Browsing by Subject "Proteomanalyse"

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Deciphering the potential of large-scale proteomics to improve product quality and nutritional value in different wheat species
(2022) Afzal, Muhammad; Longin, Friedrich
Wheat (Triticum aestivum) is one of the most important staple crops globally, which provides on average ~20% of the dietary intake of protein, starch and further important ingredients like fiber, minerals, vitamins, and essential amino acids for humans. Besides common wheat, there exist further wheat species with global to only local importance, i.e., durum, spelt, emmer and einkorn. Common wheat and durum are relatively widely cultivated whereas the other three species are cultivated only in specific regions. Apart from other functions, wheat proteins largely influence the end-use quality of products such as bread and pasta quality. Furthermore, wheat proteins can induce inflammatory reactions in humans such as celiac disease, wheat allergy and non-celiac wheat sensitivity. Thus, proteome profiles of different wheat species and cultivars within these species are of high relevance for stakeholders along the wheat supply chain. Proteomic technology has made breakthrough advancements in the recent times capable of quantifying thousands of proteins in 1.5–2 hours. Also, the wheat reference genome has been published and extended recently. These developments are extremely helpful in studying the wheat proteome at a high resolution. However, the modern large-scale proteomics has yet neither been applied to perform comparative investigation of the proteomes of different wheat species nor to study the proteomes of different types of breads and flours nor to study its application in the context of plant breeding. Therefore, we utilized modern large-scale proteomics to fill these gaps within the framework of this PhD work. First of all, an optimized data analysis pipeline was designed to deal with big proteomics data. This was necessary to estimate a multitude of quantitative genetics parameters for each protein and perform a comparative investigation of the proteomes. Optimization included implementation of data filtering based on the quantification of a protein in a given proportion of the samples, cultivars and environments. Different tests such as test for normal distribution of each protein in the context of statistical modelling and test to check the equality of variance between groups to apply the appropriate t-test were incorporated into a semi-automated workflow. In parallel, we adjusted and improved the lab methodology to deal with hundreds of samples within a short time period. We introduced a novel hybrid liquid chromatography-mass spectrometry (LC-MS) approach that combines quantification concatamer (QconCAT) technology with short microflow LC gradients and data-independent acquisition (DIA). The proposed approach measures the proteome by label-free quantification (LFQ) while concurrently providing accurate QconCAT-based absolute quantification of the key amylase/trypsin inhibitors (ATIs). These methods were then applied to compare different wheat species based on dozens of cultivars grown at multiple locations. First, we compared common wheat and spelt and identified 3,050 proteins overall. Of total proteins, 1,555 proteins in spelt and 1,166 in common wheat were only detected in a subset of the field locations. There were 1,495 and 1,604 proteins in spelt and common wheat, respectively, which were consistently expressed across all test locations in at least one cultivar. Finally, there were 84 and 193 unique proteins for spelt and common wheat, respectively, as well as 396 joint proteins, which were significantly differentially expressed between the two species. Using potentially allergenic proteins – annotated as amylase/trypsin inhibitors, serpins, and wheat germ agglutinin – we calculated an equally weighted “allergen index” that largely varied across cultivars ranging from –13.32 to 10.88 indicating the potential to select for cultivars with favorable proteome profiles. Next, we examined the proteomes of six different flours (wholegrain and superfine flours) and 14 different bread types (yeast and sourdough fermented breads and common wheat breads plus/minus bread improver) from common wheat, spelt and rye. Proteins that could cause allergies were functionally classified and comparatively measured by LFQ in flours and breads. Our findings showed that allergenic proteins were more prevalent in common wheat and spelt than rye and were not specifically degraded during bread manufacturing. In terms of abundance of the allergenic proteins, there was almost no difference between spelt and common wheat and the type of grain is likely more important for allergenicity than milling or traditional fermentation techniques. In a further study, we generated the flour reference proteomes for five wheat species, identifying at least 2,540 proteins in each species. More than 50% of the proteins significantly differed between species. Particularly, einkorn expressed 5.4 and 7.2 times less allergens and amylase/trypsin inhibitors than common wheat, respectively, emerging as a potential alternative cereal crop for people with sensitivities to cereal allergens. Lastly, we studied the application of large-scale proteomics for plant breeding. We found a significant impact of the environmental factors on protein expression. Only a fraction of proteins was stably expressed in all environments in at least one cultivar. Environmental influence was observed not only in the form of absolute expression or suppression of a certain protein at one or more environments but also in the form of low heritability (H2). High coefficients of