensity increased specific root length and surface area and decreased root tissue density, especially in the two grasses. Similarly, the direction of PSFs changed under high wind intensity in all four species, but differences in biomass production on the different soils between high and low wind intensity were marginal and most pronounced when comparing grasses with forbs. Because soils did not differ in plant-available nor total nutrient content, the results suggest that wind-induced changes in root morphology have the potential to influence plant–soil interactions. Linking wind-induced changes in fine-root morphology to effects on PSF improves our understanding of plant–soil interactions under changing environmental conditions.
During the last decade, intracellular actin waves have attracted much attention due to their essential role in various cellular functions, ranging from motility to cytokinesis. Experimental methods have advanced significantly and can capture the dynamics of actin waves over a large range of spatio-temporal scales. However, the corresponding coarse-grained theory mostly avoids the full complexity of this multi-scale phenomenon. In this perspective, we focus on a minimal continuum model of activator–inhibitor type and highlight the qualitative role of mass conservation, which is typically overlooked. Specifically, our interest is to connect between the mathematical mechanisms of pattern formation in the presence of a large-scale mode, due to mass conservation, and distinct behaviors of actin waves.
Welcome to the Dark Side
(2022)
Differences in natural light conditions caused by changes in moonlight are known to affect perceived predation risk in many nocturnal prey species. As artificial light at night (ALAN) is steadily increasing in space and intensity, it has the potential to change movement and foraging behavior of many species as it might increase perceived predation risk and mask natural light cycles. We investigated if partial nighttime illumination leads to changes in foraging behavior during the night and the subsequent day in a small mammal and whether these changes are related to animal personalities. We subjected bank voles to partial nighttime illumination in a foraging landscape under laboratory conditions and in large grassland enclosures under near natural conditions. We measured giving-up density of food in illuminated and dark artificial seed patches and video recorded the movement of animals. While animals reduced number of visits to illuminated seed patches at night, they increased visits to these patches at the following day compared to dark seed patches. Overall, bold individuals had lower giving-up densities than shy individuals but this difference increased at day in formerly illuminated seed patches. Small mammals thus showed carry-over effects on daytime foraging behavior due to ALAN, i.e., nocturnal illumination has the potential to affect intra- and interspecific interactions during both night and day with possible changes in personality structure within populations and altered predator-prey dynamics.
Background
The kidneys are essential for the metabolism of vitamin A (retinol) and its transport proteins retinol-binding protein 4 (RBP4) and transthyretin. Little is known about changes in serum concentration after living donor kidney transplantation (LDKT) as a consequence of unilateral nephrectomy; although an association of these parameters with the risk of cardiovascular diseases and insulin resistance has been suggested. Therefore we analyzed the concentration of retinol, RBP4, apoRBP4 and transthyretin in serum of 20 living-kidney donors and respective recipients at baseline as well as 6 weeks and 6 months after LDKT.
Results
As a consequence of LDKT, the kidney function of recipients was improved while the kidney function of donors was moderately reduced within 6 weeks after LDKT. With regard to vitamin A metabolism, the recipients revealed higher levels of retinol, RBP4, transthyretin and apoRBP4 before LDKT in comparison to donors. After LDKT, the levels of all four parameters decreased in serum of the recipients, while retinol, RBP4 as well as apoRBP4 serum levels of donors increased and remained increased during the follow-up period of 6 months.
Conclusion
LDKT is generally regarded as beneficial for allograft recipients and not particularly detrimental for the donors. However, it could be demonstrated in this study that a moderate reduction of kidney function by unilateral nephrectomy, resulted in an imbalance of components of vitamin A metabolism with a significant increase of retinol and RBP4 and apoRBP4 concentration in serum of donors.
Plastic pollution is an increasing environmental problem, but a comprehensive understanding of its effect in the environment is still missing. The wide variety of size, shape, and polymer composition of plastics impedes an adequate risk assessment. We investigated the effect of differently sized polystyrene beads (1-, 3-, 6-µm; PS) and polyamide fragments (5–25 µm, PA) and non-plastics items such as silica beads (3-µm, SiO2) on the population growth, reproduction (egg ratio), and survival of two common aquatic micro invertebrates: the rotifer species Brachionus calyciflorus and Brachionus fernandoi. The MPs were combined with food quantity, limiting and saturating food concentration, and with food of different quality. We found variable fitness responses with a significant effect of 3-µm PS on the population growth rate in both rotifer species with respect to food quantity. An interaction between the food quality and the MPs treatments was found in the reproduction of B. calyciflorus. PA and SiO2 beads had no effect on fitness response. This study provides further evidence of the indirect effect of MPs in planktonic rotifers and the importance of testing different environmental conditions that could influence the effect of MPs.
