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The main objective of this study was to identify genomic regions involved in biomass heterosis using QTL, generation means, and mode-of-inheritance classification analyses. In a modified North Carolina Design III we backcrossed 429 recombinant inbred line and 140 introgression line populations to the two parental accessions, C24 and Col-0, whose F 1 hybrid exhibited 44% heterosis for biomass. Mid-parent heterosis in the RILs ranged from −31 to 99% for dry weight and from −58 to 143% for leaf area. We detected ten genomic positions involved in biomass heterosis at an early developmental stage, individually explaining between 2.4 and 15.7% of the phenotypic variation. While overdominant gene action was prevalent in heterotic QTL, our results suggest that a combination of dominance, overdominance and epistasis is involved in biomass heterosis in this Arabidopsis cross.
Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers
(2009)
A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected.
‘Heterosis’ is a term used in genetics and breeding referring to hybrid vigour or the superiority of hybrids over their parents in terms of traits such as size, growth rate, biomass, fertility, yield, nutrient content, disease resistance or tolerance to abiotic and abiotic stress. Parental plants which are two different inbred (pure) lines that have desired traits are crossed to obtain hybrids. Maximum heterosis is observed in the first generation (F1) of crosses. Heterosis has been utilised in plant and animal breeding programs for at least 90 years: by the end of the 21st century, 65% of worldwide maize production was hybrid-based. Generally, it is believed that an understanding of the molecular basis of heterosis will allow the creation of new superior genotypes which could either be used directly as F1 hybrids or form the basis for the future breeding selection programmes. Two selected accessions of a research model plant Arabidopsis thaliana (thale cress) were crossed to obtain hybrids. These typically exhibited a 60-80% increase of biomass when compared to the average weight of both parents. This PhD project focused on investigating the role of selected regulatory genes given their potentially key involvement in heterosis. In the first part of the project, the most appropriate developmental stage for this heterosis study was determined by metabolite level measurements and growth observations in parents and hybrids. At the selected stage, around 60 candidate regulatory genes (i.e. differentially expressed in hybrids when compared to parents) were identified. Of these, the majority were transcription factors, genes that coordinate the expression of other genes. Subsequent expression analyses of the candidate genes in biomass-heterotic hybrids of other Arabidopsis accessions revealed a differential expression in a gene subset, highlighting their relevance for heterosis. Moreover, a fraction of the candidate regulatory genes were found within DNA regions closely linked to the genes that underlie the biomass or growth heterosis. Additional analyses to validate the role of selected candidate regulatory genes in heterosis appeared insufficient to establish their role in heterosis. This uncovered a need for using novel approaches as discussed in the thesis. Taken together, the work provided an insight into studies on the molecular mechanisms underlying heterosis. Although studies on heterosis date back to more than one hundred years, this project as many others revealed that more investigations will be needed to uncover this phenomenon.
Myrmecochory, i.e. dispersal of seeds by ants towards and around their nests, plays an important role in temperate forests. Yet hardly any study has examined plant population spread over several years and the underlying joint contribution of a hierarchy of dispersal modes and plant demography. We used a seed-sowing approach with three replicates to examine colonization patterns of Melampyrum pratense, an annual myrmecochorous herb, in a mixed Scots pine forest in northeastern Germany. Using a spatially explicit individualbased (SEIB) model population patterns over 4 years were explained by short-distance transport of seeds by small ant species with high nest densities, resulting in random spread. However, plant distributions in the field after another 4 years were clearly deviating from model predictions. Mean annual spread rate increased from 0.9 m to 5.1 m per year, with a clear inhomogeneous component. Obviously, after a lag-phase of several years, non-random seed dispersal by large red wood ants (Formica rufa) was determining the species’ spread, thus resulting in stratified dispersal due to interactions with different-sized ant species. Hypotheses on stratified dispersal, on dispersal lag, and on non-random dispersal were verified using an extended SEIB model, by comparison of model outputs with field patterns (individual numbers, population areas, and maximum distances). Dispersal towards red wood ant nests together with seed loss during transport and redistribution around nests were essential features of the model extension. The observed lag-phase in the initiation of non-random, medium-distance transport was probably due to a change of ant behaviour towards a new food source of increasing importance, being a meaningful example for a lag-phase in local plant species invasion. The results demonstrate that field studies should check model predictions wherever possible. Future research will show whether or not the M. pratense–ant system is representative for migration patterns of similar animal dispersal systems after having crossed range edges by long-distance dispersal events.
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.
The phenolamines octopamine and tyramine control, regulate, and modulate many physiological and behavioral processes in invertebrates. Vertebrates possess only small amounts of both substances, and thus, octopamine and tyramine, together with other biogenic amines, are referred to as “trace amines.” Biogenic amines evoke cellular responses by activating G-protein-coupled receptors. We have isolated a complementary DNA (cDNA) that encodes a biogenic amine receptor from the American cockroach Periplaneta americana, viz., Peatyr1, which shares high sequence similarity to members of the invertebrate tyramine-receptor family. The PeaTYR1 receptor was stably expressed in human embryonic kidney (HEK) 293 cells, and its ligand response has been examined. Receptor activation with tyramine reduces adenylyl cyclase activity in a dose-dependent manner (EC50 350 nM). The inhibitory effect of tyramine is abolished by co-incubation with either yohimbine or chlorpromazine. Receptor expression has been investigated by reverse transcription polymerase chain reaction and immunocytochemistry. The mRNA is present in various tissues including brain, salivary glands, midgut, Malpighian tubules, and leg muscles. The effect of tyramine on salivary gland acinar cells has been investigated by intracellular recordings, which have revealed excitatory presynaptic actions of tyramine. This study marks the first comprehensive molecular, pharmacological, and functional characterization of a tyramine receptor in the cockroach.
Background: Biological systems adapt to changing environments by reorganizing their cellula r and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underl ying metabolic network. Methodology/Principal Findings: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic conditiondependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple ob servation s about the changes of metabolic concentrations. The approach was tested with Escherichia colias a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diau xie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical path ways, and (3) ind ependently of the response scale, based on their importance in the reorganization of the cor relation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. Conclusions/Significance: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-ba sed approach does not rely on major changes in concentration to identify metabolites important for st ress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches.
The study of non-coding RNA genes has received increased attention in recent years fuelled by accumulating evidence that larger portions of genomes than previously acknowledged are transcribed into RNA molecules of mostly unknown function, as well as the discovery of novel non-coding RNA types and functional RNA elements. Here, we demonstrate that specific properties of graphs that represent the predicted RNA secondary structure reflect functional information. We introduce a computational algorithm and an associated web-based tool (GraPPLE) for classifying non-coding RNA molecules as functional and, furthermore, into Rfam families based on their graph properties. Unlike sequence-similarity-based methods and covariance models, GraPPLE is demonstrated to be more robust with regard to increasing sequence divergence, and when combined with existing methods, leads to a significant improvement of prediction accuracy. Furthermore, graph properties identified as most informative are shown to provide an understanding as to what particular structural features render RNA molecules functional. Thus, GraPPLE may offer a valuable computational filtering tool to identify potentially interesting RNA molecules among large candidate datasets.