variation across wheat cultivars indicate that the protein profiles of different cultivars vary considerably. Although, heritability was low for many proteins, we were able to identify hundreds of proteins with H²>0.5 – including key proteins for baking quality and human health. It should be possible to specifically manipulate the expression of functionally important proteins with high heritability by selecting and breeding for superior wheat cultivars along the wheat supply chain. Nevertheless, a successful implementation in plant breeding programs needs an improvement in the speed of protein quantification methods and in the validation of protein functions and annotations. In a nutshell, high number of proteins can be quantified in cereal grains utilizing cutting-edge proteomics techniques, opening new avenues for their use in the wheat supply chain. We generated lists of intriguing candidate proteins for further investigations on wheat sensitivity, and proteins with high heritability and important biological functions. Current research work has significant implications for the scientific and business communities across multiple disciplines including breeding, agriculture, cereal technology, nutritional science, health, and medicine. Political decision-makers and stakeholders in the food supply chain can benefit from the findings of this PhD project.
External nutrition stimuli induced proteome and phosphoproteome responses of maize root hairs and arabidopsis root microsomal fraction
(2021) Li, Zhi; Schulze, Waltraud
This work studied how the proteome from young maize root hair cells responds to different nutrition deprivation, and gives perspectives to the possible involvement of NRT1.1 and NRT2.1 in regulating root membrane phosphoproteome responses. This work also proposes a phospho-switch model that may explain how the NRT2.1 activity was regulated.
Prediction of protein-protein complexes by combining size exclusion chromatography and mass spectrometric analysis
(2021) Gilbert, Max; Schulze, Waltraud
Two major objectives were pursued and met in this study. First, the goal was to add to the scientific toolbox a diligent method for uncovering PPi dynamics on a proteomic scale, with a focus on plant membranes. There are large-scale or high-throughput approaches, but they rely on genetically modified proteins or heterologous expression systems to describe PPi outside of their natural context. Similarly, those methods are incapable of describing the dynamics of protein interactions. In course of this study, a co-elution based approach was combined with modern mass spectrometric label free quantification in order to investigate PPi and interaction dynamics on a proteomic scale. A rigorous data processing pipeline was developed to not only address known fallacies of using co-elution based methods (such as for example random co elution), but also to access and utilize meta-information in form of protein abundance and protein network connectivity to draw conclusions not only on proteomic scale, but also for individual proteins. In total, 6.928 individual proteins extracted from Arabidopsis thaliana root membranes were detected under different nutritional conditions (full nutrition, nitrogen starvation and nitrogen resupply). The data processing pipeline described in this study was used to predict and discover connectivity information for at least 2.058 of these proteins. Each step in data processing was validated by comparison to database confirmed interactions to improve filtering criteria. Protein abundance was evaluated through a unique ranking system, allowing a seamless integration as network attributes for each condition. From the suggested interaction data, an interactome network of the various nutritional conditions was reconstructed. Using different network parameters from graph theory, protein significance and dynamic conditional changes were described. Second, this study applied the aforementioned approach to identify relevant proteins involved in nitrogen signaling in Arabidopsis thaliana root membranes. Through correlation analysis and network reconstruction, receptor kinase AT5G49770 was identified as a component of the nitrogen signaling network that collaborates with co-receptor QSK1, BAK1, the nitrogen transporter NRT2.1 and proton pump AHA2. In response to nitrogen deficiency, the network parameters of AT5G49770 reacted strongly and its involvement was demonstrated by a phenotypic similarity to knock-out lines of NRT2.1, NRT1.1 and AHA2 during a root growth assay of Arabidopsis seedlings. The interaction between QSK1 and BAK1 was further confirmed using FRET/FLIM microscopy and pulldown assays. These findings show that combining a co-elution based approach with a rigorous data processing pipeline and network analysis is suitable to study the protein interaction environment and signal response dynamics in plant root membranes. The modular experimental design allows for a simple adaptation to study different stimuli and the unbiased proteomic approach yields results for proteins regardless of the individual scientific focus. Meta-information such as protein abundance and network connectivity parameters can be used to prospect and identify important proteins involved in stress response dynamics. The author of this study is confident that the proteomic data produced can be utilized in further research and contributes to the understanding of nitrogen signaling in plant root membranes. Through integration of the data processing pipeline and adaptation to different scientific scenarios, valuable information beyond protein interaction is gained. Thus, this work makes an important contribution to the advancement of proteomic analysis and data interpretation methodology.
