Reconstruction and analysis of nutrient-induced phosphorylation networks in Arabidopsis thaliana

A Data-Driven Signaling Network Inference Approach for Phosphoproteomics

Proteins are rapidly and dynamically post-transcriptionally modified as cells respond to changes in their environment. For example, protein phosphorylation is mediated by kinases while dephosphorylation is mediated by phosphatases. Quantifying and predicting interactions between kinases, phosphatases, and target proteins over time will aid the study of signaling cascades under a variety of environmental conditions. Here, we describe methods to statistically analyze label-free phosphoproteomic data and infer posttranscriptional regulatory networks over time. We provide an R-based method that can be used to normalize and analyze label-free phosphoproteomic data using variance stabilizing normalization and a linear mixed model across multiple time points and conditions. We also provide a method to infer regulator-target interactions over time using a discretization scheme followed by dynamic Bayesian modeling computations to validate our conclusions. Overall, this pipeline is designed to perform functional analyses and predictions of phosphoproteomic signaling cascades.

Spatial origin of the extracellular ATP-induced cytosolic calcium signature in Arabidopsis thaliana roots: wave formation and variation with phosphate nutrition

Extracellular ATP (eATP) increases cytosolic free calcium ([Ca²⁺ ]_cyt ) as a specific second messenger 'signature' through the plasma membrane DORN1/P2K1 receptor. Previous studies revealed a biphasic signature in Arabidopsis thaliana roots that is altered by inorganic phosphate (Pi) deprivation. The relationship between the two phases of the signature and possible wave formation have been tested as a function of Pi nutrition. The bioluminescent aequorin and intensiometric GCaMP3 reporters were used to resolve the spatial origin of the eATP [Ca²⁺ ]_cyt signature in Arabidopsis root tips. Application of eATP only to the root apex allowed [Ca²⁺ ]_cyt wave resolution without the confounding effects of eATP delivery by superfusion. The first apical millimetre of the root generates the first [Ca²⁺ ]_cyt increase by eATP, regardless of nutritional status. The second increase occurs sub-apically in the root hair zone, has some autonomy and is significantly reduced in Pi-starved roots. A significant component of the Pi-replete signature does not require DORN1/P2K1, but Pi-starved roots appear to have an absolute requirement for that receptor. Application of eATP specifically to the root apex provides evidence for cell-to-cell propagation of a [Ca²⁺ ]_cyt wave that diminishes sub-apically. The apex maintains a robust [Ca²⁺ ]_cyt increase (even under Pi starvation) that is the basis of a propagative wave, with implications for the ability of the root's eATP signalling systems to signal systemically. Partial autonomy of the sub-apical region may be relevant to the perception of eATP from microbes. eATP-induced [Ca²⁺ ]_cyt increase may not have always have an obligate requirement for DORN1/P2K1.

Computational Phosphorylation Network Reconstruction: An Update on Methods and Resources

Most proteins undergo some form of modification after translation, and phosphorylation is one of the most relevant and ubiquitous post-translational modifications. The succession of protein phosphorylation and dephosphorylation catalyzed by protein kinase and phosphatase, respectively, constitutes a key mechanism of molecular information flow in cellular systems. The protein interactions of kinases, phosphatases, and their regulatory subunits and substrates are the main part of phosphorylation networks. To elucidate the landscape of phosphorylation events has been a central goal pursued by both experimental and computational approaches. Substrate specificity (e.g., sequence, structure) or the phosphoproteome has been utilized in an array of different statistical learning methods to infer phosphorylation networks. In this chapter, different computational phosphorylation network inference-related methods and resources are summarized and discussed.

