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In this work the energy transfer and excitonic coupling in different chromophore arrangements were investigated. A difference in the coupling strength was introduced by varring the connecting unit and the spacial orientation relative to each other.
The synthesis of the 2,7-substituted pyrene compounds could be optimised and good yields of HAB 1 and HAB 2 and small amounts of HAB 2 could be achieved by cobalt-catalysed trimerisation or Diels Alder reaction in the end. Absorption and fluorescence spectra reveal strong intramolecular interactions between the pyrene molecules in the HAB 1. Excitation spectra recorded at the high and low energy fluorescence suggest the contribution of two components to the spectra. One being similar to the ground state aggregate and a second species similar to undisturbed pyrene. All these feature can be accounted to two different fluorescent states which are due to electronical decoupling in the excited state. Due to the strong intramolecular coupling already in the ground state of the molecule, no energy transfer could be studied, as the six pyrene units cannot be seen as separate spectroscopic entities between which energy could be transferred.
In the second part of this thesis dye conjugates of different size and alignment were synthesised to study the interaction of the transition-dipole moments. Therefore a systematic investigation of Sonogashira conditions was performed in order to obtain good yields of the desired compounds and keep dehalogenation at a minimum level. Nevertheless only the symmetrical triads could be purified as the asymmeric triads and pentades proved to decompose during purification.
The pyrene containing triads Py2B and Py2SQB show small interactions already in the ground state represented by red shifts of the spectra and a broadening of the bands. Nevertheless, these interactions are in the weak coupling regime and energy transfer between the constituents is possible. On the contrary in the TA spectra it is obvious that always the whole triad, at least to some extend is excited. To question if the excitation of the high energy state is deactivated by energy transfer or rather IC in a superchromophore could not be distinguished in the course of this work. At present additional time-dependent calculations of the dynamics are in progress to get a deeper understanding of the photophysical processes taking place in the triads.
The dye conjugates B2SQB-3 and (SQB)2B-4 can be assigned to the strong interaction range and hence are describable by exciton theory. The transition-dipole moments proved to be more than additive and increase for both compounds from absorption to fluorescence. This can be explained by an enhancement of the coupling in the relaxed excited state compared to the absorption into the Franck-Condon state due to a more steep potential energy surface in the excited state and hence smaller fluctuations.
In the last part of this thesis the influence of disrupting electronical communication by implementing a rigid non-conjugated bridge in a bichromophoric trans-squaraine system was tested. While the flexible linked squaraines show complex spectra due to different conformers the SQA2Anth compound is rigified and no rotation is possible. This change in flexibility is represented in the steady-state spectra where just one main absorption and fluorescence band is present due to a single allowed excitonic state. The system proves to own an excited state that is completely delocalised over the whole molecule.
The present work investigates the influence of environmental stimuli on the building behavior of workers of the leaf-cutting ant Atta vollenweideri. It focuses on cues related to the airflow-driven ventilation of their giant underground nests, i.e., air movements and their direction, carbon dioxide concentrations and humidity levels of the nest air. First, it is shown that workers are able to use airflow and its direction as learned orientation cue by performing learning experiments with individual foragers using a classical conditioning paradigm. This ability is expected to allow workers to also navigate inside the nest tunnels using the prevailing airflow directions for orientation, for example during tasks related to nest construction and climate control.
Furthermore, the influence of carbon dioxide on the digging behavior of workers is investigated. While elevated CO2 levels hardly affect the digging rate of the ants, workers prefer to excavate at locations with lower concentrations and avoid higher CO2 levels when given a choice. Under natural conditions, shifting their digging activity to soil layers containing lower carbon dioxide levels might help colonies to excavate new or to broaden existing nest openings, if the CO2 concentration in the underground rises.
It is also shown that workers preferably transport excavated soil along tunnels containing high CO2 concentrations, when carbon dioxide levels in the underground are elevated as well. In addition, workers prefer to carry soil pellets along outflow tunnels instead of inflow tunnels, at least for high humidity levels of the air. The material transported along tunnels providing outflow of CO2-rich air might be used by workers for the construction of ventilation turrets on top of the nest mound, which is expected to promote the wind-induced ventilation and the removal of carbon dioxide from the underground.