The activity of vacuolar H+-ATPase (V-ATPase) in the apical membrane of blowfly (Calliphora vicina) salivary glands is regulated by the neurohormone serotonin (5-HT). 5-HT induces, via protein kinase A, the phosphorylation of V-ATPase subunit C and the assembly of V-ATPase holoenzymes. The protein phosphatase responsible for the dephosphorylation of subunit C and V-ATPase inactivation is not as yet known. We show here that inhibitors of protein phosphatases PP1 and PP2A (tautomycin, ocadaic acid) and PP2B (cyclosporin A, FK-506) do not prevent V-ATPase deactivation and dephosphorylation of subunit C. A decrease in the intracellular Mg2+ level caused by loading secretory cells with EDTA-AM leads to the activation of proton pumping in the absence of 5-HT, prolongs the 5-HT-induced response in proton pumping, and inhibits the dephosphorylation of subunit C. Thus, the deactivation of V-ATPase is most probably mediated by a protein phosphatase that is insensitive to okadaic acid and that requires Mg2+, namely, a member of the PP2C protein family. By molecular biological techniques, we demonstrate the expression of at least two PP2C protein family members in blowfly salivary glands. © 2009 Wiley Periodicals, Inc.
Using ESTs for phylogenomics
(2008)
Background
While full genome sequences are still only available for a handful of taxa, large collections of partial gene sequences are available for many more. The alignment of partial gene sequences results in a multiple sequence alignment containing large gaps that are arranged in a staggered pattern. The consequences of this pattern of missing data on the accuracy of phylogenetic analysis are not well understood. We conducted a simulation study to determine the accuracy of phylogenetic trees obtained from gappy alignments using three commonly used phylogenetic reconstruction methods (Neighbor Joining, Maximum Parsimony, and Maximum Likelihood) and studied ways to improve the accuracy of trees obtained from such datasets.
Results
We found that the pattern of gappiness in multiple sequence alignments derived from partial gene sequences substantially compromised phylogenetic accuracy even in the absence of alignment error. The decline in accuracy was beyond what would be expected based on the amount of missing data. The decline was particularly dramatic for Neighbor Joining and Maximum Parsimony, where the majority of gappy alignments contained 25% to 40% incorrect quartets. To improve the accuracy of the trees obtained from a gappy multiple sequence alignment, we examined two approaches. In the first approach, alignment masking, potentially problematic columns and input sequences are excluded from from the dataset. Even in the absence of alignment error, masking improved phylogenetic accuracy up to 100-fold. However, masking retained, on average, only 83% of the input sequences. In the second approach, alignment subdivision, the missing data is statistically modelled in order to retain as many sequences as possible in the phylogenetic analysis. Subdivision resulted in more modest improvements to alignment accuracy, but succeeded in including almost all of the input sequences.
Conclusion
These results demonstrate that partial gene sequences and gappy multiple sequence alignments can pose a major problem for phylogenetic analysis. The concern will be greatest for high-throughput phylogenomic analyses, in which Neighbor Joining is often the preferred method due to its computational efficiency. Both approaches can be used to increase the accuracy of phylogenetic inference from a gappy alignment. The choice between the two approaches will depend upon how robust the application is to the loss of sequences from the input set, with alignment masking generally giving a much greater improvement in accuracy but at the cost of discarding a larger number of the input sequences.
Background: Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications.
Results: Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study.
Conclusions: Our study is intended to serve as a guide for choosing a particular combination of similarity measures and scoring schemes suitable for reconstruction of gene regulatory networks from short time series data. We show that further improvement of algorithms for reverse engineering can be obtained if one considers measures that are rooted in the study of symbolic dynamics or ranks, in contrast to the application of common similarity measures which do not consider the temporal character of the employed data. Moreover, we establish that the asymmetric weighting scoring scheme together with symbol based measures (for low noise level) and rank based measures (for high noise level) are the most suitable choices.
Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10-100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (similar to 60,000 km(2)) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999-2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.