Phosphate and phosphite have a differential impact on the proteome and phosphoproteome of Arabidopsis suspension cell cultures

Phosphorus absorbed in the form of phosphate (H₂ PO₄^- ) is an essential but limiting macronutrient for plant growth and agricultural productivity. A comprehensive understanding of how plants respond to phosphate starvation is essential for the development of more phosphate-efficient crops. Here we employed label-free proteomics and phosphoproteomics to quantify protein-level responses to 48 h of phosphate versus phosphite (H₂ PO₃^- ) resupply to phosphate-deprived Arabidopsis thaliana suspension cells. Phosphite is similarly sensed, taken up and transported by plant cells as phosphate, but cannot be metabolized or used as a nutrient. Phosphite is thus a useful tool for differentiating between non-specific processes related to phosphate sensing and transport and specific responses to phosphorus nutrition. We found that responses to phosphate versus phosphite resupply occurred mainly at the level of protein phosphorylation, complemented by limited changes in protein abundance, primarily in protein translation, phosphate transport and scavenging, and central metabolism proteins. Altered phosphorylation of proteins involved in core processes such as translation, RNA splicing and kinase signaling was especially important. We also found differential phosphorylation in response to phosphate and phosphite in 69 proteins, including splicing factors, translation factors, the PHT1;4 phosphate transporter and the HAT1 histone acetyltransferase - potential phospho-switches signaling changes in phosphorus nutrition. Our study illuminates several new aspects of the phosphate starvation response and identifies important targets for further investigation and potential crop improvement.

Phosphoproteomics Profiling of Receptor Kinase Mutants

The transmembrane receptor kinase family is the largest protein kinase family in Arabidopsis. Many members of this family play critical roles in plant signaling pathways. However, many of these kinases have yet uncharacterized functions and very little is known about the direct substrates of these kinases. We have developed the "ShortPhos" method, an efficient and simple mass spectrometry (MS)-based phosphoproteomics protocol to perform comparative phosphopeptide profiling of knockout mutants of receptor-like kinases. Through this method, we are able to better understand the functional roles of plant kinases in the context of their signaling networks.

Determinants of correlated expression of transcription factors and their target genes

While transcription factors (TFs) are known to regulate the expression of their target genes (TGs), only a weak correlation of expression between TFs and their TGs has generally been observed. As lack of correlation could be caused by additional layers of regulation, the overall correlation distribution may hide the presence of a subset of regulatory TF-TG pairs with tight expression coupling. Using reported regulatory pairs in the plant Arabidopsis thaliana along with comprehensive gene expression information and testing a wide array of molecular features, we aimed to discern the molecular determinants of high expression correlation of TFs and their TGs. TF-family assignment, stress-response process involvement, short genomic distances of the TF-binding sites to the transcription start site of their TGs, few required protein-protein-interaction connections to establish physical interactions between the TF and polymerase-II, unambiguous TF-binding motifs, increased numbers of miRNA target-sites in TF-mRNAs, and a young evolutionary age of TGs were found particularly indicative of high TF-TG correlation. The modulating roles of post-transcriptional, post-translational processes, and epigenetic factors have been characterized as well. Our study reveals that regulatory pairs with high expression coupling are associated with specific molecular determinants.

The Systemin Signaling Cascade As Derived from Time Course Analyses of the Systemin-responsive Phosphoproteome

Systemin is a small peptide with important functions in plant wound response signaling. Although the transcriptional responses of systemin action are well described, the signaling cascades involved in systemin perception and signal transduction at the protein level are poorly understood. Here we used a tomato cell suspension culture system to profile phosphoproteomic responses induced by systemin and its inactive Thr17Ala analog, allowing us to reconstruct a systemin-specific kinase/phosphatase signaling network. Our time-course analysis revealed early phosphorylation events at the plasma membrane, such as dephosphorylation of H+-ATPase, rapid phosphorylation of NADPH-oxidase and Ca2+-ATPase. Later responses involved transient phosphorylation of small GTPases, vesicle trafficking proteins and transcription factors. Based on a correlation analysis of systemin-induced phosphorylation profiles, we predicted substrate candidates for 44 early systemin-responsive kinases, which includes receptor kinases and downstream kinases such as MAP kinases, as well as nine phosphatases. We propose a regulatory module in which H+-ATPase LHA1 is rapidly de-phosphorylated at its C-terminal regulatory residue T955 by phosphatase PLL5, resulting in the alkalization of the growth medium within 2 mins of systemin treatment. We found the MAP kinase MPK2 to have increased phosphorylation level at its activating TEY-motif at 15 min post-treatment. The predicted interaction of MPK2 with LHA1 was confirmed by in vitro kinase assays, suggesting that the H+-ATPase LHA1 is re-activated by MPK2 later in the systemin response. Our data set provides a resource of proteomic events involved in systemin signaling that will be valuable for further in-depth functional studies in elucidation of systemin signaling cascades.