A macro-tidal freshwater ecosystem recovering from hypereutrophication : the Schelde lease study
(2009)
We report a 40 year record of eutrophication and hypoxia on an estuarine ecosystem and its recovery from hypereutrophication. After decades of high inorganic nutrient concentrations and recurring anoxia and hypoxia, we observe a paradoxical increase in chlorophyll-a concentrations with decreasing nutrient inputs. We hypothesise that algal growth was inhibited due to hypereutrophication, either by elevated ammonium concentrations, severe hypoxia or the production of harmful substances in such a reduced environment. We study the dynamics of a simple but realistic mathematical model, incorporating the assumption of algal growth inhibition. It shows a high algal biomass, net oxygen production equilibrium with low ammonia inputs, and a low algal biomass, net oxygen consumption equilibrium with high ammonia inputs. At intermediate ammonia inputs it displays two alternative stable states. Although not intentional, the numerical output of this model corresponds to observations, giving extra support for assumption of algal growth inhibition. Due to potential algal growth inhibition, the recovery of hypereutrophied systems towards a classical eutrophied state, will need reduction of waste loads below certain thresholds and will be accompanied by large fluctuations in oxygen concentrations. We conclude that also flow-through systems, heavily influenced by external forcings which partly mask internal system dynamics, can display multiple stable states.
Background: Multidirectional interactions in social networks can have a profound effect on mate choice behavior; e.g., Poecilia mexicana males show weaker expression of mating preferences when being observed by a rival. This may be an adaptation to reduce sperm competition risk, which arises because commonly preferred female phenotypes will receive attention also from surrounding males, and/or because other males can copy the focal male's mate choice. Do P. mexicana males indeed respond to perceived sperm competition risk? We gave males a choice between two females and repeated the tests under one of the following conditions: (1) an empty transparent cylinder was presented (control); (2) another ("audience") male inside the cylinder observed the focal male throughout the 2nd part, or (3) the audience male was presented only before the tests, but could not eavesdrop during the actual choice tests (non-specific sperm competition risk treatments); (4) the focal male could see a rival male interact sexually with the previously preferred, or (5) with the non-preferred female before the 2nd part of the tests (specific sperm competition risk treatments). Results: The strength of individual male preferences declined slightly also during the control treatment (1). However, this decrease was more than two-fold stronger in audience treatment (2), i.e., with non-specific sperm competition risk including the possibility for visual eavesdropping by the audience male. No audience effect was found in treatments (3) and (5), but a weak effect was also observed when the focal male had seen the previously preferred female sexually interact with a rival male (treatment 4; specific sperm competition risk). Conclusion: When comparing the two 'non-specific sperm competition risk' treatments, a very strong effect was found only when the audience male could actually observe the focal male during mate choice [treatment (2)]. This suggests that focal males indeed attempt to conceal their mating preferences so as to prevent surrounding males from copying their mate choice. When there is no potential for eavesdropping [treatment (3)], non-specific specific sperm competition risk seems to play a minor or no role. Our results also show that P. mexicana males tend to share their mating effort more equally among females when the resource value of their previously preferred mate decreases after mating with a rival male (perceived specific sperm competition risk), but this effect is comparatively weak.
Background: Hybrids represent a cornerstone in the success story of breeding programs. The fundamental principle underlying this success is the phenomenon of hybrid vigour, or heterosis. It describes an advantage of the offspring as compared to the two parental lines with respect to parameters such as growth and resistance against abiotic or biotic stress. Dominance, overdominance or epistasis based models are commonly used explanations. Conclusion/Significance: The heterosis level is clearly a function of the combination of the parents used for offspring production. This results in a major challenge for plant breeders, as usually several thousand combinations of parents have to be tested for identifying the best combinations. Thus, any approach to reliably predict heterosis levels based on properties of the parental lines would be highly beneficial for plant breeding. Methodology/Principal Findings: Recently, genetic data have been used to predict heterosis. Here we show that a combination of parental genetic and metabolic markers, identified via feature selection and minimum-description-length based regression methods, significantly improves the prediction of biomass heterosis in resulting offspring. These findings will help furthering our understanding of the molecular basis of heterosis, revealing, for instance, the presence of nonlinear genotype-phenotype relationships. In addition, we describe a possible approach for accelerated selection in plant breeding.
Background: Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites. Results: We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information. Conclusion: While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structurebased P-site prediction method has been made available at http://phos3d.mpimp-golm.mpg.de.
Background: The EXO (EXORDIUM) gene was identified as a potential mediator of brassinosteroid (BR)-promoted growth. It is part of a gene family with eight members in Arabidopsis. EXO gene expression is under control of BR, and EXO overexpression promotes shoot and root growth. In this study, the consequences of loss of EXO function are described. Results: The exo loss of function mutant showed diminished leaf and root growth and reduced biomass production. Light and scanning electron microscopy analyses revealed that impaired leaf growth is due to reduced cell expansion. Epidermis, palisade, and spongy parenchyma cells were smaller in comparison to the wild-type. The exo mutant showed reduced brassinolide-induced cotyledon and hypocotyl growth. In contrast, exo roots were significantly more sensitive to the inhibitory effect of synthetic brassinolide. Apart from reduced growth, exo did not show severe morphological abnormalities. Gene expression analyses of leaf material identified genes that showed robust EXO-dependent expression. Growth-related genes such as WAK1, EXP5, and KCS1, and genes involved in primary and secondary metabolism showed weaker expression in exo than in wild-type plants. However, the vast majority of BR-regulated genes were normally expressed in exo. HA- and GFP-tagged EXO proteins were targeted to the apoplast. Conclusion: The EXO gene is essential for cell expansion in leaves. Gene expression patterns and growth assays suggest that EXO mediates BR-induced leaf growth. However, EXO does not control BR-levels or BR-sensitivity in the shoot. EXO presumably is involved in a signalling process which coordinates BR-responses with environmental or developmental signals. The hypersensitivity of exo roots to BR suggests that EXO plays a diverse role in the control of BR responses in the root.
Arabidopsis thaliana HYL1 is a nuclear doublestranded RNA-binding protein involved in the maturation of pri-miRNAs. A quantitative real-time PCR platform for parallel quantification of 176 primiRNAs was used to reveal strong accumulation of 57 miRNA precursors in the hyl1 mutant that completely lacks HYL1 protein. This approach enabled us for the first time to pinpoint particular members of MIRNA family genes that require HYL1 activity for efficient maturation of their precursors. Moreover, the accumulation of miRNA precursors in the hyl1 mutant gave us the opportunity to carry out 3’ and 5’ RACE experiments which revealed that some of these precursors are of unexpected length. The alignment of HYL1- dependent miRNA precursors to A. thaliana genomic sequences indicated the presence of introns in 12 out of 20 genes studied. Some of the characterized intron-containing pri-miRNAs undergo alternative splicing such as exon skipping or usage of alternative 5’ splice sites suggesting that this process plays a role in the regulation of miRNA biogenesis. In the hyl1 mutant intron-containing pri-miRNAs accumulate alongside spliced primiRNAs suggesting the recruitment of HYL1 into the miRNA precursor maturation pathway before their splicing occurs.
The GABI Primary Database, GabiPD (http:// www.gabipd.org/), was established in the frame of the German initiative for Genome Analysis of the Plant Biological System (GABI). The goal of GabiPD is to collect, integrate, analyze and visualize primary information from GABI projects. GabiPD constitutes a repository and analysis platform for a wide array of heterogeneous data from high-throughput experiments in several plant species. Data from different ‘omics’ fronts are incorporated (i.e. genomics, transcriptomics, proteomics and metabolomics), originating from 14 different model or crop species. We have developed the concept of GreenCards for textbased retrieval of all data types in GabiPD (e.g. clones, genes, mutant lines). All data types point to a central Gene GreenCard, where gene information is integrated from genome projects or NCBI UniGene sets. The centralized Gene GreenCard allows visualizing ESTs aligned to annotated transcripts as well as displaying identified protein domains and gene structure. Moreover, GabiPD makes available interactive genetic maps from potato and barley, and protein 2DE gels from Arabidopsis thaliana and Brassica napus. Gene expression and metabolic-profiling data can be visualized through MapManWeb. By the integration of complex data in a framework of existing knowledge, GabiPD provides new insights and allows for new interpretations of the data.