The climatic conditions inside the nest tunnels also influence the structural features of the turrets constructed by workers on top the nest. While airflow and humidity have no effect on turret structure, outflow of CO2-rich air from the nest causes workers to construct turrets with additional openings and increased aperture, potentially enhancing the airflow-driven gas exchanges within the nest.
Finally, the effect of airflow and ventilation turrets on the gas exchanges in Atta vollenweideri nests is tested experimentally on a physical model of a small nest consisting of a single chamber and two nest tunnels. The carbon dioxide clearance rate from the underground was measured depending on both the presence of airflow in the nest and the structural features of the built turrets. Carbon dioxide is removed faster from the physical nest model when air moves through the nest, confirming the contribution of wind-induced flow inside the nest tunnels to the ventilation of Atta vollenweideri nests. In addition, turrets placed on top of one of the tunnel openings of the nest further enhance the CO2 clearance rate and the effect is positively correlated with turret aperture.
Taken together, climatic variables like airflow, carbon dioxide and humidity levels strongly affect the building responses of Atta vollenweideri leaf-cutting ants. Workers use these environmental stimuli as orientation cue in the nest during tasks related to excavation, soil transport and turret construction. Although the effects of these building responses on the microclimatic conditions inside the nest remain elusive so far, the described behaviors are expected to allow ant colonies to restore and maintain a proper nest climate in the underground.
RNA sequencing (RNA-seq) has in recent years become the preferred method for gene expression analysis and whole transcriptome annotation. While initial RNA-seq experiments focused on eukaryotic messenger RNAs (mRNAs), which can be purified from the cellular ribonucleic acid (RNA) pool with relative ease, more advanced protocols had to be developed for sequencing of microbial transcriptomes. The resulting RNA-seq data revealed an unexpected complexity of bacterial transcriptomes and the requirement for specific analysis methods, which in many cases is not covered by tools developed for processing of eukaryotic data.
The aim of this thesis was the development and application of specific data analysis methods for different RNA-seq-based approaches used to gain insights into transcription and gene regulatory processes in prokaryotes.
The differential RNA sequencing (dRNA-seq) approach allows for transcriptional start site (TSS) annotation by differentiating between primary transcripts with a 5’-triphosphate (5’-PPP) and processed transcripts with a 5’-monophosphate (5’-P). This method was applied in combination with an automated TSS annotation tool to generate global trancriptome maps for Escherichia coli (E. coli) and Helicobacter pylori (H. pylori).
In the E. coli study we conducted different downstream analyses to gain a deeper understanding of the nature and properties of transcripts in our TSS map. Here, we focused especially on putative antisense RNAs (asRNAs), an RNA class transcribed from the opposite strand of known protein-coding genes with the potential to regulate corresponding sense transcripts. Besides providing a set of putative asRNAs and experimental validation of candidates via Northern analysis, we analyzed and discussed different sources of variation in RNA-seq data.
The aim of the H. pylori study was to provide a detailed description of the dRNA-seq approach and its application to a bacterial model organism. It includes information on experimental protocols and requirements for data analysis to generate a genome-wide TSS map. We show how the included TSS can be used to identify and analyze transcriptome and regulatory features and discuss challenges in terms oflibrary preparation protocols, sequencing platforms, and data analysis including manual and automated TSS annotation.
The TSS maps and associated transcriptome data from both H. pylori and E. coli were made available for visualization in an easily accessible online browser.
Furthermore, a modified version of dRNA-seq was used to identify transcriptome targets of the RNA pyrophosphohydrolase (RppH) in H. pylori. RppH initiates 5’-end-dependent degradation of transcripts by converting the 5’-PPP of primary transcripts to a 5’-P. I developed an analysis method, which uses data from complementary DNA (cDNA) libraries specific for transcripts carrying a 5’-PPP, 5’-P or both, to specifically identify transcripts modified by RppH. For this, the method assessed the 5’-phosphorylation state and cellular concentration of transcripts in rppH deletion in comparison to strains with the intact gene. Several of the identified potential RppH targets were further validated via half-life measurements and quantification of their 5’-phosphorylation state in wild-type and mutant cells. Our findings suggest an important role for RppH in post-transcriptional gene regulationin H. pylori and related organisms.