The Scope, Functions, and Dynamics of Posttranslational Protein Modifications

Assessing posttranslational modification (PTM) patterns within protein molecules and reading their functional implications present grand challenges for plant biology. We combine four perspectives on PTMs and their roles by considering five classes of PTMs as examples of the broader context of PTMs. These include modifications of the N terminus, glycosylation, phosphorylation, oxidation, and N-terminal and protein modifiers linked to protein degradation. We consider the spatial distribution of PTMs, the subcellular distribution of modifying enzymes, and their targets throughout the cell, and we outline the complexity of compartmentation in understanding of PTM function. We also consider PTMs temporally in the context of the lifetime of a protein molecule and the need for different PTMs for assembly, localization, function, and degradation. Finally, we consider the combined action of PTMs on the same proteins, their interactions, and the challenge ahead of integrating PTMs into an understanding of protein function in plants.

Phosphate Starvation Alters Abiotic-Stress-Induced Cytosolic Free Calcium Increases in Roots

Phosphate (Pi) deficiency strongly limits plant growth, and plant roots foraging the soil for nutrients need to adapt to optimize Pi uptake. Ca²⁺ is known to signal in root development and adaptation but has to be tightly controlled, as it is highly toxic to Pi metabolism. Under Pi starvation and the resulting decreased cellular Pi pool, the use of cytosolic free Ca²⁺ ([Ca²⁺]_cyt) as a signal transducer may therefore have to be altered. Employing aequorin-expressing Arabidopsis (Arabidopsis thaliana), we show that Pi starvation, but not nitrogen starvation, strongly dampens the [Ca²⁺]_cyt increases evoked by mechanical, salt, osmotic, and oxidative stress as well as by extracellular nucleotides. The altered root [Ca²⁺]_cyt response to extracellular ATP manifests during seedling development under chronic Pi deprivation but can be reversed by Pi resupply. Employing ratiometric imaging, we delineate that Pi-starved roots have a normal response to extracellular ATP at the apex but show a strongly dampened [Ca²⁺]_cyt response in distal parts of the root tip, correlating with high reactive oxygen species levels induced by Pi starvation. Excluding iron, as well as Pi, rescues this altered [Ca²⁺]_cyt response and restores reactive oxygen species levels to those seen under nutrient-replete conditions. These results indicate that, while Pi availability does not seem to be signaled through [Ca²⁺]_cyt, Pi starvation strongly affects stress-induced [Ca²⁺]_cyt signatures. These data reveal how plants can integrate nutritional and environmental cues, adding another layer of complexity to the use of Ca²⁺ as a signal transducer.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

Plant genome-scale reconstruction: from single cell to multi-tissue modelling and omics analyses

In this review, we present the latest developments in plant systems biology with particular emphasis on plant genome-scale reconstructions and multi-omics analyses. Understanding multicellular metabolism is far from trivial and 'omics' data are difficult to interpret in the absence of a systems framework. 'Omics' data appropriately integrated with genome-scale reconstructions and modelling facilitates our understanding of how individual components interact and influence overall cell, tissue or organisms function. Here we present examples of how plant metabolic reconstructions and modelling are used as a systems-based framework for improving our understanding of the plant metabolic processes in single cells and multiple tissues.

