Browsing by Person "Schulze, Waltraud"

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Adaptations of maize to low phosphate availability : establishing regulatory networks from large-scale quantitative proteomic profiling
(2022) He, Mingjie; Schulze, Waltraud
Maize (Zea mays) is an important crop in global for human food, animal feed and industrial usage. Suboptimal phosphorus (P) availability is one of the primary constraints for maize growth and productivity (Jianbo Shen et al., 2011; L.pez-Arredondo et al., 2014). Over 70% arable land suffers from P-deficiency, and plants can take up small amounts of P from the soil due to P-fixation. However, over-application of P fertilizer has frequently happened in last decades and resulted in environmental pollution (L.pez- Arredondo et al., 2014). Modern agriculture calls for maintaining productivity while reducing synthetic-P fertilizer inputs and losses, thus, requiring breeding of novel cultivars to increase phosphate use efficiency (PUE) (Balemi and Negisho, 2012; X., Li, Mang, et al., 2021; Mardamootoo et al., 2021). Understanding the regulation of maize to low phosphate(LP)-availability at the molecular level will offer unlimited potential for the development of selection markers and engineering targets in breeding programs. Nowadays, “OMIC” approaches and computational science are developing rapidly. They are advanced tools for investigation of molecular adaptations on a large-scale and in a systemic view. Thereby, the major research task within this thesis is to reveal P-deficiency induced responsive components and regulations at protein level based on proteomic profiles, aiming to provide promising candidate genes/proteins for research on the molecular mechanisms of adaptation to LP-stress, and potentially to provide promising candidate gene/proteins for development of selection markers and engineering targets to obtain desired traits, in the long term goal of improving PUE in novel cultivars. In Chapter 1, we focused on six genotypes (EP1, F2, F142, F160, SF1, SM1) with close genetic background but several contrasting traits to LP-stress, such as PUE (X., Li, Mang, et al., 2021). They were cultured in pot with either sufficient or inefficient P-fertilizer in a climate chamber for one month. The young seedlings were sampled by root and shoot for analysis of multiple traits, transcriptome and proteome. Firstly, we constructed the co-expression network of proteins and transcripts separately using WGCNA method (Langfelder and Horvath, 2008), which predicted potential protein-protein interactions or their co-regulations. Secondly, we categorized proteins/transcripts to modules according to their different coexpression patterns, thus, identified potential determining relationships of modules-traits. Thirdly, we compared the responses between transcripts and proteins, presenting their responses being concordant or dis-concordant. Fourthly, we identified common and genotype-specific P-starvation response modules and biological processes. Finally, we focused on protein kinases, which play roles as regulators, to demonstrated protein kinases-centered network and validated protein interactions between mitogenactivated protein kinase-kinase 1 (MEK1, Zm00001d043609) either with sucrose synthase1 (SH1,Zm00001d045042) or translation elongation factor 1-gamma 3 (eEF1B-γ, Zm00001d046352). MEK1 is a potential genotype-specific regulator via sucrose metabolism and translation elongation process. In Chapter 2, we aimed to adapted an experimental workflow for phosphoproteome analysis in maize, addressing the interference to phosphoproteome quantification by fibers, secondary metabolites and low abundant of phosphorylated proteins. In this manuscript, we described a rapid and universal protocol for both proteome and phosphoproteome analysis that is suitable for cereal crops. The results of phosphoproteome in maize root testing samples showed that proteins within kinase-centered network in Chapter 1 can be largely quantified based on this workflow. It provides a possible way to analyze phosphorylation dynamics to P-starvation responses, it allows further investigation for kinase-centered 1 network in Chapter 1 to identify phosphorylation pairs of “protein kinase – protein substrate”, which will largely expand a view on P-starvation regulations through posttranslational modifications.
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.
PEP7 is a ligand for receptor kinase SIRK1 to regulate aquaporins and root growth
(2021) Wang, Jiahui; Schulze, Waltraud
Receptor kinases constitute the largest protein family in regulating various responses to external and internal biotic and abiotic signals. Functional characterization of this large protein family and particularly the identification of their ligands remains a major challenge in plant biology. Previously, we identified SIRK1 and QSK1 as a receptor / co-receptor pair involved in regulation of aquaporins in response to osmotic changes induced by sucrose. Here, we now identify a member of the Elicitor Peptide (PEP) family, namely PEP7, as a ligand to receptor kinase SIRK1. PEP7 was shown to bind to the extracellular domain of SIRK1 with a binding constant of 19 µM. PEP7 was secreted to the apoplasm specifically in response to sucrose. Formation of a signaling complex involving SIRK1, QSK1 as well as aquaporins as substrates was induced by sucrose or external PEP7 treatment. PEP7 induced aquaporin phosphorylation and water influx activity. The knock-out mutant of receptor SIRK1 was not responsive to external PEP7 treatment. Binding to receptor SIRK1 and induction of physiological responses was specific to PEP7, neither other members of the PEP-family (PEP6, PEP4), nor other small signaling peptides (CLEs, IDA, RALFs) induced SIRK1 kinase activity, aquaporin phosphorylation, or protoplast water influx activity.
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.