In addition, we applied two RNA-seq -based approaches, RNA immunoprecipitation followed by sequencing (RIP-seq) and cross-linking immunoprecipitation followed by sequencing (CLIP-seq), to identify transcripts bound by Hfq and CsrA, two RNA-binding proteins (RBPs) with an important role in post-transcriptional regulation.
For RIP-seq -based identification of CsrA binding regions in Campylobacter jejuni(C. jejuni), we used annotation-based analysis and, in addition, a self-developed peak calling method based on a sliding window approach. Both methods revealed flaA mRNA, encoding the major flagellin, as the main target and functional analysis of identified targets showed a significant enrichment of genes involved in flagella biosynthesis. Further experimental analysis revealed the role of flaA mRNA in post-transcriptional regulation. In comparison to RIP-seq, CLIP-seq allows mapping of RBP binding sites with a higher resolution. To identify these sites an approach called “block-based peak calling” was developed and resulting peaks were used to identify sequence and structural constraints required for interaction of Hfq and CsrA with Salmonella transcripts.
Overall, the different RNA-seq-based approaches described in this thesis together with their associated analyis pipelines extended our knowledge on the transcriptional repertoire and modes of post-transcriptional regulation in bacteria. The global TSS maps, including further characterized asRNA candidates, putative RppH targets, and identified RBP interactomes will likely trigger similar global studies in the same or different organisms or will be used as a resource for closer examination of these features.
Bacterial functional membrane microdomains (FMMs) are membrane platforms that resemble lipid rafts of eukaryotic cells in certain functional and structural aspects. Lipid rafts are nanometer-sized, dynamic clusters of proteins and lipids in eukaryotic cell membranes that serve as signaling hubs and assembling platforms. Yet, studying these structures can often be hampered by the complexity of a eukaryotic cell. Thus, the analogous structures of prokaryotes are an attractive model to study molecular traits of this type of membrane organization.
Similar to eukaryotic lipid rafts, the bacterial FMMs are comprised of polyisoprenoid lipids, scaffold proteins and a distinct set of membrane proteins, involved in signaling or secretion. Investigating bacterial FMMs not only contributes to the understanding of the physiological importance of FMMs in bacteria, but also helps to elucidate general principles of rafts beyond prokaryotes.
In this work, a bacterial model organism was used to investigate effects of synthetic overproduction of the raft scaffolding proteins on bacterial physiology. This overexpression causes an unusual stabilization of the FMM-harbored protease FtsH and therefore the proteolytic targets of FtsH are not correctly regulated. Developmental defects and aberrances in shape are the consequence, which in turn negatively affects cell physiology. These findings may be adapted to better understand lipid raft processes in humans, where flotillin upregulation is detected along with development of neurological diseases.
Moreover, it was aimed at understanding the FMM-proteome of the human pathogen Staphylococcus aureus. An in-depth quantitative mass-spectrometry analysis reveals adaption of the protein cargo during different conditions, while maintaining a distinct set of core FMM proteins. As a case study, the assembly of the type VII secretion system was shown to be dependent on FMM integrity and more specifically on the activity of the FMM-scaffold flotillin. This secretion system is important for the virulence of this pathogen and its secretion efficiency can be targeted by small molecules that inhibit flotillin activity. This opens new venues for non-conventional antimicrobial compounds to treat staphylococcal infections.
Anxiety and depressive disorders result from a complex interplay of genetic and environmental factors and are common mutual comorbidities. On the level of cellular signaling, regulator of G protein signaling 2 (Rgs2) has been implicated in human and rodent anxiety as well as rodent depression. Rgs2 negatively regulates G protein-coupled receptor (GPCR) signaling by acting as a GTPase accelerating protein towards the Gα subunit.
The present study investigates, whether mice with a homozygous Rgs2 deletion (Rgs2-/-) show behavioral alterations as well as an increased susceptibility to stressful life events related to human anxiety and depressive disorders and tries to elucidate molecular underlying’s of these changes.
