@phdthesis{Scholz2006, author = {Scholz, Matthias}, title = {Approaches to analyse and interpret biological profile data}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-7839}, school = {Universit{\"a}t Potsdam}, year = {2006}, abstract = {Advances in biotechnologies rapidly increase the number of molecules of a cell which can be observed simultaneously. This includes expression levels of thousands or ten-thousands of genes as well as concentration levels of metabolites or proteins. Such Profile data, observed at different times or at different experimental conditions (e.g., heat or dry stress), show how the biological experiment is reflected on the molecular level. This information is helpful to understand the molecular behaviour and to identify molecules or combination of molecules that characterise specific biological condition (e.g., disease). This work shows the potentials of component extraction algorithms to identify the major factors which influenced the observed data. This can be the expected experimental factors such as the time or temperature as well as unexpected factors such as technical artefacts or even unknown biological behaviour. Extracting components means to reduce the very high-dimensional data to a small set of new variables termed components. Each component is a combination of all original variables. The classical approach for that purpose is the principal component analysis (PCA). It is shown that, in contrast to PCA which maximises the variance only, modern approaches such as independent component analysis (ICA) are more suitable for analysing molecular data. The condition of independence between components of ICA fits more naturally our assumption of individual (independent) factors which influence the data. This higher potential of ICA is demonstrated by a crossing experiment of the model plant Arabidopsis thaliana (Thale Cress). The experimental factors could be well identified and, in addition, ICA could even detect a technical artefact. However, in continuously observations such as in time experiments, the data show, in general, a nonlinear distribution. To analyse such nonlinear data, a nonlinear extension of PCA is used. This nonlinear PCA (NLPCA) is based on a neural network algorithm. The algorithm is adapted to be applicable to incomplete molecular data sets. Thus, it provides also the ability to estimate the missing data. The potential of nonlinear PCA to identify nonlinear factors is demonstrated by a cold stress experiment of Arabidopsis thaliana. The results of component analysis can be used to build a molecular network model. Since it includes functional dependencies it is termed functional network. Applied to the cold stress data, it is shown that functional networks are appropriate to visualise biological processes and thereby reveals molecular dynamics.}, subject = {Bioinformatik}, language = {en} } @phdthesis{Bieniawska2006, author = {Bieniawska, Zuzanna}, title = {Functional analysis of the sucrose synthase gene family in Arabidopsis thaliana}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-13132}, school = {Universit{\"a}t Potsdam}, year = {2006}, abstract = {Sucrose synthase (Susy) is a key enzyme of sucrose metabolism, catalysing the reversible conversion of sucrose and UDP to UDP-glucose and fructose. Therefore, its activity, localization and function have been studied in various plant species. It has been shown that Susy can play a role in supplying energy in companion cells for phloem loading (Fu and Park, 1995), provides substrates for starch synthesis (Zrenner et al., 1995), and supplies UDP-glucose for cell wall synthesis (Haigler et al., 2001). Analysis of the Arabidopsis genome identifies six Susy isoforms. The expression of these isoforms was investigated using promoter-reporter gene constructs (GUS) and real time RT-PCR. Although these isoforms are closely related at the protein level they have radically different spatial and temporal patterns of expression in the plant with no two isoforms showing the same distribution. More than one isoform is expressed in all organs examined. Some of them have high but specific expression in particular organs or developmental stages whilst others are constantly expressed throughout the whole plant and across various stages of development. The in planta function of the six Susy isoforms were explored through analysis of T-DNA insertion mutants and RNAi lines. Plants without the expression of individual isoforms show no differences in growth and development, and are not significantly different from wild type plants in soluble sugars, starch and cellulose contents under all growth conditions investigated. Analysis of T-DNA insertion mutant lacking Sus3 isoform that was exclusively expressed in stomata cells only had a minor influence on guard cell osmoregulation and/or bioenergetics. Although none of the sucrose synthases appear to be essential for normal growth under our standard growth conditions, they may be necessary for growth under stress conditions. Different isoforms of sucrose synthase respond differently to various abiotic stresses. It has been shown that oxygen deprivation up regulates Sus1 and Sus4 and increases total Susy activity. However, the analysis of the plants with reduced expression of both Sus1 and Sus4 revealed no obvious effects on plant performance under oxygen deprivation. Low temperature up regulates Sus1 expression but the loss of this isoform has no effect on the freezing tolerance of non acclimated and cold acclimated plants. These data provide a comprehensive overview of the expression of this gene family which supports some of the previously reported roles for Susy and indicates the involvement of specific isoforms in metabolism and/or signalling.