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Institute
- Institut für Biochemie und Biologie (158) (remove)
Random matrix theory (RMT) is well suited to describing the emergent properties of systems with complex interactions amongst their constituents through their eigenvalue spectrums. Some RMT results are applied to the problem of clustering high dimensional biological data with complex dependence structure amongst the variables. It will be shown that a gene relevance or correlation network can be constructed by choosing a correlation threshold in a principled way, such that it corresponds to a block diagonal structure in the correlation matrix, if such a structure exists. The structure is then found using community detection algorithms, but with parameter choice guided by RMT predictions. The resulting clustering is compared to a variety of hierarchical clustering outputs and is found to the most generalised result, in that it captures all the features found by the other considered methods.
Diffusion in a series of ionic liquids is investigated by a combination of Broadband Dielectric Spectroscopy (BDS) and Pulsed Field Gradient Nuclear Magnetic Resonance (PFG NMR). It is demonstrated that the mean jump lengths increase with the molecular volumes determined from quantum-chemical calculations. This provides a direct means-via Einstein-Smoluchowski relation-to determine the diffusion coefficient by BDS over more than 8 decades unambiguously and in quantitative agreement with PFG NMR measurements. New possibilities in the study of charge transport and dynamic glass transition in ionic liquids are thus opened.
Yeast hexokinase isoenzyme ScHxk2 stability of a two-domain protein with discontinuous domains
(2011)
The hexokinase isoenzyme 2 of Saccharomyces cerevisiae (ScHxk2) represents an archetype of a two-domain protein with the active site located in a cleft between the two domains. Binding of the substrate glucose results in a rigid body movement of the two domains leading to a cleft closure of the active site. Both domains of this enzyme are composed of discontinuous peptide sequences. This structural feature is reflected in the stability and folding of the ScHxk2 protein. Structural transitions induced by urea treatment resulted in the population of a thermodynamically stable folding intermediate, which, however, does not correspond to a molecule with one domain folded and the other unfolded. As demonstrated by different spectroscopic techniques, both domains are structurally affected by the partial denaturation. The intermediate possesses only 40% of the native secondary structural content and a substantial increase in the Stokes radius as judged by circular dichroism and dynamic light scattering analyses. One-dimensional H-1 NMR data prove that all tryptophan residues are in a non-native environment in the intermediate, indicating substantial changes in the tertiary structure. Still, the intermediate possesses quite a high stability for a transition intermediate of about Delta G = -22 kJ mol(-1).
Understanding changes in biodiversity in agricultural landscapes in relation to land-use type and intensity is a major issue in current ecological research. In this context nutrient enrichment has been identified as a key mechanism inducing species loss in Central European grassland ecosystems. At the same time, insights into the linkage between agricultural land use and plant nutrient status are largely missing. So far, studies on the relationship between chemical composition of plant community biomass and biodiversity have mainly been restricted to wetlands and all these studies neglected the effects of land use. Therefore, we analyzed aboveground biomass of 145 grassland plots covering a gradient of land-use intensities in three regions across Germany. In particular, we explored relationships between vascular plant species richness and nutrient concentrations as well as fibre contents (neutral and acid detergent fibre and lignin) in the aboveground community biomass.
We found the concentrations of several nutrients in the biomass to be closely linked to plant species richness and land use. Whereas phosphorus concentrations increased with land-use intensity and decreased with plant species richness, nitrogen and potassium concentrations showed less clear patterns. Fibre fractions were negatively related to nutrient concentrations in biomass, but hardly to land-use measures and species richness. Only high lignin contents were positively associated with species richness of grasslands. The N:P ratio was strongly positively related to species richness and even more so to the number of endangered plant species, indicating a higher persistence of endangered species under P (co-)limited conditions. Therefore, we stress the importance of low P supply for species-rich grasslands and suggest the N:P ratio in community biomass to be a useful proxy of the conservation value of agriculturally used grasslands.
Trait-based studies have become extremely common in plant ecology. Trait-based approaches often rely on the tacit assumption that intraspecific trait variability (ITV) is negligible compared to interspecific variability, so that species can be characterized by mean trait values. Yet, numerous recent studies have challenged this assumption by showing that ITV significantly affects various ecological processes. Accounting for ITV may thus strengthen trait-based approaches, but measuring trait values on a large number of individuals per species and site is not feasible. Therefore, it is important and timely to synthesize existing knowledge on ITV in order to (1) decide critically when ITV should be considered, and (2) establish methods for incorporating this variability. Here we propose a practical set of rules to identify circumstances under which ITV should be accounted for. We formulate a spatial trait variance partitioning hypothesis to highlight the spatial scales at which ITV cannot be ignored in ecological studies. We then refine a set of four consecutive questions on the research question, the spatial scale, the sampling design, and the type of studied traits, to determine case-by-case if a given study should quantify ITV and test its effects. We review methods for quantifying ITV and develop a step-by-step guideline to design and interpret simulation studies that test for the importance of ITV. Even in the absence of quantitative knowledge on ITV, its effects can be assessed by varying trait values within species within realistic bounds around the known mean values. We finish with a discussion of future requirements to further incorporate ITV within trait-based approaches. This paper thus delineates a general framework to account for ITV and suggests a direction towards a more quantitative trait-based ecology.
