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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.
Dopamine is found in many invertebrate organisms, including insects, however, the mechanisms through which this amine operates remain unclear. We have expressed two dopamine receptors cloned from honey bee (AmDOP1 and AmDOP2) in insect cells (Spodoptera frugiperda), and compared their pharmacology directly using production of cAMP as a functional assay. In each assay, AmDOP1 receptors required lower concentrations of dopamine and 6,7-ADTN for maximal activation than AmDOP2 receptors. Conversely, butaclamol and cis(Z)-flupentixol were more potent at blocking the cAMP response mediated through AmDOP2 than AmDOP1 receptors. Expression of AmDOP1, but not AmDOP2, receptors significantly increased levels of cAMP even in the absence of ligand. This constitutive activity was blocked by cis(Z)-flupentixol. This work provides the first evidence of a constitutively activated dopamine receptor in invertebrates and suggests that although AmDOP1 and AmDOP2 share much less homology than their vertebrate counterparts, they display a number of functional parallels with the mammalian D1-like dopamine receptors.
Electro-chemical signal transduction is the basis of communication between n eurons and their target cells. An important group of neuroactive substances that are released by action potentials from neurons are the biogenic amines. These a re small organic molecules that bind to specific receptors located in the target cell membrane. Once activated these receptors cause changes in the intracellula r concentration of second messengers, i.e. cyclic nucleotides, phosphoinositides , or Ca2+, leading to slow but long-lasting cellular responses. Biochemical, pha rmacological, physiological, and molecular biological approaches have unequivoca lly shown that biogenic amines are important regulators of cellular function in both vertebrates and invertebrates. In this review, we will concentrate on the p roperties of two biogenic amines and their receptors that were originally identi fied in invertebrates: tyramine and octopamine.
Lake ecosystems across the globe have responded to climate warming of recent decades. However, correctly attributing observed changes to altered climatic conditions is complicated by multiple anthropogenic influences on lakes. This thesis contributes to a better understanding of climate impacts on freshwater phytoplankton, which forms the basis of the food chain and decisively influences water quality. The analyses were, for the most part, based on a long-term data set of physical, chemical and biological variables of a shallow, polymictic lake in north-eastern Germany (Müggelsee), which was subject to a simultaneous change in climate and trophic state during the past three decades. Data analysis included constructing a dynamic simulation model, implementing a genetic algorithm to parameterize models, and applying statistical techniques of classification tree and time-series analysis. Model results indicated that climatic factors and trophic state interactively determine the timing of the phytoplankton spring bloom (phenology) in shallow lakes. Under equally mild spring conditions, the phytoplankton spring bloom collapsed earlier under high than under low nutrient availability, due to a switch from a bottom-up driven to a top-down driven collapse. A novel approach to model phenology proved useful to assess the timings of population peaks in an artificially forced zooplankton-phytoplankton system. Mimicking climate warming by lengthening the growing period advanced algal blooms and consequently also peaks in zooplankton abundance. Investigating the reasons for the contrasting development of cyanobacteria during two recent summer heat wave events revealed that anomalously hot weather did not always, as often hypothesized, promote cyanobacteria in the nutrient-rich lake studied. The seasonal timing and duration of heat waves determined whether critical thresholds of thermal stratification, decisive for cyanobacterial bloom formation, were crossed. In addition, the temporal patterns of heat wave events influenced the summer abundance of some zooplankton species, which as predators may serve as a buffer by suppressing phytoplankton bloom formation. This thesis adds to the growing body of evidence that lake ecosystems have strongly responded to climatic changes of recent decades. It reaches beyond many previous studies of climate impacts on lakes by focusing on underlying mechanisms and explicitly considering multiple environmental changes. Key findings show that climate impacts are more severe in nutrient-rich than in nutrient-poor lakes. Hence, to develop lake management plans for the future, limnologists need to seek a comprehensive, mechanistic understanding of overlapping effects of the multi-faceted human footprint on aquatic ecosystems.