}, language = {en} } @phdthesis{Dolniak2005, author = {Dolniak, Blazej}, title = {Functional characterisation of NIC2, a member of the MATE family from Arabidopsis thaliana (L.) Heynh.}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-5372}, school = {Universit{\"a}t Potsdam}, year = {2005}, abstract = {The multidrug and toxic compounds extrusion (MATE) family includes hundreds of functionally uncharacterised proteins from bacteria and all eukaryotic kingdoms except the animal kingdom, that function as drug/toxin::Na+ or H+ antiporters. In Arabidopsis thaliana the MATE family comprises 56 members, one of which is NIC2 (Novel Ion Carrier 2). Using heterologous expression systems including Escherichia coli and Saccharomyces cerevisiae, and the homologous expression system of Arabidopsis thaliana, the functional characterisation of NIC2 was performed. It has been demonstrated that NIC2 confers resistance of E. coli towards the chemically diverse compounds such as tetraethylammonium chloride (TEACl), tetramethylammonium chloride (TMACl) and a toxic analogue of indole-3-acetic acid, 5-fluoro-indole-acetic acid (F-IAA). Therefore, NIC2 may be able to transport a broad range of drug and toxic compounds. In wild-type yeast the expression of NIC2 increased the tolerance towards lithium and sodium, but not towards potassium and calcium. In A. thaliana, the overexpression of NIC2 led to strong phenotypic changes. Under normal growth condtions overexpression caused an extremely bushy phenotype with no apical dominance but an enhanced number of lateral flowering shoots. The amount of rossette leaves and flowers with accompanying siliques were also much higher than in wild-type plants and the senescence occurred earlier in the transgenic plants. In contrast, RNA interference (RNAi) used to silence NIC2 expression, induced early flower stalk development and flowering compared with wild-type plants. In additon, the main flower stalks were not able to grow vertically, but instead had a strong tendency to bend towards the ground. While NIC2 RNAi seedlings produced many lateral roots outgrowing from the primary root and the root-shoot junction, NIC2 overexpression seedlings displayed longer primary roots that were characterised by a 2 to 4 h delay in the gravitropic response. In addition, these lines exhibited an enhanced resistance to exogenously applied auxins, i.e. indole-3-acetic acid (IAA) and indole-3-butyric acid (IBA) when compared with the wild-type roots. Based on these results, it is suggested that the NIC2 overexpression and NIC2 RNAi phenotypes were due to decreased or increased levels of auxin, respectively. The ProNIC2:GUS fusion gene revealed that NIC2 is expressed in the stele of the elongation zone, in the lateral root cap, in new lateral root primordia, and in pericycle cells of the root system. In the vascular tissue of rosette leaves and inflorescence stems, the expression was observed in the xylem parenchyma cells, while in siliques it was also in vascular tissue, but as well in the dehiscence and abscission zones. The organ- and tissue-specific expression sites of NIC2 correlate with the sites of auxin action in mature Arabidopsis plants. Further experiments using ProNIC2:GUS indicated that NIC2 is an auxin-inducible gene. Additionally, during the gravitropic response when an endogenous auxin gradient across the root tip forms, the GUS activity pattern of the ProNIC2:GUS fusion gene markedly changed at the upper side of the root tip, while at the lower side stayed unchanged. Finally, at the subcellular level NIC2-GFP fusion protein localised in the peroxisomes of Nicotana tabacum BY2 protoplasts. Considering the experimental results, it is proposed that the hypothetical function of NIC2 is the efflux transport which takes part in the auxin homeostasis in plant tissues probably by removing auxin conjugates from the cytoplasm into peroxisomes.}, subject = {Ackerschmalwand}, language = {en} } @phdthesis{Arvidsson2010, author = {Arvidsson, Samuel Janne}, title = {Identification of growth-related tonoplast proteins in Arabidopsis thaliana}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-52408}, school = {Universit{\"a}t Potsdam}, year = {2010}, abstract = {In a very simplified view, the plant leaf growth can be reduced to two processes, cell division and cell expansion, accompanied by expansion of their surrounding cell walls. The vacuole, as being the largest compartment of the plant cell, plays a major role in controlling the water balance of the plant. This is achieved by regulating the osmotic pressure, through import and export of solutes over the vacuolar membrane (the tonoplast) and by controlling the water channels, the aquaporins. Together with the control of cell wall relaxation, vacuolar osmotic pressure regulation is thought to play an important role in cell expansion, directly by providing cell volume and indirectly by providing ion and pH