Site directed mutagenesis of amino acid residues at the active site of mouse aldehyde oxidase AOX1
(2009)
Mouse aldehyde oxidase (mAOX1) forms a homodimer and belongs to the xanthine oxidase family of molybdoenzymes which are characterized by an essential equatorial sulfur ligand coordinated to the molybdenum atom. In general, mammalian AOs are characterized by broad substrate specificity and an yet obscure physiological function. To define the physiological substrates and the enzymatic characteristics of mAOX1, we established a system for the heterologous expression of the enzyme in Eschericia coli. The recombinant protein showed spectral features and a range of substrate specificity similar to the native protein purified from mouse liver. The EPR data of recombinant mAOX1 were similar to those of AO from rabbit liver, but differed from the homologous xanthine oxidoreductase enzymes. Site-directed mutagenesis of amino acids Val806, Met884 and Glu1265 at the active site resulted in a drastic decrease in the oxidation of aldehydes with no increase in the oxidation of purine substrates. The double mutant V806E/M884R and the single mutant E1265Q were catalytically inactive enzymes regardless of the aldehyde or purine substrates tested. Our results show that only Glu1265 is essential for the catalytic activity by initiating the base-catalyzed mechanism of substrate oxidation. In addition, it is concluded that the substrate specificity of molybdo-flavoenzymes is more complex and not only defined by the three characterized amino acids in the active site.
Background: In Arabidopsis thaliana, the family of cyclic nucleotide-gated channels (CNGCs) is composed of 20 members. Previous studies indicate that plant CNGCs are involved in the control of growth processes and responses to abiotic and biotic stresses. According to their proposed function as cation entry pathways these channels contribute to cellular cation homeostasis, including calcium and sodium, as well as to stress-related signal transduction. Here, we studied the expression patterns and regulation of CNGC19 and CNGC20, which constitute one of the five CNGC subfamilies. Results: GUS, GFP and luciferase reporter assays were used to study the expression of CNGC19 and CNGC20 genes from Arabidopsis thaliana in response to developmental cues and salt stress. CNGC19 and CNGC20 were differentially expressed in roots and shoots. The CNGC19 gene was predominantly active in roots already at early growth stages. Major expression was observed in the phloem. CNGC20 showed highest promoter activity in mesophyll cells surrounding the veins. Its expression increased during development and was maximal in mature and senescent leaves. Both genes were upregulated in the shoot in response to elevated NaCl but not mannitol concentrations. While in the root, CNGC19 did not respond to changes in the salt concentration, in the shoot it was strongly upregulated in the observed time frame (6-72 hours). Salt-induction of CNGC20 was also observed in the shoot, starting already one hour after stress treatment. It occurred with similar kinetics, irrespective of whether NaCl was applied to roots of intact plants or to the petiole of detached leaves. No differences in K and Na contents of the shoots were measured in homozygous T-DNA insertion lines for CNGC19 and CNGC20, respectively, which developed a growth phenotype in the presence of up to 75 mM NaCl similar to that of the wild type. Conclusion: Together, the results strongly suggest that both channels are involved in the salinity response of different cell types in the shoot. Upon salinity both genes are upregulated within hours. CNGC19 and CNGC20 could assist the plant to cope with toxic effects caused by salt stress, probably by contributing to a re-allocation of sodium within the plant.
Synonymous codon usage and variations in the level of isoaccepting tRNAs exert a powerful selective force on translation fidelity. We have developed an algorithm to evaluate the relative rate of translation which allows large-scale comparisons of the non-uniform translation rate on the protein biogenesis. Using the complete genomes of Escherichia coli and Bacillus subtilis we show that stretches of codons pairing to minor tRNAs form putative sites to locally attenuate translation; thereby the tendency is to cluster in near proximity whereas long contiguous stretches of slow-translating triplets are avoided. The presence of slow-translating segments positively correlates with the protein length irrespective of the protein abundance. The slow-translating clusters are predominantly located down-stream of the domain boundaries presumably to fine-tune translational accuracy with the folding fidelity of multidomain proteins. Translation attenuation patterns at highly structurally and functionally conserved domains are preserved across the species suggesting a concerted selective pressure on the codon selection and species-specific tRNA abundance in these regions.
The ability of an organism to survive depends on its capability to adapt to external conditions. In addition to metabolic versatility and efficient replication, reliable signal transduction is essential. As signaling systems are under permanent evolutionary pressure one may assume that their structure reflects certain functional properties. However, despite promising theoretical studies in recent years, the selective forces which shape signaling network topologies in general remain unclear. Here, we propose prevention of autoactivation as one possible evolutionary design principle. A generic framework for continuous kinetic models is used to derive topological implications of demanding a dynamically stable ground state in signaling systems. To this end graph theoretical methods are applied. The index of the underlying digraph is shown to be a key topological property which determines the so-called kinetic ground state (or off-state) robustness. The kinetic robustness depends solely on the composition of the subdigraph with the strongly connected components, which comprise all positive feedbacks in the network. The component with the highest index in the feedback family is shown to dominate the kinetic robustness of the whole network, whereas relative size and girth of these motifs are emphasized as important determinants of the component index. Moreover, depending on topological features, the maintenance of robustness differs when networks are faced with structural perturbations. This structural off-state robustness, defined as the average kinetic robustness of a network’s neighborhood, turns out to be useful since some structural features are neutral towards kinetic robustness, but show up to be supporting against structural perturbations. Among these are a low connectivity, a high divergence and a low path sum. All results are tested against real signaling networks obtained from databases. The analysis suggests that ground state robustness may serve as a rationale for some structural peculiarities found in intracellular signaling networks.
We propose two strategies to characterize organisms with respect to their metabolic capabilities. The first, investigative, strategy describes metabolic networks in terms of their capability to utilize different carbon sources, resulting in the concept of carbon utilization spectra. In the second, predictive, approach minimal nutrient combinations are predicted from the structure of the metabolic networks, resulting in a characteristic nutrient profile. Both strategies allow for a quantification of functional properties of metabolic networks, allowing to identify groups of organisms with similar functions. We investigate whether the functional description reflects the typical environments of the corresponding organisms by dividing all species into disjoint groups based on whether they are aerotolerant and/or photosynthetic. Despite differences in the underlying concepts, both measures display some common features. Closely related organisms often display a similar functional behavior and in both cases the functional measures appear to correlate with the considered classes of environments. Carbon utilization spectra and nutrient profiles are complementary approaches toward a functional classification of organism-wide metabolic networks. Both approaches contain different information and thus yield different clusterings, which are both different from the classical taxonomy of organisms. Our results indicate that a sophisticated combination of our approaches will allow for a quantitative description reflecting the lifestyles of organisms.
Background: The loss of photosynthesis has occurred often in eukaryotic evolution, even more than its acquisition, which occurred at least nine times independently and which generated the evolution of the supergroups Archaeplastida, Rhizaria, Chromalveolata and Excavata. This secondary loss of autotrophic capability is essential to explain the evolution of eukaryotes and the high diversity of protists, which has been severely underestimated until recently. However, the ecological and evolutionary scenarios behind this evolutionary ‘‘step back’’ are still largely unknown. Methodology/Principal Findings: Using a dynamic model of heterotrophic and mixotrophic flagellates and two types of prey, large bacteria and ultramicrobacteria, we examine the influence of DOC concentration, mixotroph’s photosynthetic growth rate, and external limitations of photosynthesis on the coexistence of both types of flagellates. Our key premises are: large bacteria grow faster than small ones at high DOC concentrations, and vice versa; and heterotrophic flagellates are more efficient than the mixotrophs grazing small bacteria (both empirically supported). We show that differential efficiency in bacteria grazing, which strongly depends on cell size, is a key factor to explain the loss of photosynthesis in mixotrophs (which combine photosynthesis and bacterivory) leading to purely heterotrophic lineages. Further, we show in what conditions an heterotroph mutant can coexist, or even out-compete, its mixotrophic ancestor, suggesting that bacterivory and cell size reduction may have been major triggers for the diversification of eukaryotes. Conclusions/Significance: Our results suggest that, provided the mixotroph’s photosynthetic advantage is not too large, the (small) heterotroph will also dominate in nutrient-poor environments and will readily invade a community of mixotrophs and bacteria, due to its higher efficiency exploiting the ultramicrobacteria. As carbon-limited conditions were presumably widespread throughout Earth history, such a scenario may explain the numerous transitions from phototrophy to mixotrophy and further to heterotrophy within virtually all major algal lineages. We challenge prevailing concepts that affiliated the evolution of phagotrophy with eutrophic or strongly light-limited environments only.
