Small‐scale genetic structure and mating patterns in an extensive sessile oak forest (Quercus petraea (Matt.) Liebl.)

Oaks (Quercus) are major components of temperate forest ecosystems in the Northern Hemisphere where they form intermediate or climax communities. Sessile oak (Quercus petraea) forests represent the climax vegetation in eastern Germany and western Poland. Here, sessile oak forms pure stands or occurs intermixed with Scots Pine (Pinus sylvestris). A large body of research is available on gene flow, reproduction dynamics, and genetic structure in fragmented landscapes and mixed populations. At the same time, our knowledge regarding large, contiguous, and monospecific populations is considerably less well developed. Our study is an attempt to further develop our understanding of the reproduction ecology of sessile oak as an ecologically and economically important forest tree by analyzing mating patterns and genetic structure within adult trees and seedlings originating from one or two reproduction events in an extensive, naturally regenerating sessile oak forest. We detected positive spatial genetic structure up to 30 meters between adult trees and up to 40 meters between seedlings. Seed dispersal distances averaged 8.4 meters. Pollen dispersal distances averaged 22.6 meters. In both cases, the largest proportion of the dispersal occurred over short distances. Dispersal over longer distances was more common for pollen but also appeared regularly for seeds. The reproductive success of individual trees was highly skewed. Only 41 percent of all adult trees produced any offspring while the majority did not participate in reproduction. Among those trees that contributed to the analyzed seedling sample, 80 percent contributed 1–3 gametes. Only 20 percent of all parent trees contributed four or more gametes. However, these relatively few most fertile trees contributed 51 percent of all gametes within the seedling sample. Vitality and growth differed significantly between reproducing and nonreproducing adult trees with reproducing trees being more vital and vigorous than nonreproducing individuals. Our study demonstrates that extensive, apparently homogenous oak forests are far from uniform on the genetic level. On the contrary, they form highly complex mosaics of remarkably small local neighborhoods. This counterbalances the levelling effect of long‐distance dispersal and may increase the species’ adaptive potential. Incorporating these dynamics in the management, conservation, and restoration of oak forests can support the conservation of forest genetic diversity and assist those forests in coping with environmental change.     

Compensation of large motion sensor displacements during long recordings of limb movements

In motion capture applications using electromagnetic tracking systems the process of anatomical calibration associates the technical frames of sensors attached to the skin with the human anatomy. Joint centers and axes are determined relative to these frames. A change of orientation of the sensor relative to the skin renders this calibration faulty. This sensitivity regarding sensor displacement can turn out to be a serious problem with movement recordings of several minutes duration. We propose the “dislocation distance” as a novel method to quantify sensor displacement and to detect gradual and sudden changes of sensor orientation. Furthermore a method to define a so called fixed technical frame is proposed as a robust reference frame which can adapt to a new sensor orientation on the skin. The proposed methods are applied to quantify the effects of sensor displacement of 120 upper and lower limb movement recordings of newborns revealing the need for a method to compensate for sensor displacement. The reliability of the fixed technical frame is quantified and it is shown that trend and dispersion of the dislocation distance can be significantly reduced. A working example illustrates the consequences of sensor displacement on derived angle time series and how they are avoided using the fixed technical frame.     

How Prof. Burnstock’s enthusiasm supported P2 receptor research in Germany

Purinergic Signalling -     

Species- and clone-specific responses to environmental stimuli in the cladocerans Bosmina cornuta and B. pellucida - a comparison with Daphnia

We studied the variation of small-scale swimming behaviour in eight Bosmina cornuta and ten B. pellucida clones in response to key environmental factors to test whether swimming behaviour and genotypes are linked in non-Daphnia cladocerans. We quantified (1) the short-term responses to changes in temperature, light intensity and pH, (2) the response to long-term temperature acclimation, and (3) the pH-related survival rates. Vertical swimming activity S was quantified in cuvette experiments as crossings of a line at 2 cm height per individual an hour. S differed significantly among species and conspecific clones. At any temperature, light intensity and pH tested, B. cornuta (clone variation: 40-58 crossings/ind.- h) showed a higher vertical swimming activity than B. pellucida (clone variation: 25-48 crossings/ind.- h). A short-term change of water temperature (range tested: 10-25C) only affected S of B. cornuta, whereas that of B. pellucida remained unaltered. In contrast, S increased with rising temperature following long-term temperature acclimation (range tested: 10-20C) in both species. Swimming activity was inversely related to the light intensity (range tested: 60-60,000 lux), but decrease of activity was stronger in B. pellucida (44′ 12 crossings/ind - h) than in B. cornuta (50′ 40 crossings/ind.- h). Short-term changes of pH (range tested: 4-6) did not influence swimming activity in any species, although a prolonged exposure (24 h) to pH 4 was lethal. Thus, Bosmina showed behavioural responses which permit to distinguish between the species and which are related to their seasonal succession and distribution pattern.     

Reverse Action of Ribonuclease T1 Variants In ICE

Abstract

Synthesis of guanylyl(3′→5′)cytidine catalysed by RNase T1 variants (Tyr42Trp, Tyr24Trp and GluSSAla) was studied in frozen aqueous systems at-10°C and in solution at 0°C. Freezing the reaction mixture resulted in significantly enhanced dinucleoside monophosphate yields independently of the effect of mutation on substrate binding and catalytic mechanism. We assume that the protonation state of the catalytic residues is influenced by freezing, possibly due to conformational changes of the enzyme proteins.     

Combination of a Proteomics Approach and Reengineering of Meso Scale Network Models for Prediction of Mode-of-Action for Tyrosine Kinase Inhibitors

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs.