570 Biowissenschaften; Biologie
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Background: Leishmania tarentolae, a unicellular eukaryotic protozoan, has been established as a novel host for recombinant protein production in recent years. Current protocols for protein expression in Leishmania are, however, time consuming and require extensive lab work in order to identify well-expressing cell lines. Here we established an alternative protein expression work-flow that employs recently engineered infrared fluorescence protein (IFP) as a suitable and easy-to-handle reporter protein for recombinant protein expression in Leishmania. As model proteins we tested three proteins from the plant Arabidopsis thaliana, including a NAC and a type-B ARR transcription factor. Results: IFP and IFP fusion proteins were expressed in Leishmania and rapidly detected in cells by deconvolution microscopy and in culture by infrared imaging of 96-well microtiter plates using small cell culture volumes (2 μL - 100 μL). Motility, shape and growth of Leishmania cells were not impaired by intracellular accumulation of IFP. In-cell detection of IFP and IFP fusion proteins was straightforward already at the beginning of the expression pipeline and thus allowed early pre-selection of well-expressing Leishmania clones. Furthermore, IFP fusion proteins retained infrared fluorescence after electrophoresis in denaturing SDS-polyacrylamide gels, allowing direct in-gel detection without the need to disassemble cast protein gels. Thus, parameters for scaling up protein production and streamlining purification routes can be easily optimized when employing IFP as reporter. Conclusions: Using IFP as biosensor we devised a protocol for rapid and convenient protein expression in Leishmania tarentolae. Our expression pipeline is superior to previously established methods in that it significantly reduces the hands-on-time and work load required for identifying well-expressing clones, refining protein production parameters and establishing purification protocols. The facile in-cell and in-gel detection tools built on IFP make Leishmania amenable for high-throughput expression of proteins from plant and animal sources.
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.
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.
Results: Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.
Conclusions: The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.
Multi-color fluorescence imaging experiments of wave forming Dictyostelium cells have revealed that actin waves separate two domains of the cell cortex that differ in their actin structure and phosphoinositide composition. We propose a bistable model of actin dynamics to account for these experimental observation. The model is based on the simplifying assumption that the actin cytoskeleton is composed of two distinct network types, a dendritic and a bundled network. The two structurally different states that were observed in experiments correspond to the stable fixed points in the bistable regime of this model. Each fixed point is dominated by one of the two network types. The experimentally observed actin waves can be considered as trigger waves that propagate transitions between the two stable fixed points.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
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.
Pektatlyase (Pel-15) aus dem alkalophilen Bodenbakterium Bacillus spec. KSM-P15 ist mit 197 Aminosäuren eines der kleinsten, bekannten β-3-Solenoidproteine. Sie spaltet Polygalakturonsäurederivate in einem Ca2+-abhängigen β-Eliminierungsprozess. Wie bei allen Proteinen dieser Enzymfamilie ist auch die Polypeptidkette von Pel-15 zu einer einsträngigen, rechtsgängigen, parallelen β-Helix aufgewunden. In diesem Strukturmotiv enthält jede Windung drei β-Stränge, die jeweils durch flexible Schleifenbereiche miteinander verbunden sind. Insgesamt acht Windungen stapeln sich in Pel-15 übereinander und bilden entlang der Helixachse flächige, parallele β-Faltblätter aus. Im Bereich dieser β-Faltblätter existiert ein ausgedehntes Netzwerk von Wasserstoffbrückenbindungen, durch das der hydrophobe Kern, der sich im Inneren der β-Helix befindet, vom umgebenden Lösungsmittel abgeschirmt wird. Besondere Abschlussstrukturen an beiden Enden der β-Helix, wie sie typischerweise bei anderen Ver-tretern dieser Strukturklasse ausgeprägt werden, sind in Pel-15 nicht zu beobachten. Stattdessen sind die terminalen Bereiche der β-Helix über Salzbrücken und hydrophobe Seitenkettenkontakte stabilisiert. In der vorliegenden Dissertation wurde die Pektatlyase Pel-15 hinsichtlich ihres Faltungsgleichgewichtes, ihrer enzymatischen Aktivität und der Kinetik ihrer Strukturbildung charakterisiert. In eine evolutionär konservierte Helixwindung wurden destabilisierende Mutationen eingeführt, und deren Auswirkungen mittels spektroskopischer Methoden analysiert. Die Ergebnisse zeigen, dass Pel-15 in Gegenwart des Denaturierungsmittels Guanidiniumhydrochlorid einen hyperfluoreszenten Gleichgewichtsustand (HF) populiert, der nach Messungen von Faltungs- und Entfaltungskinetiken ein konformationelles Ensemble aus den Zuständen HFslow und HFfast darstellt. Diese HF-Zustände sind durch eine hohe Aktivierungsbarriere voneinander getrennt. In Rückfaltungsexperimenten populieren nur etwa 80 % der faltenden Moleküle den Zwischenzustand HFslow, der mit einer Zeitkonstante von ca. 100 s zu HFfast weiterreagiert. Die Denaturierungsmittelabhängigkeit dieser Reaktion ist sehr gering, was eine trans-/cis-Prolylisomerisierung als geschwindigkeitslimitierenden Schritt nahelegt. Die Existenz eines cis-Peptides in der nativen Struktur macht es erforderlich, den denaturierten Zustand als ein Ensemble kinetisch separierter Konformationen, kurz: DSE, zu betrachten, das durch die Spezies Ufast und Uslow populiert wird. Nach dem in dieser Arbeit aufgestellten „Minimalmodell der Pel-15 Faltung“ stehen die HF-Spezies (HFslow, HFfast) mit den Konformationen des DSE in einem thermodynamischen Kreisprozess. Das Modell positioniert HFfast und die native Konformation N auf die „native Seite“ der Aktivierungsbarriere und trägt damit der Tatsache Rechnung, dass die Gleichgewichtseinstellung zwischen diesen Spezies zu schnell ist, um mit manuellen Techniken erfasst zu werden. Die hochaffine Bindung von Ca2+ (Kd = 10 μM) verschiebt sich das Faltungsgleichgewicht bereits in Gegenwart von 1 mM CaCl2 soweit auf die Seite des nativen Zustandes, das HFfast nicht länger nachweisbar ist. Entgegen anfänglicher Vermutungen kommt einer lokalen, evolutionär konservierten Disulfidbrücke im Zentrum der β-Helix eine wichtige Stabilisierungsfunktion zu. Die Disulfidbrücke befindet sich in einem kurzen Schleifenbereich der β-Helix nahe dem aktiven Zentrum. Obwohl ihr Austausch gegen die Reste Val und Ala die freie Stabilisierungsenthalpie des Proteins um ca. 10 kJ/mol reduziert, lässt die Struktur im Bereich der Mutationsstelle keine gravierende Veränderung erkennen. Auch die katalytisch relevante Ca2+-Bindungsaffinität bleibt unbeeinflusst; dennoch zeigen Enzymaktivitätstests für VA-Mutanten eine Reduktion der enzymatischen Aktivität um fast 50 % an. Die evolutionär konservierte Helixwindung im Allgemeinen und die in ihr enthaltene Disulfidbrücke im Besonderen müssen nach den vorliegenden Ergebnissen also eine zentrale Funktion sowohl für die Struktur des katalytischen Zentrums als auch für die Strukturbildung der β-Helix während der Faltungsreaktion besitzen. Die Ergebnisse dieser Arbeit finden in mehreren Punkten Anklang an Faltungseigenschaften, die für andere β -Helixproteine beschrieben wurden. Vor allem aber prädestinieren sie Pel-15 als ein neues, β-helikales Modellprotein. Aufgrund seiner einfachen Topologie, seiner niedrigen Windungszahl und seiner hohen thermodynamischen Stabilität ist Pel-15 sehr gut geeignet, die Determinanten von Stabilität und Strukturbildung des parallelen β-Helix-Motivs in einer Auflösung zu studieren, die aufgrund der Komplexität bestehender β-helikaler Modellsysteme bislang nicht zur Verfügung stand.