ChlamyCyc : an integrative systems biology database and web-portal for Chlamydomonas reinhardtii
(2009)
Background: The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern highthroughput technologies there is an imperative need to integrate large-scale data sets from highthroughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism. Results: In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc) was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification. Conclusion: ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under http://chlamycyc.mpimp-golm.mpg.de.
Background: Mitochondrial genomes are a valuable source of data for analysing phylogenetic relationships. Besides sequence information, mitochondrial gene order may add phylogenetically useful information, too. Sipuncula are unsegmented marine worms, traditionally placed in their own phylum. Recent molecular and morphological findings suggest a close affinity to the segmented Annelida. Results: The first complete mitochondrial genome of a member of Sipuncula, Sipunculus nudus, is presented. All 37 genes characteristic for metazoan mtDNA were detected and are encoded on the same strand. The mitochondrial gene order (protein-coding and ribosomal RNA genes) resembles that of annelids, but shows several derivations so far found only in Sipuncula. Sequence based phylogenetic analysis of mitochondrial protein-coding genes results in significant bootstrap support for Annelida sensu lato, combining Annelida together with Sipuncula, Echiura, Pogonophora and Myzostomida. Conclusion: The mitochondrial sequence data support a close relationship of Annelida and Sipuncula. Also the most parsimonious explanation of changes in gene order favours a derivation from the annelid gene order. These results complement findings from recent phylogenetic analyses of nuclear encoded genes as well as a report of a segmental neural patterning in Sipuncula.
Background: Phylogenomic analyses recently became popular to address questions about deep metazoan phylogeny. Ribosomal proteins (RP) dominate many of these analyses or are, in some cases, the only genes included. Despite initial hopes, hylogenomic analyses including tens to hundreds of genes still fail to robustly place many bilaterian taxa. Results: Using the phylogenetic position of myzostomids as an example, we show that phylogenies derived from RP genes and mitochondrial genes produce incongruent results. Whereas the former support a position within a clade of platyzoan taxa, mitochondrial data recovers an annelid affinity, which is strongly supported by the gene order data and is congruent with morphology. Using hypothesis testing, our RP data significantly rejects the annelids affinity, whereas a platyzoan relationship is significantly rejected by the mitochondrial data. Conclusion: We conclude (i) that reliance of a set of markers belonging to a single class of macromolecular complexes might bias the analysis, and (ii) that concatenation of all available data might introduce conflicting signal into phylogenetic analyses. We therefore strongly recommend testing for data incongruence in phylogenomic analyses. Furthermore, judging all available data, we consider the annelid affinity hypothesis more plausible than a possible platyzoan affinity for myzostomids, and suspect long branch attraction is influencing the RP data. However, this hypothesis needs further confirmation by future analyses.
Source, topography and excitatory effects of GABAergic innervation in cockroach salivary glands
(2009)
Cockroach salivary glands are innervated by dopaminergic and serotonergic neurons. Both transmitters elicit saliva secretion. We studied the distribution pattern of neurons containing gamma-aminobutyric acid ( GABA) and their physiological role. Immunofluorescence revealed a GABA-immunoreactive axon that originates within the subesophageal ganglion at the salivary neuron 2 (SN2) and this extends within the salivary duct nerve towards the salivary gland. GABA-positive fibers form a network on most acinar lobules and a dense plexus in the interior of a minor fraction of acinar lobules. Co-staining with anti-synapsin revealed that some putative GABAergic terminals seem to make pre-synaptic contacts with GABA-negative release sites. Many putative GABAergic release sites are at some distance from other synapses and at distance from the acinar tissue. Intracellular recordings from isolated salivary glands have revealed that GABA does not affect the basolateral membrane potential of the acinar cells directly. When applied during salivary duct nerve stimulation, GABA enhances the electrical response of the acinar cells and increases the rates of fluid and protein secretion. The effect on electrical cell responses is mimicked by the GABA(B) receptor agonists baclofen and SKF97541, and blocked by the GABAB receptor antagonists CGP52432 and CGP54626. These findings indicate that GABA has a modulatory role in the control of salivation, acting presynaptically on serotonergic and/or dopaminergic neurotransmission.
About 2,000 of the more than 27,000 genes of the genetic model plant Arabidopsis thaliana encode for transcription factors (TFs), proteins that bind DNA in the promoter region of their target genes and thus act as transcriptional activators and repressors. Since TFs play essential roles in nearly all biological processes, they are of great scientific and biotechnological interest. This thesis concentrated on the functional characterisation of four selected members of the Arabidopsis DOF-family, namely DOF1.2, DOF3.1, DOF3.5 and DOF5.2, which were selected because of their specific expression pattern in the root tip, a region that comprises the stem cell niche and cells for the perception of environmental stimuli. DOF1.2, DOF3.1 and DOF3.5 are previously uncharacterized members of the Arabidopsis DOF-family, while DOF5.2 has been shown to be involved in the phototrophic flowering response. However, its role in root development has not been described so far. To identify biological processes regulated by the four DOF proteins in detail, molecular and physiological characterization of transgenic plants with modified levels of DOF1.2, DOF3.1, DOF3.5 and DOF5.2 expression (constitutive and inducible over-expression, artificial microRNA) was performed. Additionally expression patterns of the TFs and their target genes were analyzed using promoter-GUS lines and publicly available microarray data. Finally putative protein-protein interaction partners and upstream regulating TFs were identified using the yeast two-hybrid and one-hybrid system. This combinatorial approach revealed distinct biological functions of DOF1.2, DOF3.1, DOF3.5 and DOF5.2 in the context of root development. DOF1.2 and DOF3.5 are specifically and exclusively expressed in the root cap, including the central root cap (columella) and the lateral root cap, organs which are essential to direct oriented root growth. It could be demonstrated that both genes work in the plant hormone auxin signaling pathway and have an impact on distal cell differentiation. Altered levels of gene expression lead to changes in auxin distribution, abnormal cell division patterns and altered root growth orientation. DOF3.1 and DOF5.2 share a specific expression pattern in the organizing centre of the root stem cell niche, called the quiescent centre. Both genes redundantly control cell differentiation in the root´s proximal meristem and unravel a novel transcriptional regulation pathway for genes enriched in the QC cells. Furthermore this work revealed a novel bipartite nuclear localisation signal being present in the protein sequence of the DOF TF family from all sequenced plant species. Summing up, this work provides an important input into our knowledge about the role of DOF TFs during root development. Future work will concentrate on revealing the exact regulatory networks of DOF1.2, DOF3.1, DOF3.5 and DOF5.2 and their possible biotechnological applications.
