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Ribonuclease H2 plays an essential role for genome stability as it removes ribonucleotides misincorporated into genomic DNA by replicative polymerases and resolves RNA/DNA hybrids. Biallelic mutations in the genes encoding the three RNase H2 subunits cause Aicardi-Goutieres syndrome (AGS), an early-onset inflammatory encephalopathy that phenotypically overlaps with the autoimmune disorder systemic lupus erythematosus. Here we studied the intracellular dynamics of RNase H2 in living cells during DNA replication and in response to DNA damage using confocal time-lapse imaging and fluorescence cross-correlation spectroscopy. We demonstrate that the RNase H2 complex is assembled in the cytosol and imported into the nucleus in an RNase H2B-dependent manner. RNase H2 is not only recruited to DNA replication foci, but also to sites of PCNA-dependent DNA repair. By fluorescence recovery after photobleaching, we demonstrate a high mobility and fast exchange of RNase H2 at sites of DNA repair and replication. We provide evidence that recruitment of RNase H2 is not only PCNA-dependent, mediated by an interaction of the B subunit with PCNA, but also PCNA-independent mediated via the catalytic domain of the A subunit. We found that AGS-associated mutations alter complex formation, recruitment efficiency and exchange kinetics at sites of DNA replication and repair suggesting that impaired ribonucleotide removal contributes to AGS pathogenesis.
In addition to their role as a source of reduced carbon, sugars may directly or indirectly control a wide range of activities in plant cells, through transcriptional and post-translational regulation. This control has been studied in detail using Arabidopsis thaliana, where genetic analysis offers many possibilities. Much less is known about perennial woody species. For several years, various aspects of sugar sensing and signalling have been investigated in the grape (Vitis vinifera L.) berry, an organ that accumulates high concentrations of hexoses in the vacuoles of flesh cells. Here we review various aspects of this topic: the molecular basis of sugar transport and its regulation by sugars in grapevine; the functional analysis of several sugar-induced genes; the effects of some biotic and abiotic stresses on the sugar content of the berry; and finally the effects of exogenous sugar supply on the ripening process in field conditions. A picture of complex feedback and multiprocess regulation emerges from these data.
Metabolic systems tend to exhibit steady states that can be measured in terms of their concentrations and fluxes. These measurements can be regarded as a phenotypic representation of all the complex interactions and regulatory mechanisms taking place in the underlying metabolic network. Such interactions determine the system's response to external perturbations and are responsible, for example, for its asymptotic stability or for oscillatory trajectories around the steady state. However, determining these perturbation responses in the absence of fully specified kinetic models remains an important challenge of computational systems biology. Structural kinetic modeling (SKM) is a framework to analyse whether a metabolic steady state remains stable under perturbation, without requiring detailed knowledge about individual rate equations. It provides a parameterised representation of the system's Jacobian matrix in which the model parameters encode information about the enzyme-metabolite interactions. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. The parameter space can be analysed statistically in order to detect network positions that contribute significantly to the perturbation response. Because the sampled parameters are equivalent to the elasticities used in metabolic control analysis (MCA), the results are easy to interpret biologically. In this project, the SKM framework was extended by several novel methodological improvements. These improvements were evaluated in a simulation study using a set of small example pathways with simple Michaelis Menten rate laws. Afterwards, a detailed analysis of the dynamic properties of the neuronal TCA cycle was performed in order to demonstrate how the new insights obtained in this work could be used for the study of complex metabolic systems. The first improvement was achieved by examining the biological feasibility of the elasticity combinations created during Monte Carlo sampling. Using a set of small example systems, the findings showed that the majority of sampled SK-models would yield negative kinetic parameters if they were translated back into kinetic models. To overcome this problem, a simple criterion was formulated that mitigates such infeasible models and the application of this criterion changed the conclusions of the SKM experiment. The second improvement of this work was the application of supervised machine-learning approaches in order to analyse SKM experiments. So far, SKM experiments have focused on the detection of individual enzymes to identify single reactions important for maintaining the stability or oscillatory trajectories. In this work, this approach was extended by demonstrating how SKM enables the detection of ensembles of enzymes or metabolites that act together in an orchestrated manner to coordinate the pathways response to perturbations. In doing so, stable and unstable states served as class labels, and classifiers were trained to detect elasticity regions associated with stability and instability. Classification was performed using decision trees and relevance vector machines (RVMs). The decision trees produced good classification accuracy in terms of model bias and generalizability. RVMs outperformed decision trees when applied to small models, but encountered severe problems when applied to larger systems because of their high runtime requirements. The decision tree rulesets were analysed statistically and individually in order to explore the role of individual enzymes or metabolites in controlling the system's trajectories around steady states. The third improvement of this work was the establishment of a relationship between the SKM framework and the related field of MCA. In particular, it was shown how the sampled elasticities could be converted to flux control coefficients, which were then investigated for their predictive information content in classifier training. After evaluation on the small example pathways, the methodology was used to study two steady states of the neuronal TCA cycle with respect to their intrinsic mechanisms responsible for stability or instability. The findings showed that several elasticities were jointly coordinated to control stability and that the main source for potential instabilities were mutations in the enzyme alpha-ketoglutarate dehydrogenase.