To this end, Rgs2-/- mice were characterized in an aversive-associative learning paradigm to evaluate learned fear as a model for the etiology of human anxiety disorders. Spatial learning and reward motivated spatial learning were evaluated to control for learning in non-aversive paradigms. Rgs2 deletion enhanced learning in all three paradigms, rendering increased learning upon deletion of Rgs2 not specific for aversive learning. These data support reports indicating increased long-term potentiation in Rgs2-/- mice and may predict treatment response to conditioning based behavior therapy in patients with polymorphisms associated with reduced RGS2 expression. Previous reports of increased innate anxiety were corroborated in three tests based on the approach-avoidance conflict. Interestingly, Rgs2-/- mice showed novelty-induced hypo-locomotion suggesting neophobia, which may translate to the clinical picture of agoraphobia in humans and reduced RGS2 expression in humans was associated with a higher incidence of panic disorder with agoraphobia. Depression-like behavior was more distinctive in female Rgs2-/- mice. Stress resilience, tested in an acute and a chronic stress paradigm, was also more distinctive in female Rgs2-/- mice, suggesting Rgs2 to contribute to sex specific effects of anxiety disorders and depression.
Rgs2 deletion was associated with GPCR expression changes of the adrenergic, serotonergic, dopaminergic and neuropeptide Y systems in the brain and heart as well as reduced monoaminergic neurotransmitter levels. Furthermore, the expression of two stress-related microRNAs was increased upon Rgs2 deletion. The aversive-associative learning paradigm induced a dynamic Rgs2 expression change. The observed molecular changes may contribute to the anxious and depressed phenotype as well as promote altered stress reactivity, while reflecting an alter basal stress level and a disrupted sympathetic tone. Dynamic Rgs2 expression may mediate changes in GPCR signaling duration during memory formation.
Taken together, Rgs2 deletion promotes increased anxiety-like and depression-like behavior, altered stress reactivity as well as increased cognitive function.
BACKGROUND. Prostate cancer (PCa) remains a major health concern in men of the Western World. However, we still lack effective diagnostic tools a) for an effective screening with both high sensitivity and specificity, b) to guide biopsies and avoid histology sampling errors and c) to predict tumor aggressiveness in order to avoid overtreatment. Therefore, a more reliable, highly cancer-specific and ideally in vivo approach is needed. The present study has been designed in order to further develop and test the method of "metabolomic imaging" using magnetic resonance spectroscopy (MRS) at 7T to address those challenges.
METHODS. Thirty whole prostates with biopsy-proven PCa were in vitro analyzed with a 7T human MR scanner. A voxel grid containing the spectral information was overlaid with the MR image of the middle transverse cross-sectional plane of each case. Subsequent histopathological evaluation of the prostate specimen followed. After the spectral output was processed, all voxels were compared with a metabolomic PCa profile, which had been established within a preliminary study, in order to create a metabolomic map indicating MRS cancer-suspicious regions. Those regions were compared with the histologically identified tumor lesions regarding location.
RESULTS. Sixty-one percent of the histological cancer lesions were detected by metabolomic imaging. Among the cases with PCa on the examined slice, 75% were identified as cancerous. None of the tested features significantly differed between detected and undetected cancer lesions. A defined "Malignancy Index" (MI) significantly differentiated between MRS-suspicious lesions corresponding with a histological cancer lesion and benign lesions (p = 0.006) with an overall accuracy of 70%. The MI furthermore showed a positive correlation with the Gleason grade (p = 0.021).
CONCLUSION. A new approach within PCa diagnostics was developed with spectral analysis including the whole measureable metabolome - referred to as "metabolomics" - rather than focusing on single metabolites. The MI facilitates precise tumor detection and may additionally serve as a marker for tumor aggressiveness. Metabolomic imaging might contribute to a highly cancer-specific in vivo diagnostic protocol for PCa.
Neurobiology is widely supported by bioinformatics. Due to the big amount of data generated from the biological side a computational approach is required. This thesis presents four different cases of bioinformatic tools applied to the service of Neurobiology.
The first two tools presented belong to the field of image processing. In the first case, we make use of an algorithm based on the wavelet transformation to assess calcium activity events in cultured neurons. We designed an open source tool to assist neurobiology researchers in the analysis of calcium imaging videos. Such analysis is usually done manually which is time consuming and highly subjective. Our tool speeds up the work and offers the possibility of an unbiased detection of the calcium events. Even more important is that our algorithm not only detects the neuron spiking activity but also local spontaneous activity which is normally discarded because it is considered irrelevant. We showed that this activity is determinant in the calcium dynamics in neurons and it is involved in important functions like signal modulation and memory and learning.