The inversion of the flexible five-membered ring in tetrahydrodicyclopentadiene (TH-DCPD) derivatives remains fast on the NMR timescale even at 103 K. Since the intramolecular exchange process could not be sufficiently slowed for spectroscopic evaluation, the conformational equilibrium is thus inaccessible by dynamic NMR. Fortunately, the spatial magnetic properties of the aryl and carbonyl groups attached to the DCPD skeleton can be employed in order to evaluate the conformational state of the system. In this context, the anisotropic effects of the functional groups in the H-1 NMR spectra prove to be the molecular response property of spatial nucleus independent chemical shifts (NICS).
Understanding and predicting the composition and spatial structure of communities is a central challenge in ecology. An important structural property of animal communities is the distribution of individual home ranges. Home range formation is controlled by resource heterogeneity, the physiology and behaviour of individual animals, and their intra- and interspecific interactions. However, a quantitative mechanistic understanding of how home range formation influences community composition is still lacking. To explore the link between home range formation and community composition in heterogeneous landscapes we combine allometric relationships for physiological properties with an algorithm that selects optimal home ranges given locomotion costs, resource depletion and competition in a spatially-explicit individual-based modelling framework. From a spatial distribution of resources and an input distribution of animal body mass, our model predicts the size and location of individual home ranges as well as the individual size distribution (ISD) in an animal community. For a broad range of body mass input distributions, including empirical body mass distributions of North American and Australian mammals, our model predictions agree with independent data on the body mass scaling of home range size and individual abundance in terrestrial mammals. Model predictions are also robust against variation in habitat productivity and landscape heterogeneity. The combination of allometric relationships for locomotion costs and resource needs with resource competition in an optimal foraging framework enables us to scale from individual properties to the structure of animal communities in heterogeneous landscapes. The proposed spatially-explicit modelling concept not only allows for detailed investigation of landscape effects on animal communities, but also provides novel insights into the mechanisms by which resource competition in space shapes animal communities.
Standing stocks are typically easier to measure than process rates such as production. Hence, stocks are often used as indicators of ecosystem functions although the latter are generally more strongly related to rates than to stocks. The regulation of stocks and rates and thus their variability over time may differ, as stocks constitute the net result of production and losses. Based on long-term high frequency measurements in a large, deep lake we explore the variability patterns in primary and bacterial production and relate them to those of the corresponding standing stocks, i.e. chlorophyll concentration, phytoplankton and bacterial biomass. We employ different methods (coefficient of variation, spline fitting and spectral analysis) which complement each other for assessing the variability present in the plankton data, at different temporal scales. In phytoplankton, we found that the overall variability of primary production is dominated by fluctuations at low frequencies, such as the annual, whereas in stocks and chlorophyll in particular, higher frequencies contribute substantially to the overall variance. This suggests that using standing stocks instead of rate measures leads to an under- or overestimation of food shortage for consumers during distinct periods of the year. The range of annual variation in bacterial production is 8 times greater than biomass, showing that the variability of bacterial activity (e.g. oxygen consumption, remineralisation) would be underestimated if biomass is used. The P/B ratios were variable and although clear trends are present in both bacteria and phytoplankton, no systematic relationship between stock and rate measures were found for the two groups. Hence, standing stock and process rate measures exhibit different variability patterns and care is needed when interpreting the mechanisms and implications of the variability encountered.
To gain a deeper understanding of the mechanisms behind biomass accumulation, it is important to study plant growth behavior. Manually phenotyping large sets of plants requires important human resources and expertise and is typically not feasible for detection of weak growth phenotypes. Here, we established an automated growth phenotyping pipeline for Arabidopsis thaliana to aid researchers in comparing growth behaviors of different genotypes.
The analysis pipeline includes automated image analysis of two-dimensional digital plant images and evaluation of manually annotated information of growth stages. It employs linear mixed-effects models to quantify genotype effects on total rosette area and relative leaf growth rate (RLGR) and ANOVAs to quantify effects on developmental times.
Using the system, a single researcher can phenotype up to 7000 plants d(-1). Technical variance is very low (typically < 2%). We show quantitative results for the growth-impaired starch-excessmutant sex4-3 and the growth-enhancedmutant grf9.
We show that recordings of environmental and developmental variables reduce noise levels in the phenotyping datasets significantly and that careful examination of predictor variables (such as d after sowing or germination) is crucial to avoid exaggerations of recorded phenotypes and thus biased conclusions.
Genome sequencing of closely related individuals has yielded valuable insights that link genome evolution to phenotypic variations. However, advancement in sequencing technology has also led to an escalation in the number of poor quality-drafted genomes assembled based on reference genomes that can have highly divergent or haplotypic regions. The self-fertilizing nature of Arabidopsis thaliana poses an advantage to sequencing projects because its genome is mostly homozygous. To determine the accuracy of an Arabidopsis drafted genome in less conserved regions, we performed a resequencing experiment on a similar to 371-kb genomic interval in the Landsberg erecta (Ler-0) accession. We identified novel structural variations (SVs) between Ler-0 and the reference accession Col-0 using a long-range polymerase chain reaction approach to generate an Illumina data set that has positional information, that is, a data set with reads that map to a known location. Positional information is important for accurate genome assembly and the resolution of SVs particularly in highly duplicated or repetitive regions. Sixty-one regions with misassembly signatures were identified from the Ler-0 draft, suggesting the presence of novel SVs that are not represented in the draft sequence. Sixty of those were resolved by iterative mapping using our data set. Fifteen large indels (> 100 bp) identified from this study were found to be located either within protein-coding regions or upstream regulatory regions, suggesting the formation of novel alleles or altered regulation of existing genes in Ler-0. We propose future genome-sequencing experiments to follow a clone-based approach that incorporates positional information to ultimately reveal haplotype-specific differences between accessions.