D-Peptides have been attributed pharmacological advantages over regular L-peptides, yet design rules are largely unknown. Based on a designed coiled coil-like D/L heterotetramer, named L-Base/D-Acid, we generated a library offering alternative residues for interaction with the D-peptide. Phage display selection yielded one predominant peptide, named HelixA, that differed at 13 positions from the scaffold helix. In addition to the observed D-/L-heterotetramers, ratio-dependent intermediate states were detected by isothermal titration calorimetry. Importantly, the formation of the selected HelixA/D-Acid bundle passes through fewer intermediate states than L-Base/D-Acid. Back mutation of HelixA core residues to L-Base (HelixLL) revealed that the residues at e/g-positions are responsible for the different intermediates. Furthermore, a Val-core variant (PeptideVV) was completely devoid of binding D-Acid, whereas an Ile-core helix (HelixII) interacted with D-Acid in a significantly more specific complex than L-Base.
Starch synthase (SS) and branching enzyme (BE) establish the two glycosidic linkages existing in starch. Both enzymes exist as several isoforms. Enzymes derived from several species were studied extensively both in vivo and in vitro over the last years, however, analyses of a functional interaction of SS and BE isoforms are missing so far. Here, we present data from in vitro studies including both interaction of leaf derived and heterologously expressed SS and BE isoforms. We found that SSI activity in native PAGE without addition of glucans was dependent on at least one of the two BE isoforms active in Arabidopsis leaves. This interaction is most likely not based on a physical association of the enzymes, as demonstrated by immunodetection and native PAGE mobility analysis of SSI, BE2, and BE3. The glucans formed by the action of SSI/BEs were analysed using leaf protein extracts from wild type and be single mutants (Atbe2 and Atbe3 mutant lines) and by different combinations of recombinant proteins. Chain length distribution (CLD) patterns of the formed glucans were irrespective of SSI and BE isoforms origin and still independent of assay conditions. Furthermore, we show that all SS isoforms (SSI-SSIV) were able to interact with BEs and form branched glucans. However, only SSI/BEs generated a polymodal distribution of glucans which was similar to CLD pattern detected in amylopectin of Arabidopsis leaf starch. We discuss the impact of the SSI/BEs interplay for the CLD pattern of amylopectin.
Ancient mitochondrial DNA and the genetic history of Eurasian beaver (Castor fiber) in Europe
(2014)
After centuries of human hunting, the Eurasian beaver Castor fiber had disappeared from most of its original range by the end of the 19th century. The surviving relict populations are characterized by both low genetic diversity and strong phylogeographical structure. However, it remains unclear whether these attributes are the result of a human-induced, late Holocene bottleneck or already existed prior to this reduction in range. To investigate genetic diversity in Eurasian beaver populations during the Holocene, we obtained mitochondrial control region DNA sequences from 48 ancient beaver samples and added 152 modern sequences from GenBank. Phylogeographical analyses of the data indicate a differentiation of European beaver populations into three mitochondrial clades. The two main clades occur in western and eastern Europe, respectively, with an early Holocene contact zone in eastern Europe near a present-day contact zone. A divergent and previously unknown clade of beavers from the Danube Basin survived until at least 6000years ago, but went extinct during the transition to modern times. Finally, we identify a recent decline in effective population size of Eurasian beavers, with a stronger bottleneck signal in the western than in the eastern clade. Our results suggest that the low genetic diversity and the strong phylogeographical structure in recent beavers are artefacts of human hunting-associated population reductions. While beaver populations have been growing rapidly since the late 19th century, genetic diversity within modern beaver populations remains considerably reduced compared to what was present prior to the period of human hunting and habitat reduction.