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 genome can be considered the blueprint for an organism. Composed of DNA, it harbours all organism-specific instructions for the synthesis of all structural components and their associated functions. The role of carriers of actual molecular structure and functions was believed to be exclusively assumed by proteins encoded in particular segments of the genome, the genes. In the process of converting the information stored genes into functional proteins, RNA – a third major molecule class – was discovered early on to act a messenger by copying the genomic information and relaying it to the protein-synthesizing machinery. Furthermore, RNA molecules were identified to assist in the assembly of amino acids into native proteins. For a long time, these - rather passive - roles were thought to be the sole purpose of RNA. However, in recent years, new discoveries have led to a radical revision of this view. First, RNA molecules with catalytic functions - thought to be the exclusive domain of proteins - were discovered. Then, scientists realized that much more of the genomic sequence is transcribed into RNA molecules than there are proteins in cells begging the question what the function of all these molecules are. Furthermore, very short and altogether new types of RNA molecules seemingly playing a critical role in orchestrating cellular processes were discovered. Thus, RNA has become a central research topic in molecular biology, even to the extent that some researcher dub cells as “RNA machines”. This thesis aims to contribute towards our understanding of RNA-related phenomena by applying Bioinformatics means. First, we performed a genome-wide screen to identify sites at which the chemical composition of DNA (the genotype) critically influences phenotypic traits (the phenotype) of the model plant Arabidopsis thaliana. Whole genome hybridisation arrays were used and an informatics strategy developed, to identify polymorphic sites from hybridisation to genomic DNA. Following this approach, not only were genotype-phenotype associations discovered across the entire Arabidopsis genome, but also regions not currently known to encode proteins, thus representing candidate sites for novel RNA functional molecules. By statistically associating them with phenotypic traits, clues as to their particular functions were obtained. Furthermore, these candidate regions were subjected to a novel RNA-function classification prediction method developed as part of this thesis. While determining the chemical structure (the sequence) of candidate RNA molecules is relatively straightforward, the elucidation of its structure-function relationship is much more challenging. Towards this end, we devised and implemented a novel algorithmic approach to predict the structural and, thereby, functional class of RNA molecules. In this algorithm, the concept of treating RNA molecule structures as graphs was introduced. We demonstrate that this abstraction of the actual structure leads to meaningful results that may greatly assist in the characterization of novel RNA molecules. Furthermore, by using graph-theoretic properties as descriptors of structure, we indentified particular structural features of RNA molecules that may determine their function, thus providing new insights into the structure-function relationships of RNA. The method (termed Grapple) has been made available to the scientific community as a web-based service. RNA has taken centre stage in molecular biology research and novel discoveries can be expected to further solidify the central role of RNA in the origin and support of life on earth. As illustrated by this thesis, Bioinformatics methods will continue to play an essential role in these discoveries.
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.
The uptake of nutrients and their subsequent chemical conversion by reactions which provide energy and building blocks for growth and propagation is a fundamental property of life. This property is termed metabolism. In the course of evolution life has been dependent on chemical reactions which generate molecules that are common and indispensable to all life forms. These molecules are the so-called primary metabolites. In addition, life has evolved highly diverse biochemical reactions. These reactions allow organisms to produce unique molecules, the so-called secondary metabolites, which provide a competitive advantage for survival. The sum of all metabolites produced by the complex network of reactions within an organism has since 1998 been called the metabolome. The size of the metabolome can only be estimated and may range from less than 1,000 metabolites in unicellular organisms to approximately 200,000 in the whole plant kingdom. In current biology, three additional types of molecules are thought to be important to the understanding of the phenomena of life: (1) the proteins, in other words the proteome, including enzymes which perform the metabolic reactions, (2) the ribonucleic acids (RNAs) which constitute the so-called transcriptome, and (3) all genes of the genome which are encoded within the double strands of desoxyribonucleic acid (DNA). Investigations of each of these molecular levels of life require analytical technologies which should best enable the comprehensive analysis of all proteins, RNAs, et cetera. At the beginning of this thesis such analytical technologies were available for DNA, RNA and proteins, but not for metabolites. Therefore, this thesis was dedicated to the implementation of the gas chromatography – mass spectrometry technology, in short GC-MS, for the in-parallel analysis of as many metabolites as possible. Today GC-MS is one of the most widely applied technologies and indispensable for the efficient profiling of primary metabolites. The main achievements and research topics of this work can be divided into technological advances and novel insights into the metabolic mechanisms which allow plants to cope with environmental stresses. Firstly, the GC-MS profiling technology has been highly automated and standardized. The major technological achievements were (1) substantial contributions to the development of automated and, within the limits of GC-MS, comprehensive chemical analysis, (2) contributions to the implementation of time of flight mass spectrometry for GC-MS based metabolite profiling, (3) the creation of a software platform for reproducible GC-MS data processing, named TagFinder, and (4) the establishment of an internationally coordinated library of mass spectra which allows the identification of metabolites in diverse and complex biological samples. In addition, the Golm Metabolome Database (GMD) has been initiated to harbor this library and to cope with the increasing amount of generated profiling data. This database makes publicly available all chemical information essential for GC-MS profiling and has been extended to a global resource of GC-MS based metabolite profiles. Querying the concentration changes of hundreds of known and yet non-identified metabolites has recently been enabled by uploading standardized, TagFinder-processed data. Long-term technological aims have been pursued with the central aims (1) to enhance the precision of absolute and relative quantification and (2) to enable the combined analysis of metabolite concentrations and metabolic flux. In contrast to concentrations which provide information on metabolite amounts, flux analysis provides information on the speed of biochemical reactions or reaction sequences, for example on the rate of CO2 conversion into metabolites. This conversion is an essential function of plants which is the basis of life on earth. Secondly, GC-MS based metabolite profiling technology has been continuously applied to advance plant stress physiology. These efforts have yielded a detailed description of and new functional insights into metabolic changes in response to high and low temperatures as well as common and divergent responses to salt stress among higher plants, such as Arabidopsis thaliana, Lotus japonicus and rice (Oryza sativa). Time course analysis after temperature stress and investigations into salt dosage responses indicated that metabolism changed in a gradual manner rather than by stepwise transitions between fixed states. In agreement with these observations, metabolite profiles of the model plant Lotus japonicus, when exposed to increased soil salinity, were demonstrated to have a highly predictive power for both NaCl accumulation and plant biomass. Thus, it may be possible to use GC-MS based metabolite profiling as a breeding tool to support the selection of individual plants that cope best with salt stress or other environmental challenges.
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.