The present thesis aims to introduce process-based model for species range dynamics that can be fitted to abundance data. For this purpose, the well-studied Proteaceae species of the South African Cape Floristic Region (CFR) offer a great data set to fit process-based models. These species are subject to wildflower harvesting and environmental threats like habitat loss and climate change. The general introduction of this thesis presents shortly the available models for species distribution modelling. Subsequently, it presents the feasibility of process-based modelling. Finally, it introduces the study system as well as the objectives and layout. In Chapter 1, I present the process-based model for range dynamics and a statistical framework to fit it to abundance distribution data. The model has a spatially-explicit demographic submodel (describing dispersal, reproduction, mortality and local extinction) and an observation submodel (describing imperfect detection of individuals). The demographic submodel links species-specific habitat models describing the suitable habitat and process-based demographic models that consider local dynamics and anemochoric seed dispersal between populations. After testing the fitting framework with simulated data, I applied it to eight Proteaceae species with different demographic properties. Moreover, I assess the role of two other demographic mechanisms: positive (Allee effects) and negative density-dependence. Results indicate that Allee effects and overcompensatory local dynamics (including chaotic behaviour) seem to be important for several species. Most parameter estimates quantitatively agreed with independent data. Hence, the presented approach seemed to suit the demand of investigating non-equilibrium scenarios involving wildflower harvesting (Chapter 2) and environmental change (Chapter 3). The Chapter 2 addresses the impacts of wildflower harvesting. The chapter includes a sensitivity analysis over multiple spatial scales and demographic properties (dispersal ability, strength of Allee effects, maximum reproductive rate, adult mortality, local extinction probability and carrying capacity). Subsequently, harvesting effects are investigated on real case study species. Plant response to harvesting showed abrupt threshold behavior. Species with short-distance seed dispersal, strong Allee effects, low maximum reproductive rate, high mortality and high local extinction are most affected by harvesting. Larger spatial scales benefit species response, but the thresholds become sharper. The three case study species supported very low to moderate harvesting rates. Summarizing, demographic knowledge about the study system and careful identification of the spatial scale of interest should guide harvesting assessments and conservation of exploited species. The sensitivity analysis’ results can be used to qualitatively assess harvesting impacts for poorly studied species. I investigated in Chapter 3 the consequences of past habitat loss, future climate change and their interaction on plant response. I use the species-specific estimates of the best model describing local dynamics obtained in Chapter 1. Both habitat loss and climate change had strong negative impacts on species dynamics. Climate change affected mainly range size and range filling due to habitat reductions and shifts combined with low colonization. Habitat loss affected mostly local abundances. The scenario with both habitat loss and climate change was the worst for most species. However, this impact was better than expected by simple summing of separate effects of habitat loss and climate change. This is explained by shifting ranges to areas less affected by humans. Range size response was well predicted by the strength of environmental change, whereas range filling and local abundance responses were better explained by demographic properties. Hence, risk assessments under global change should consider demographic properties. Most surviving populations were restricted to refugia, serving as key conservation focus.The findings obtained for the study system as well as the advantages, limitations and potentials of the model presented here are further discussed in the General Discussion. In summary, the results indicate that 1) process-based demographic models for range dynamics can be fitted to data; 2) demographic processes improve species distribution models; 3) different species are subject to different processes and respond differently to environmental change and exploitation; 4) density regulation type and Allee effects should be considered when investigating range dynamics of species; 5) the consequences of wildflower harvesting, habitat loss and climate change could be disastrous for some species, but impacts vary depending on demographic properties; 6) wildflower harvesting impacts varies over spatial scale; 7) The effects of habitat loss and climate change are not always additive.
Leaves are the main photosynthetic organs of vascular plants, and leaf development is dependent on a proper control of gene expression. Transcription factors (TFs) are global regulators of gene expression that play essential roles in almost all biological processes among eukaryotes. This PhD project focused on the characterization of the sink-to-source transition of Arabidopsis leaves and on the analysis of TFs that play a role in early leaf development. The sink-to-source transition occurs when the young emerging leaves (net carbon importers) acquire a positive photosynthetic balance and start exporting photoassimilates. We have established molecular and physiological markers (i.e., CAB1 and CAB2 expression levels, AtSUC2 and AtCHoR expression patterns, chlorophyll and starch levels, and photosynthetic electron transport rates) to identify the starting point of the transition, especially because the sink-to-source is not accompanied by a visual phenotype in contrast to other developmental transitions, such as the mature-to-senescent transition of leaves. The sink-to-source transition can be divided into two different processes: one light dependent, related to photosynthesis and light responses; and one light independent or impaired, related to the changes in the vascular tissue that occur when leaves change from an import to an export mode. Furthermore, starch, but not sucrose, has been identified as one of the potential signalling molecules for this transition. The expression level of 1880 TFs during early leaf development was assessed by qRTPCR, and 153 TFs were found to exhibit differential expression levels of at least 5-fold. GRF, MYB and SRS are TF families, which are overrepresented among the differentially expressed TFs. Additionally, processes like cell identity acquisition, formation of the epidermis and leaf development are overrepresented among the differentially expressed TFs, which helps to validate the results obtained. Two of these TFs were further characterized. bZIP21 is a gene up-regulated during the sink-to-source and mature-to-senescent transitions. Its expression pattern in leaves overlaps with the one observed for AtCHoR, therefore it constitutes a good marker for the sink-to-source transition. Homozygous null mutants of bZIP21 could not be obtained, indicating that the total absence of bZIP21 function may be lethal to the plant. Phylogenetic analyses indicate that bZIP21 is an orthologue of Liguleless2 from maize. In these analyses, we identified that the whole set of bZIPs in plants originated from four founder genes, and that all bZIPs from angiosperms can be classified into 13 groups of homologues and 34 Possible Groups of Orthologues (PoGOs). bHLH64 is a gene highly expressed in early sink leaves, its expression is downregulated during the mature-to-senescent transition. Null mutants of bHLH64 are characterized by delayed bolting when compared to the wild-type; this indicates a possible delay in the sink-to-source transition or the retention of a juvenile identity. A third TF, Dof4, was also characterized. Dof4 is neither differentially expressed during the sink-to-source nor during the senescent-to-mature transition, but a null mutant of Dof4 develops bigger leaves than the wild-type and forms a greater number of siliques. The Dof4 null mutant has proven to be a good background for biomass accumulation analysis. Though not overrepresented during the sink-to-source transition, NAC transcription factors seem to contribute significantly to the mature-to-senescent transition. Twenty two NACs from Arabidopsis and 44 from rice are differentially expressed during late stages of leaf development. Phylogenetic analyses revealed that most of these NACs cluster into three big groups of homologues, indicating functional conservation between eudicots and monocots. To prove functional conservation of orthologues, the expression of ten NAC genes of barley was analysed. Eight of the ten NAC genes were found to be differentially expressed during senescence. The use of evolutionary approaches combined with functional studies is thus expected to support the transfer of current knowledge of gene control gained in model species to crops.
