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Institute
- Institut für Biochemie und Biologie (12) (remove)
‘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.
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.