Quantitative Proteomanalyse von Pseudomonaden zur Aufklärung biotechnologisch relevanter Stoffwechselwege
(2013) Simon, Oliver; Huber, Armin
The main focus of this work was a quantitative proteome analysis of a variety of Pseudomonas strains with respect to the biotechnological synthesis of the base chemicals glyoxylic acid, butanol and vanillin. In addition, effects of the terpene citronellol on the proteome of P. aeruginosa were investigated. A second key aspect of this work involved the establishment of proteomics methods for the analysis of complex samples, especially for the analysis of membrane proteins. Using carbonate extraction followed by label-free MS-based quantification allowed the identification and quantification of a significant number of hydrophobic proteins which were not covered by the 2D-DIGE approach. In addition, the GeLCMSMS workflow was found to be a simple and efficient method for the analysis of total bacterial lysates. Using this method, about 30% of all proteins encoded by the P. putida KT2440 genome could be identified and quantified. In conclusion, this work demonstrated that different proteomics methods can substantially contribute to biotechnological strain development and the understanding of cellular networks.
Reaktionen einer Weizen-Wildkraut Gemeinschaft auf erhöhtes CO2 im FACE Experiment: Proteomik, Physiologie und Bestandesentwicklung
(2006) Weber, Simone; Fangmeier, Andreas
The enhancement of the atmospheric carbon dioxide concentration in the last 150 years due to human activities is one of the main components of global change. For the future, different scenarios predict a steadily increase of carbon dioxide in our atmosphere. As carbon dioxide is the most important carbon source for plants, higher CO2 concentrations have the potential to cause direct effects on plant metabolism and vegetation development. Until now almost all of the studies concerning the effects of elevated CO2 on plants were carried out under controlled conditions, whereas the effects under natural conditions are in-vestigated at only 33 sites worldwide. The aims of this study were to investigate the effects of elevated carbon dioxide on a plant community under natural conditions with regard of (i) the plant proteome, (ii) the plant physiology, (iii) the vegetation development and (iv) the potential interactions between these criteria. Therefore a Mini-FACE system was used to expose a plant community composed of wheat and weeds to two different treatments: (a) Ambient (ambient CO2 concentration, circa 380 ppm) and (b) FACE (Ambient + 150 ppm CO2). The study mainly focussed on the bio-chemical and physiological reactions of spring wheat (Triticum aestivum cv. Triso) as a crop species and wild mustard (Sinapis arvensis L.) as a weed species on carbon dioxide enrich-ment. The SELDI-TOF-MS technology was applied for the first time in the topic of carbon dioxide impacts on plants. The technology provides the opportunity to quantitatively and qualitatively investigate low molecular weight proteins with low abundances, which has been difficult to realise with the standardized methodology in proteomics until now. In addition to the biochemical and physiological analysis, the vegetation development was investigated continuously during the vegetation period using non-destructive methods. This included the assessment of species phenology and species dominance. The results of the performed study show that the carbon dioxide enrichment affects the protein profiles of both species wheat and wild mustard. Interestingly, many alterations in the protein concentrations were found, but no protein could be detected to be exclusively ex-pressed under CO2 treatment. The degree of modification in both species was influenced by their developmental stage. Particularly the protein profile of wheat leaves was strongly in-fluenced during generative plant development, therefore the plants seems to be highly sensitive to environmental changes during this developmental stage. Altogether three proteins were identified which were affected by CO2 treatment. The first protein, the saccharose-H+-symporter protein, was detected in the grain