For the elucidation of the dynamics of signal transduction processes that are induced by cellular interactions, defined events along the signal transduction cascade and subsequent activation steps have to be analyzed and then also correlated with each other. This cannot be achieved by ensemble measurements because averaging biological data ignores the variability in timing and response patterns of individual cells and leads to highly blurred results. Instead, only a multi-parameter analysis at a single-cell level is able to exploit the information that is crucially needed for deducing the signaling pathways involved. The aim of this work was to develop a process line that allows the initiation of cell-cell or cell-particle interactions while at the same time the induced cellular reactions can be analyzed at various stages along the signal transduction cascade and correlated with each other. As this approach requires the gentle management of individually addressable cells, a dielectrophoresis (DEP)-based microfluidic system was employed that provides the manipulation of microscale objects with very high spatiotemporal precision and without the need of contacting the cell membrane. The system offers a high potential for automation and parallelization. This is essential for achieving a high level of robustness and reproducibility, which are key requirements in order to qualify this approach for a biomedical application. As an example process for intercellular communication, T cell activation has been chosen. The activation of the single T cells was triggered by contacting them individually with microbeads that were coated with antibodies directed against specific cell surface proteins, like the T cell receptor-associated kinase CD3 and the costimulatory molecule CD28 (CD; cluster of differentiation). The stimulation of the cells with the functionalized beads led to a rapid rise of their cytosolic Ca2+ concentration which was analyzed by a dual-wavelength ratiometric fluorescence measurement of the Ca2+-sensitive dye Fura-2. After Ca2+ imaging, the cells were isolated individually from the microfluidic system and cultivated further. Cell division and expression of the marker molecule CD69 as a late activation event of great significance were analyzed the following day and correlated with the previously recorded Ca2+ traces for each individual cell. It turned out such that the temporal profile of the Ca2+ traces between both activated and non-activated cells as well as dividing and non-dividing cells differed significantly. This shows that the pattern of Ca2+ signals in T cells can provide early information about a later reaction of the cell. As isolated cells are highly delicate objects, a precondition for these experiments was the successful adaptation of the system to maintain the vitality of single cells during and after manipulation. In this context, the influences of the microfluidic environment as well as the applied electric fields on the vitality of the cells and the cytosolic Ca2+ concentration as crucially important physiological parameters were thoroughly investigated. While a short-term DEP manipulation did not affect the vitality of the cells, they showed irregular Ca2+ transients upon exposure to the DEP field only. The rate and the strength of these Ca2+ signals depended on exposure time, electric field strength and field frequency. By minimizing their occurrence rate, experimental conditions were identified that caused the least interference with the physiology of the cell. The possibility to precisely control the exact time point of stimulus application, to simultaneously analyze short-term reactions and to correlate them with later events of the signal transduction cascade on the level of individual cells makes this approach unique among previously described applications and offers new possibilities to unravel the mechanisms underlying intercellular communication.
Dispersal behavior plays an important role for the geographical distribution and population structure of any given species. Individual’s fitness, reproductive and competitive ability, and dispersal behavior can be determined by the age of the individual. Age-dependent as well as density-dependent dispersal patterns are common in many bird species. In this thesis, I first present age-dependent breeding ability and natal site fidelity in white storks (Ciconia ciconia); migratory birds breeding in large parts of Europe. I predicted that both the proportion of breeding birds and natal site fidelity increase with the age. After the seventies of the last century, following a steep population decline, a recovery of the white stork population has been observed in many regions in Europe. Increasing population density in the white stork population in Eastern Germany especially after 1983 allowed examining density- as well as age-dependent breeding dispersal patterns. Therefore second, I present whether: young birds show more often and longer breeding dispersal than old birds, and frequency of dispersal events increase with the population density increase, especially in the young storks. Third, I present age- and density-dependent dispersal direction preferences in the give population. I asked whether and how the major spring migration direction interacts with dispersal directions of white storks: in different age, and under different population densities. The proportion of breeding individuals increased in the first 22 years of life and then decreased suggesting, the senescent decay in aging storks. Young storks were more faithful to their natal sites than old storks probably due to their innate migratory direction and distance. Young storks dispersed more frequently than old storks in general, but not for longer distance. Proportion of dispersing individuals increased significantly with increasing population densities indicating, density- dependent dispersal behavior in white storks. Moreover, the finding of a significant interaction effects between the age of dispersing birds and year (1980–2006) suggesting, older birds dispersed more from their previous nest sites over time due to increased competition. Both young and old storks dispersed along their spring migration direction; however, directional preferences were different in young storks and old storks. Young storks tended to settle down before reaching their previous nest sites (leading to the south-eastward dispersal) while old birds tended to keep migrating along the migration direction after reaching their previous nest sites (leading to the north-westward dispersal). Cues triggering dispersal events may be age-dependent. Changes in the dispersal direction over time were observed. Dispersal direction became obscured during the second half of the observation period (1993–2006). Increase in competition may affect dispersal behavior in storks. I discuss the potential role of: age for the observed age-dependent dispersal behavior, and competition for the density dependent dispersal behavior. This Ph.D. thesis contributes significantly to the understanding of population structure and geographical distribution of white storks. Moreover, presented age- and density (competition)-dependent dispersal behavior helps understanding underpinning mechanisms of dispersal behavior in bird species.
To date, positive relationships between diversity and community biomass have been mainly found, especially in terrestrial ecosystems due to the complementarity and/or dominance effect. In this thesis, the effect of diversity on the performance of terrestrial plant and phytoplankton communities was investigated to get a better understanding of the underlying mechanisms in the biodiversity-ecosystem functioning context. In a large grassland biodiversity experiment, the Jena Experiment, the effect of community diversity on the individual plant performance was investigated for all species. The species pool consisted of 60 plant species belonging to 4 functional groups (grasses, small herbs, tall herbs, legumes). The experiment included 82 large plots which differed in species richness (1-60), functional richness (1-4), and community composition. Individual plant height increased with increasing species richness suggesting stronger competition for light in more diverse communities. The aboveground biomass of the individual plants decreased with increasing species richness indicating stronger competition in more species-rich communities. Moreover, in more species-rich communities plant individuals were less likely to flower out and had fewer inflorescences which may be resulting from a trade-off between resource allocation to vegetative height growth and to reproduction. Responses to changing species richness differed strongly between functional groups and between species of similar functional groups. To conclude, individual plant performance can largely depend on the diversity of the surrounding community. Positive diversity effects on biomass have been mainly found for substrate-bound plant communities. Therefore, the effect of diversity on the community biomass of phytoplankton was studied using microcosms. The communities consisted of 8 algal species belonging to 4 functional groups (green algae, diatoms, cyanobacteria, phytoflagellates) and were grown at different functional richness levels (1-4). Functional richness and community biomass were negatively correlated and all community biomasses were lower than their average monoculture biomasses of the component species, revealing community underyielding. This was mainly caused by the dominance of a fast-growing species which built up low biomasses in monoculture and mixture. A trade-off between biomass and growth rate in monoculture was found for all species, and thus fast-growing species built up low biomasses and slow-growing species reached high biomasses in monoculture. As the fast-growing, low-productive species monopolised nutrients in the mixtures, they became the dominant species resulting in the observed community underyielding. These findings suggest community overyielding when biomasses of the component species are positively correlated with their growth rates in monocultures. Aquatic microcosm experiments with an extensive design were performed to get a broad range of community responses. The phytoplankton communities differed in species diversity (1, 2, 4, 8, and 12), functional diversity (1, 2, 3, and 4) and community composition. The species/functional diversity positively affected community biomass, revealing overyielding in most of the communities. This was mainly caused by a positive complementarity effect which can be attributed to resource use complementarity and/or facilitative interaction among the species. Overyielding of more diverse communities occurred when the biomass of the component species was correlated positively with their growth rates in monoculture and thus, fast-growing and high-productive species were dominant in mixtures. This and the study mentioned above generated an emergent pattern for community overyielding and underyielding from the relationship between biomass and growth rate in monoculture as long as the initial community structure prevailed. Invasive species can largely affect ecosystem processes, whereas invasion is also influenced by diversity. To date, studies revealed negative and positive diversity effects on the invasibility (susceptibility of a community to the invasion by new species). The effect of productivity (nutrient concentration ranging from 10 to 640 µg P L-1), herbivory (presence/absence of the generalist feeder) and diversity (3, 4, 6 species were randomly chosen from the resident species pool) on the invasibility of phytoplankton communities consisting of 10 resident species was investigated using semi-continuous microcosms. Two functionally diverse invaders were chosen: the filamentous and less-edible cynaobacterium C. raciborskii and the unicellular and well-edible phytoflagellate Cryptomonas sp. The phytoflagellate indirectly benefited from grazing pressure of herbivores whereas C. raciborskii suffered more from it. Diversity did not affect the invasibility of the phytoplankton communities. Rather, it was strongly influenced by the functional traits of the resident and invasive species.