homestasis for the cytosoplasm. In this thesis the role of tonoplast protein coding genes in cell expansion in the model plant Arabidopsis thaliana is studied and genes which play a putative role in growth are identified. Since there is, to date, no clearly identified protein localization signal for the tonoplast, there is no possibility to perform genome-wide prediction of proteins localized to this compartment. Thus, a series of recent proteomic studies of the tonoplast were used to compile a list of cross-membrane tonoplast protein coding genes (117 genes), and other growth-related genes from notably the growth regulating factor (GRF) and expansin families were included (26 genes). For these genes a platform for high-throughput reverse transcription quantitative real time polymerase chain reaction (RT-qPCR) was developed by selecting specific primer pairs. To this end, a software tool (called QuantPrime, see http://www.quantprime.de) was developed that automatically designs such primers and tests their specificity in silico against whole transcriptomes and genomes, to avoid cross-hybridizations causing unspecific amplification. The RT-qPCR platform was used in an expression study in order to identify candidate growth related genes. Here, a growth-associative spatio-temporal leaf sampling strategy was used, targeting growing regions at high expansion developmental stages and comparing them to samples taken from non-expanding regions or stages of low expansion. Candidate growth related genes were identified after applying a template-based scoring analysis on the expression data, ranking the genes according to their association with leaf expansion. To analyze the functional involvement of these genes in leaf growth on a macroscopic scale, knockout mutants of the candidate growth related genes were screened for growth phenotypes. To this end, a system for non-invasive automated leaf growth phenotyping was established, based on a commercially available image capture and analysis system. A software package was developed for detailed developmental stage annotation of the images captured with the system, and an analysis pipeline was constructed for automated data pre-processing and statistical testing, including modeling and graph generation, for various growth-related phenotypes. Using this system, 24 knockout mutant lines were analyzed, and significant growth phenotypes were found for five different genes.}, language = {en} } @phdthesis{Steinhauser2004, author = {Steinhauser, Dirk}, title = {Inferring hypotheses from complex profile data - by means of CSB.DB, a comprehensive systems-biology database}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-2467}, school = {Universit{\"a}t Potsdam}, year = {2004}, abstract = {The past decades are characterized by various efforts to provide complete sequence information of genomes regarding various organisms. The availability of full genome data triggered the development of multiplex high-throughput assays allowing simultaneous measurement of transcripts, proteins and metabolites. With genome information and profiling technologies now in hand a highly parallel experimental biology is offering opportunities to explore and discover novel principles governing biological systems. Understanding biological complexity through modelling cellular systems represents the driving force which today allows shifting from a component-centric focus to integrative and systems level investigations. The emerging field of systems biology integrates discovery and hypothesis-driven science to provide comprehensive knowledge via computational models of biological systems. Within the context of evolving systems biology, investigations were made in large-scale computational analyses on transcript co-response data through selected prokaryotic and plant model organisms. CSB.DB - a comprehensive systems-biology database - (http://csbdb.mpimp-golm.mpg.de/) was initiated to provide public and open access to the results of biostatistical analyses in conjunction with additional biological knowledge. The database tool CSB.DB enables potential users to infer hypothesis about functional interrelation of genes of interest and may serve as future basis for more sophisticated means of elucidating gene function. The co-response concept and the CSB.DB database tool were successfully applied to predict operons in Escherichia coli by using the chromosomal distance and transcriptional co-responses. Moreover, examples were shown which indicate that transcriptional co-response analysis allows identification of differential promoter activities under different experimental conditions. The co-response concept was successfully transferred to complex organisms with the focus on the eukaryotic plant model organism Arabidopsis thaliana. The investigations made enabled the discovery of novel genes regarding particular physiological processes and beyond, allowed annotation of gene functions which cannot be accessed by sequence homology. GMD - the Golm Metabolome Database - was initiated and implemented in CSB.DB to integrated metabolite information and metabolite profiles. This novel module will allow addressing complex biological questions towards transcriptional interrelation and extent the recent systems level quest towards phenotyping.}, subject = {Datenbank}, language = {en} }