ANG-2 for quantitative Na+ determination in living cells by time-resolved fluorescence microscopy
(2014)
Sodium ions (Na+) play an important role in a plethora of cellular processes, which are complex and partly still unexplored. For the investigation of these processes and quantification of intracellular Na+ concentrations ([Na+](i)), two-photon coupled fluorescence lifetime imaging microscopy (2P-FLIM) was performed in the salivary glands of the cockroach Periplaneta americana. For this, the novel Na+-sensitive fluorescent dye Asante NaTRIUM Green-2 (ANG-2) was evaluated, both in vitro and in situ. In this context, absorption coefficients, fluorescence quantum yields and 2P action cross-sections were determined for the first time. ANG-2 was 2P-excitable over a broad spectral range and displayed fluorescence in the visible spectral range. Although the fluorescence decay behaviour of ANG-2 was triexponential in vitro, its analysis indicates a Na+-sensitivity appropriate for recordings in living cells. The Na+-sensitivity was reduced in situ, but the biexponential fluorescence decay behaviour could be successfully analysed in terms of quantitative [Na+](i) recordings. Thus, physiological 2P-FLIM measurements revealed a dopamine-induced [Na+](i) rise in cockroach salivary gland cells, which was dependent on a Na+-K+-2Cl-cotransporter (NKCC) activity. It was concluded that ANG-2 is a promising new sodium indicator applicable for diverse biological systems.
The importance of a careful choice of the appropriate scale for studying ecological phenomena has been stressed repeatedly. However, issues of spatial scale in metapopulation dynamics received much more attention compared to temporal scale. Moreover, multiple calls were made to carefully choose the appropriate model structure for Population Viability Analysis (PVA). We assessed the effect of using coarser resolution in time and model structure on population dynamics. For this purpose, we compared outcomes of two PVA models differing in their time step: daily individual-based model (dIBM) and yearly stage-based model (ySBM), loaded with empirical data on a well-known metapopulation of the butterfly Boloria eunomia. Both models included the same environmental drivers of population dynamics that were previously identified as being the most important for this species. Under temperature change scenarios, both models yielded the same qualitative scenario ranking, but they quite substantially differed quantitatively with dIBM being more pessimistic in absolute viability measures. We showed that these differences stemmed from inter-individual heterogeneity in dIBM allowing for phenological shifts of individual appearance. We conclude that a finer temporal resolution and an individual-based model structure allow capturing the essential mechanisms necessary to go beyond mere PVA scenario ranking. We encourage researchers to carefully chose the temporal resolution and structure of their model aiming at (1) depicting the processes important for (meta)population dynamics of the species and (2) implementing the environmental change scenarios expected for their study system in the future, using the temporal resolution at which such changes are predicted to operate.
Plants are sessile organisms that gauge stressful conditions to ensure survival and reproductive success. While plants in nature often encounter chronic or recurring stressful conditions, the strategies to cope with those are poorly understood. Here, we demonstrate the involvement of ARGONAUTE1 and the microRNA pathway in the adaptation to recurring heat stress (HS memory) at the physiological and molecular level. We show that miR156 isoforms are highly induced after HS and are functionally important for HS memory. miR156 promotes sustained expression of HS-responsive genes and is critical only after HS, demonstrating that the effects of modulating miR156 on HS memory do not reflect preexisting developmental alterations. miR156 targets SPL transcription factor genes that are master regulators of developmental transitions. SPL genes are posttranscriptionally downregulated by miR156 after HS, and this is critical for HS memory. Altogether, the miR156-SPL module mediates the response to recurring HS in Arabidopsis thaliana and thus may serve to integrate stress responses with development.