Despite general concern that the massive deposits of methane stored under permafrost underground and undersea could be released into the atmosphere due to rising temperatures attributed to global climate change, little is known about the methanogenic microorganisms in permafrost sediments, their role in methane emissions, and their phylogeny. The aim of this thesis was to increase knowledge of uncultivated methanogenic microorganisms in submarine and terrestrial permafrost deposits, their community composition, the role they play with regard to methane emissions, and their phylogeny. It is assumed that methanogenic communities in warmer submarine permafrost may serve as a model to anticipate the response of methanogenic communities in colder terrestrial permafrost to rising temperatures. The compositions of methanogenic communities were examined in terrestrial and submarine permafrost sediment samples. The submarine permafrost studied in this research was 10°C warmer than the terrestrial permafrost. By polymerase chain reaction (PCR), DNA was extracted from each of the samples and analyzed by molecular microbiological methods such as PCR-DGGE, RT-PCR, and cloning. Furthermore, these samples were used for in vitro experiment and FISH. The submarine permafrost analysis of the isotope composition of CH4 suggested a relationship between methane content and in situ active methanogenesis. Furthermore, active methanogenesis was proven using 13C-isotope measurements of methane in submarine permafrost sediment with a high TOC value and a high methane concentration. In the molecular-microbiological studies uncultivated lines of Methanosarcina, Methanomicrobiales, Methanobacteriacea and the Groups 1.3 and Marine Benthic from Crenarchaeota were found in all submarine and terrestrial permafrost samples. Methanosarcina was the dominant group of the Archaea in all submarine and terrestrial permafrost samples. The archaeal community composition, in particular, the methanogenic community composition showed diversity with changes in temperatures. Furthermore, cell count of methanogens in submarine permafrost was 10 times higher than in terrestrial permafrost. In vitro experiments showed that methanogens adapt quickly and well to higher temperatures. If temperatures rise due to climate change, an increase in methanogenic activity can be expected as long as organic material is sufficiently available and qualitatively adequate.
Although the basic structure of biological membranes is provided by the lipid bilayer, most of the specific functions are carried out by membrane proteins (MPs) such as channels, ion-pumps and receptors. Additionally, it is known, that mutations in MPs are directly or indirectly involved in many diseases. Thus, structure determination of MPs is of major interest not only in structural biology but also in pharmacology, especially for drug development. Advances in structural biology of membrane proteins (MPs) have been strongly supported by the success of three leading techniques: X-ray crystallography, electron microscopy and solution NMR spectroscopy. However, X-ray crystallography and electron microscopy, require highly diffracting 3D or 2D crystals, respectively. Today, structure determination of non-crystalline solid protein preparations has been made possible through rapid progress of solid-state MAS NMR methodology for biological systems. Castellani et. al. solved and refined the first structure of a microcrystalline protein using only solid-state MAS NMR spectroscopy. These successful application open up perspectives to access systems that are difficult to crystallise or that form large heterogeneous complexes and insoluble aggregates, for example ligands bound to a MP-receptor, protein fibrils and heterogeneous proteins aggregates. Solid-state MAS NMR spectroscopy is in principle well suited to study MP at atomic resolution. In this thesis, different types of MP preparations were tested for their suitability to be studied by solid-state MAS NMR. Proteoliposomes, poorly diffracting 2D crystals and a PEG precipitate of the outer membrane protein G (OmpG) were prepared as a model system for large MPs. Results from this work, combined with data found in the literature, show that highly diffracting crystalline material is not a prerequirement for structural analysis of MPs by solid-state MAS NMR. Instead, it is possible to use non-diffracting 3D crystals, MP precipitates, poorly diffracting 2D crystals and proteoliposomes. For the latter two types of preparations, the MP is reconstituted into a lipid bilayer, which thus allows the structural investigation in a quasi-native environment. In addition, to prepare a MP sample for solid-state MAS NMR it is possible to use screening methods, that are well established for 3D and 2D crystallisation of MPs. Hopefully, these findings will open a fourth method for structural investigation of MP. The prerequisite for structural studies by NMR in general, and the most time consuming step, is always the assignment of resonances to specific nuclei within the protein. Since the last few years an ever-increasing number of assignments from solid-state MAS NMR of uniformly carbon and nitrogen labelled samples is being reported, mostly for small proteins of up to around 150 amino acids in length. However, the complexity of the spectra increases with increasing molecular weight of the protein. Thus the conventional assignment strategies developed for small proteins do not yield a sufficiently high degree of assignment for the large MP OmpG (281 amino acids). Therefore, a new assignment strategy to find starting points for large MPs was devised. The assignment procedure is based on a sample with [2,3-13C, 15N]-labelled Tyr and Phe and uniformly labelled alanine and glycine. This labelling pattern reduces the spectral overlap as well as the number of assignment possibilities. In order to extend the assignment, four other specifically labelled OmpG samples were used. The assignment procedure starts with the identification of the spin systems of each labelled amino acid using 2D 13C-13C and 3D NCACX correlation experiments. In a second step, 2D and 3D NCOCX type experiments are used for the sequential assignment of the observed resonances to specific nuclei in the OmpG amino acid sequence. Additionally, it was shown in this work, that biosynthetically site directed labelled samples, which are normally used to observe long-range correlations, were helpful to confirm the assignment. Another approach to find assignment starting points in large protein systems, is the use of spectroscopic filtering techniques. A filtering block that selects methyl resonances was used to find further assignment starting points for OmpG. Combining all these techniques, it was possible to assign nearly 50 % of the observed signals to the OmpG sequence. Using this information, a prediction of the secondary structure elements of OmpG was possible. Most of the calculated motifs were in good aggreement with the crystal structures of OmpG. The approaches presented here should be applicable to a wide variety of MPs and MP-complexes and should thus open a new avenue for the structural biology of MPs.
The adaptive evolutionary potential of a species or population to cope with omnipresent environmental challenges is based on its genetic variation. Variability at immune genes, such as the major histocompatibility complex (MHC) genes, is assumed to be a very powerful and effective tool to keep pace with diverse and rapidly evolving pathogens. In my thesis, I studied natural levels of variation at the MHC genes, which have a key role in immune defence, and parasite burden in different small mammal species. I assessed the importance of MHC variation for parasite burden in small mammal populations in their natural environment. To understand the processes shaping different patterns of MHC variation I focused on evidence of selection through pathogens upon the host. Further, I addressed the issue of low MHC diversity in populations or species, which could potentially arise as a result from habitat fragmentation and isolation. Despite their key role in the mammalian evolution the marsupial MHC has been rarely investigated. Studies on primarily captive or laboratory bred individuals indicated very little or even no polymorphism at the marsupial MHC class II genes. However, natural levels of marsupial MHC diversity and selection are unknown to date as studies on wild populations are virtually absent. I investigated MHC II variation in two Neotropical marsupial species endemic to the threatened Brazilian Atlantic Forest (Gracilinanus microtarsus, Marmosops incanus) to test whether the predicted low marsupial MHC class II polymorphism proves to be true under natural conditions. For the first time in marsupials I confirmed characteristics of MHC selection that were so far only known from eutherian mammals, birds, and fish: Positive selection on specific codon sites, recombination, and trans-species polymorphism. Beyond that, the two marsupial species revealed considerable differences in their MHC class II diversity. Diversity was rather low in M. incanus but tenfold higher in G. microtarsus, disproving the predicted general low marsupial MHC class II variation. As pathogens are believed to be very powerful drivers of MHC diversity, I studied parasite burden in both host species to understand the reasons for the remarkable differences in MHC diversity. In both marsupial species specific MHC class II variants were associated to either high or low parasite load highlighting the importance of the marsupial MHC class II in pathogen defence. I developed two alternative scenarios with regard to MHC variation, parasite load, and parasite diversity. In the ‘evolutionary equilibrium’ scenario I assumed the species with low MHC diversity, M. incanus, to be under relaxed pathogenic selection and expected low parasite diversity. Alternatively, low MHC diversity could be the result of a recent loss of genetic variation by means of a genetic bottleneck event. Under this ‘unbalanced situation’ scenario, I assumed a high parasite burden in M. incanus due to a lack of resistance alleles. Parasitological results clearly reject the first scenario and point to the second scenario, as M. incanus is distinctly higher parasitised but parasite diversity is relatively equal compared to G. microtarsus. Hence, I suggest that the parasite load in M. incanus is rather the consequence than the cause for its low MHC diversity. MHC variation and its associations to parasite burden have been typically studied within single populations but MHC variation between populations was rarely taken into account. To gain scientific insight on this issue, I chose a common European rodent species. In the yellow necked mouse (Apodemus flavicollis), I investigated the effects of genetic diversity on parasite load not on the individual but on the population level. I included populations, which possess different levels of variation at the MHC as well as at neutrally evolving genetic markers (microsatellites). I was able to show that mouse populations with a high MHC allele diversity are better armed against high parasite burdens highlighting the significance of adaptive genetic diversity in the field of conservation genetics. An individual itself will not directly benefit from its population’s large MHC allele pool in terms of parasite resistance. But confronted with the multitude of pathogens present in the wild a population with a large MHC allele reservoir is more likely to possess individuals with resistance alleles. These results deepen our understanding of the complex causes and processes of evolutionary adaptations between hosts and pathogens.