of spring wheat and is associated with the plant?s primary metabolism. This protein plays an important role in controlling the import of saccharose in developing grain. Consequently, elevated CO2 seems to regulate the allocation of assimilates in an active way by influencing the saccharose-H+-symporter concentration in the grain of spring wheat. Furthermore, the remaining two proteins, the PR4 protein localized in the grains and the LRR-kinase protein accumulated in the leaves of spring wheat, are associated with the secondary plant metabolism and they also responded to the elevated CO2 concentrations. These proteins are linked with defense reactions of the plants against patho-gens. The elevated CO2 concentrations caused a decrease in defense recognition in the vege-tative tissue. If the plant is infected by pathogens this down-regulation could result in a ne-gative impact. The concentration of soluble proteins and of total nitrogen decreased in the leaves of spring wheat whereas the C/N ratio increased. Despite this the relative concentration of Chlorophyll a was not affected and therefore an accelerated growth of the plants due to the carbon dioxide enrichment can be excluded. Thus the detected pattern of responses suggests an enhanced nitrogen use efficiency under increased CO2 concentrations. The biomass of single spring wheat plants was unaltered during the vegetation period whereas other investi-gations in parallel showed an enhanced growth and a greater yield of spring wheat at the end of the vegetation period. Species dominance of wheat and weeds was neither influenced in the first nor the second year of investigation with regard to CO2 enrichment. The results indicate that annual crop systems under natural conditions indeed exhibit strong reactions concerning proteomics and physiology, but not concerning the plant development probably due to a relative short time of exposition. Based on long term considerations the detected reactions of the plant proteome may play an important role in the breeding of optimal adapted plants.
Transcriptional and proteomic responses towards early nitrogen depletion in Arabidopsis thaliana
(2016) Menz, Jochen; Ludewig, Uwe
Plant roots acquire nitrogen predominantly as ammonium and nitrate, which besides serving as nutrients, also have signaling roles. Re-addition of nitrate to starved plants rapidly and di-rectly transcriptionally re-programs the metabolism and induces root architectural changes, but the earliest responses to nitrogen deprivation are unknown. In this thesis, the early transcriptional response of developed roots to nitrate or ammonium deprivation were analyzed in two Arabidopsis ecotypes contrasting in their nitrogen use efficiency: the inefficient genotype Col-0 and the efficient Tsu-0. The rapid transcriptional repression of known nitrate-induced genes proceeded the tissue NO3- concentration drop, with the transcription factor genes LBD37/38 and HRS1/HHO1 among those with earliest significant change. Some transcripts were stabilized by nitrate, but similar rapid transcriptional repression occurred in loss-of-function mutants of the nitrate response factor NLP7. In contrast, an early transcriptional response to ammonium deprivation was almost completely absent. In Col-0, the analysis was extended with the proteome and phospho-proteome resulting in a rapid and transient perturbation of the proteome induced by ammonium deprivation and a differential phosphorylation pattern in proteins involved in adjusting the pH and cation homeostasis, plasma membrane H+, NH4+, K+ and water fluxes. Fewer differential phosphorylation patterns in transporters, kinases and other proteins occurred with nitrate deprivation. The deprivation responses are not just opposite to the resupply responses, identify NO3--deprivation induced mRNA decay and signaling candidates potentially reporting the external nitrate status to the cell. Transcrip-tome comparison revealed only few N-nutrition related genes between both ecotypes contributing the increased NUE of Tsu-0, which probably relies on higher biomass accumulation. Besides, Tsu-0 confirmed the transcriptional depletion response of Col-0.