The widespread usage of products containing volatile organic compounds (VOC) has lead to a general human exposure to these chemicals in work places or homes being suspected to contribute to the growing incidence of environmental diseases. Since the causal molecular mechanisms for the development of these disorders are not completely understood, the overall objective of this thesis was to investigate VOC-mediated molecular effects on human lung cells in vitro at VOC concentrations comparable to exposure scenarios below current occupational limits. Although differential expression of single proteins in response to VOCs has been reported, effects on complex protein networks (proteome) have not been investigated. However, this information is indispensable when trying to ascertain a mechanism for VOC action on the cellular level and establishing preventive strategies. For this study, the alveolar epithelial cell line A549 has been used. This cell line, cultured in a two-phase (air/liquid) model allows the most direct exposure and had been successfully applied for the analysis of inflammatory effects in response to VOCs. Mass spectrometric identification of 266 protein spots provided the first proteomic map of A549 cell line to this extent that may foster future work with this frequently used cellular model. The distribution of three typical air contaminants, monochlorobenzene (CB), styrene and 1,2 dichlorobenzene (1,2-DCB), between gas and liquid phase of the exposure model has been analyzed by gas chromatography. The obtained VOC partitioning was in agreement with available literature data. Subsequently the adapted in vitro system has been successfully employed to characterize the effects of the aromatic compound styrene on the proteome of A549 cells (Chapter 4). Initially, the cell toxicity has been assessed in order to ensure that most of the concentrations used in the following proteomic approach were not cytotoxic. Significant changes in abundance and phosphorylation in the total soluble protein fraction of A549 cells have been detected following styrene exposure. All proteins have been identified using mass spectrometry and the main cellular functions have been assigned. Validation experiments on protein and transcript level confirmed the results of the 2-DE experiments. From the results, two main cellular pathways have been identified that were induced by styrene: the cellular oxidative stress response combined with moderate pro-apoptotic signaling. Measurement of cellular reactive oxygen species (ROS) as well as the styrene-mediated induction of oxidative stress marker proteins confirmed the hypothesis of oxidative stress as the main molecular response mechanism. Finally, adducts of cellular proteins with the reactive styrene metabolite styrene 7,8 oxide (SO) have been identified. Especially the SO-adducts observed at both the reactive centers of thioredoxin reductase 1, which is a key element in the control of the cellular redox state, may be involved in styrene-induced ROS formation and apoptosis. A similar proteomic approach has been carried out with the halobenzenes CB and 1,2-DCB (Chapter 5). In accordance with previous findings, cell toxicity assessment showed enhanced toxicity compared to the one caused by styrene. Significant changes in abundance and phosphorylation of total soluble proteins of A549 cells have been detected following exposure to subtoxic concentrations of CB and 1,2-DCB. All proteins have been identified using mass spectrometry and the main cellular functions have been assigned. As for the styrene experiment, the results indicated two main pathways to be affected in the presence of chlorinated benzenes, cell death signaling and oxidative stress response. The strong induction of pro-apoptotic signaling has been confirmed for both treatments by detection of the cleavage of caspase 3. Likewise, the induction of redox-sensitive protein species could be correlated to an increased cellular level of ROS observed following CB treatment. Finally, common mechanisms in the cellular response to aromatic VOCs have been investigated (Chapter 6). A similar number (4.6-6.9%) of all quantified protein spots showed differential expression (p<0.05) following cell exposure to styrene, CB or 1,2-DCB. However, not more than three protein spots showed significant regulation in the same direction for all three volatile compounds: voltage-dependent anion-selective channel protein 2, peroxiredoxin 1 and elongation factor 2. However, all of these proteins are important molecular targets in stress- and cell death-related signaling pathways.
The aim of this thesis is the design, expression and purification of human cytochrome c mutants and their characterization with regard to electrochemical and structural properties as well as with respect to the reaction with the superoxide radical and the selected proteins sulfite oxidase from human and fungi bilirubin oxidase. All three interaction partners are studied here for the first time with human cyt c and with mutant forms of cyt c. A further aim is the incorporation of the different cyt c forms in two bioelectronic systems: an electrochemical superoxide biosensor with an enhanced sensitivity and a protein multilayer assembly with and without bilirubin oxidase on electrodes. The first part of the thesis is dedicated to the design, expression and characterization of the mutants. A focus is here the electrochemical characterization of the protein in solution and immobilized on electrodes. Further the reaction of these mutants with superoxide was investigated and the possible reaction mechanisms are discussed. In the second part of the work an amperometric superoxide biosensor with selected human cytochrome c mutants was constructed and the performance of the sensor electrodes was studied. The human wild-type and four of the five mutant electrodes could be applied successfully for the detection of the superoxide radical. In the third part of the thesis the reaction of horse heart cyt c, the human wild-type and seven human cyt c mutants with the two proteins sulfite oxidase and bilirubin oxidase was studied electrochemically and the influence of the mutations on the electron transfer reactions was discussed. Finally protein multilayer electrodes with different cyt form including the mutant forms G77K and N70K which exhibit different reaction rates towards BOD were investigated and BOD together with the wild-type and engineered cyt c was embedded in the multilayer assembly. The relevant electron transfer steps and the kinetic behavior of the multilayer electrodes are investigated since the functionality of electroactive multilayer assemblies with incorporated redox proteins is often limited by the electron transfer abilities of the proteins within the multilayer. The formation via the layer-by-layer technique and the kinetic behavior of the mono and bi-protein multilayer system are studied by SPR and cyclic voltammetry. In conclusion this thesis shows that protein engineering is a helpful instrument to study protein reactions as well as electron transfer mechanisms of complex bioelectronic systems (such as bi-protein multilayers). Furthermore, the possibility to design tailored recognition elements for the construction of biosensors with an improved performance is demonstrated.