Pectic polysaccharides, a class of plant cell wall polymers, form one of the most complex networks known in nature. Despite their complex structure and their importance in plant biology, little is known about the molecular mechanism of their biosynthesis, modification, and turnover, particularly their structure-function relationship. One way to gain insight into pectin metabolism is the identification of mutants with an altered pectin structure. Those were obtained by a recently developed pectinase-based genetic screen. Arabidopsis thaliana seedlings grown in liquid medium containing pectinase solutions exhibited particular phenotypes: they were dwarfed and slightly chlorotic. However, when genetically different A. thaliana seed populations (random T-DNA insertional populations as well as EMS-mutagenized populations and natural variations) were subjected to this treatment, individuals were identified that exhibit a different visible phenotype compared to wild type or other ecotypes and may thus contain a different pectin structure (pec-mutants). After confirming that the altered phenotype occurs only when the pectinase is present, the EMS mutants were subjected to a detailed cell wall analysis with particular emphasis on pectins. This suite of mutants identified in this study is a valuable resource for further analysis on how the pectin network is regulated, synthesized and modified. Flanking sequences of some of the T-DNA lines have pointed toward several interesting genes, one of which is PEC100. This gene encodes a putative sugar transporter gene, which, based on our data, is implicated in rhamnogalacturonan-I synthesis. The subcellular localization of PEC100 was studied by GFP fusion and this protein was found to be localized to the Golgi apparatus, the organelle where pectin biosynthesis occurs. Arabidopsis ecotype C24 was identified as a susceptible one when grown with pectinases in liquid culture and had a different oligogalacturonide mass profile when compared to ecotype Col-0. Pectic oligosaccharides have been postulated to be signal molecules involved in plant pathogen defense mechanisms. Indeed, C24 showed elevated accumulation of reactive oxygen species upon pectinase elicitation and had altered response to the pathogen Alternaria brassicicola in comparison to Col-0. Using a recombinant inbred line population three major QTLs were identified to be responsible for the susceptibility of C24 to pectinases. In a reverse genetic approach members of the qua2 (putative pectin methyltransferase) family were tested for potential target genes that affect pectin methyl-esterification. The list of these genes was determined by in silico study of the pattern of expression and co-expression of all 34 members of this family resulting in 6 candidate genes. For only for one of the 6 analyzed genes a difference in the oligogalacturonide mass profile was observed in the corresponding knock-out lines, confirming the hypothesis that the methyl-esterification pattern of pectin is fine tuned by members of this gene family. This study of pectic polysaccharides through forward and reverse genetic screens gave new insight into how pectin structure is regulated and modified, and how these modifications could influence pectin mediated signalling and pathogenicity.
This work presents mathematical and computational approaches to cover various aspects of metabolic network modelling, especially regarding the limited availability of detailed kinetic knowledge on reaction rates. It is shown that precise mathematical formulations of problems are needed i) to find appropriate and, if possible, efficient algorithms to solve them, and ii) to determine the quality of the found approximate solutions. Furthermore, some means are introduced to gain insights on dynamic properties of metabolic networks either directly from the network structure or by additionally incorporating steady-state information. Finally, an approach to identify key reactions in a metabolic networks is introduced, which helps to develop simple yet useful kinetic models. The rise of novel techniques renders genome sequencing increasingly fast and cheap. In the near future, this will allow to analyze biological networks not only for species but also for individuals. Hence, automatic reconstruction of metabolic networks provides itself as a means for evaluating this huge amount of experimental data. A mathematical formulation as an optimization problem is presented, taking into account existing knowledge and experimental data as well as the probabilistic predictions of various bioinformatical methods. The reconstructed networks are optimized for having large connected components of high accuracy, hence avoiding fragmentation into small isolated subnetworks. The usefulness of this formalism is exemplified on the reconstruction of the sucrose biosynthesis pathway in Chlamydomonas reinhardtii. The problem is shown to be computationally demanding and therefore necessitates efficient approximation algorithms. The problem of minimal nutrient requirements for genome-scale metabolic networks is analyzed. Given a metabolic network and a set of target metabolites, the inverse scope problem has as it objective determining a minimal set of metabolites that have to be provided in order to produce the target metabolites. These target metabolites might stem from experimental measurements and therefore are known to be produced by the metabolic network under study, or are given as the desired end-products of a biotechological application. The inverse scope problem is shown to be computationally hard to solve. However, I assume that the complexity strongly depends on the number of directed cycles within the metabolic network. This might guide the development of efficient approximation algorithms. Assuming mass-action kinetics, chemical reaction network theory (CRNT) allows for eliciting conclusions about multistability directly from the structure of metabolic networks. Although CRNT is based on mass-action kinetics originally, it is shown how to incorporate further reaction schemes by emulating molecular enzyme mechanisms. CRNT is used to compare several models of the Calvin cycle, which differ in size and level of abstraction. Definite results are obtained for small models, but the available set of theorems and algorithms provided by CRNT can not be applied to larger models due to the computational limitations of the currently available implementations of the provided algorithms. Given the stoichiometry of a metabolic network together with steady-state fluxes and concentrations, structural kinetic modelling allows to analyze the dynamic behavior of the metabolic network, even if the explicit rate equations are not known. In particular, this sampling approach is used to study the stabilizing effects of allosteric regulation in a model of human erythrocytes. Furthermore, the reactions of that model can be ranked according to their impact on stability of the steady state. The most important reactions in that respect are identified as hexokinase, phosphofructokinase and pyruvate kinase, which are known to be highly regulated and almost irreversible. Kinetic modelling approaches using standard rate equations are compared and evaluated against reference models for erythrocytes and hepatocytes. The results from this simplified kinetic models can simulate acceptably the temporal behavior for small changes around a given steady state, but fail to capture important characteristics for larger changes. The aforementioned approach to rank reactions according to their influence on stability is used to identify a small number of key reactions. These reactions are modelled in detail, including knowledge about allosteric regulation, while all other reactions were still described by simplified reaction rates. These so-called hybrid models can capture the characteristics of the reference models significantly better than the simplified models alone. The resulting hybrid models might serve as a good starting point for kinetic modelling of genome-scale metabolic networks, as they provide reasonable results in the absence of experimental data, regarding, for instance, allosteric regulations, for a vast majority of enzymatic reactions.