The second project is a segmentation task. In our case we are interested in segmenting the neuron nuclei in electron microscopy images of c.elegans. Marking these structures is necessary in order to reconstruct the connectome of the organism. C.elegans is a great study case due to the simplicity of its nervous system (only 502 neurons). This worm, despite its simplicity has taught us a lot about neuronal mechanisms. There is still a lot of information we can extract from the c.elegans, therein lies the importance of reconstructing its connectome. There is a current version of the c.elegans connectome but it was done by hand and on a single subject which leaves a big room for errors. By automatizing the segmentation of the electron microscopy images we guarantee an unbiased approach and we will be able to verify the connectome on several subjects.
For the third project we moved from image processing applications to biological modeling. Because of the high complexity of even small biological systems it is necessary to analyze them with the help of computational tools. The term in silico was coined to refer to such computational models of biological systems. We designed an in silico model of the TNF (Tumor necrosis factor) ligand and its two principal receptors. This biological system is of high relevance because it is involved in the inflammation process. Inflammation is of most importance as protection mechanism but it can also lead to complicated diseases (e.g. cancer). Chronic inflammation processes can be particularly dangerous in the brain. In order to better understand the dynamics that govern the TNF system we created a model using the BioNetGen language. This is a rule based language that allows one to simulate systems where multiple agents are governed by a single rule. Using our model we characterized the TNF system and hypothesized about the relation of the ligand with each of the two receptors. Our hypotheses can be later used to define drug targets in the system or possible treatments for chronic inflammation or lack of the inflammatory response.
The final project deals with the protein folding problem. In our organism proteins are folded all the time, because only in their folded conformation are proteins capable of doing their job (with some very few exceptions). This folding process presents a great challenge for science because it has been shown to be an NP problem. NP means non deterministic Polynomial time problem. This basically means that this kind of problems cannot be efficiently solved. Nevertheless, somehow the body is capable of folding a protein in just milliseconds. This phenomenon puzzles not only biologists but also mathematicians. In mathematics NP problems have been studied for a long time and it is known that given the solution to one NP problem we could solve many of them (i.e. NP-complete problems). If we manage to understand how nature solves the protein folding problem then we might be able to apply this solution to many other problems. Our research intends to contribute to this discussion. Unfortunately, not to explain how nature solves the protein folding problem, but to explain that it does not solve the problem at all. This seems contradictory since I just mentioned that the body folds proteins all the time, but our hypothesis is that the organisms have learned to solve a simplified version of the NP problem. Nature does not solve the protein folding problem in its full complexity. It simply solves a small instance of the problem. An instance which is as simple as a convex optimization problem. We formulate the protein folding problem as an optimization problem to illustrate our claim and present some toy examples to illustrate the formulation. If our hypothesis is true, it means that protein folding is a simple problem. So we just need to understand and model the conditions of the vicinity inside the cell at the moment the folding process occurs. Once we understand this starting conformation and its influence in the folding process we will be able to design treatments for amyloid diseases such as Alzheimer's and Parkinson's.
In summary this thesis project contributes to the neurobiology research field from four different fronts. Two are practical contributions with immediate benefits, such as the calcium imaging video analysis tool and the TNF in silico model. The neuron nuclei segmentation is a contribution for the near future. A step towards the full annotation of the c.elegans connectome and later for the reconstruction of the connectome of other species. And finally, the protein folding project is a first impulse to change the way we conceive the protein folding process in nature. We try to point future research in a novel direction, where the amino code is not the most relevant characteristic of the process but the conditions within the cell.
B≡N and B≡B triple bonds induce C-H activation of acetone to yield a (2-propenyloxy)aminoborane and an unsymmetrical 1-(2- propenyloxy)-2-hydrodiborene, respectively. DFT calculations showed that, despite their stark electronic differences, both the B≡N and B≡B triple bonds activate acetone via a similar coordination-deprotonation mechansim. In contrast, the reaction of acetone with a cAAC-supported diboracumulene yielded a unique 1,2,3-oxadiborole, which according to DFT calculations also proceeds via an unsymmetrical diborene, followed by intramolecular hydride migration and a second C-H activation of the enolate ligand.