From Phosphoproteome to Modeling of Plant Signaling Pathways

Quantitative proteomic experiments in recent years became almost routine in many aspects of biology. Particularly the quantification of peptides and corresponding phosphorylated counterparts from a single experiment is highly important for understanding of dynamics of signaling pathways. We developed an analytical method to quantify phosphopeptides (pP) in relation to the quantity of the corresponding non-phosphorylated parent peptides (P). We used mixed-mode solid-phase extraction to purify total peptides from tryptic digest and separated them from most of the phosphorous-containing compounds (e.g., phospholipids, nucleotides) which enhances pP enrichment on TiO2 beads. Phosphoproteomic data derived with this designed method allows quantifying pP/P stoichiometry, and qualifying experimental data for mathematical modeling.

Spatial proximity statistics suggest a regulatory role of protein phosphorylation on compound binding

Phosphorylation is an important post-translational modification that regulates protein function by the attachment of negatively charged phosphate groups to phosphorylatable amino acid residues. As a mode of action, an influence of phosphorylation on the binding of compounds to proteins has been discussed and described for a number of proteins in the literature. However, a systematic statistical survey probing for enriched phosphorylation sites close to compound binding sites in support of this notion and with properly chosen random reference distributions has not been presented yet. Using high-resolution protein structures from the Protein Data Bank including their co-crystallized non-covalently bound compounds and experimentally determined phosphorylation sites, we analyzed the pairwise distance distributions of phosphorylation and compound binding sites on protein surfaces. We found that phosphorylation sites are indeed located at significantly closer distances to compounds than expected by chance holding true specifically also for the subset of compound binding sites serving as catalytic sites of metabolic reactions. This tendency was particularly evident when treating phosphorylation sites as collective sets supporting the relevance of phosphorylation hotspots. Interestingly, phosphorylation sites were found to be closer to negatively charged than to positively charged compounds suggesting a stronger modulation of the binding of negatively charged compounds in dependence on phosphorylation status than on positively charged compounds. The enrichment of phosphorylation sites near compound binding sites confirms a regulatory role of phosphorylation in compound binding and provides a solid statistical basis for the literature-reported selected events.

The roles of post-translational modifications in the context of protein interaction networks

Among other effects, post-translational modifications (PTMs) have been shown to exert their function via the modulation of protein-protein interactions. For twelve different main PTM-types and associated subtypes and across 9 diverse species, we investigated whether particular PTM-types are associated with proteins with specific and possibly “strategic” placements in the network of all protein interactions by determining informative network-theoretic properties. Proteins undergoing a PTM were observed to engage in more interactions and positioned in more central locations than non-PTM proteins. Among the twelve considered PTM-types, phosphorylated proteins were identified most consistently as being situated in central network locations and with the broadest interaction spectrum to proteins carrying other PTM-types, while glycosylated proteins are preferentially located at the network periphery. For the human interactome, proteins undergoing sumoylation or proteolytic cleavage were found with the most characteristic network properties. PTM-type-specific protein interaction network (PIN) properties can be rationalized with regard to the function of the respective PTM-carrying proteins. For example, glycosylation sites were found enriched in proteins with plasma membrane localizations and transporter or receptor activity, which generally have fewer interacting partners. The involvement in disease processes of human proteins undergoing PTMs was also found associated with characteristic PIN properties. By integrating global protein interaction networks and specific PTMs, our study offers a novel approach to unraveling the role of PTMs in cellular processes.

The function of proteins is frequently modulated by chemical modifications introduced after translation from RNA. These post-translational modifications (PTMs) have been shown to also influence the interaction between proteins carrying them. We tested whether specific PTM-types characterized by attaching different chemical groups are associated with proteins with characteristic and possibly strategic positions within the network of all protein interactions in cellular systems. Based on network-theoretic analyses of PTMs in the context of protein interaction networks of nine selected species, we indeed observed distinctive properties of twelve PTM-types tested. Phosphorylation was found associated with proteins in central locations with the broadest interaction scope, while glycosylation was more prominent in proteins at the periphery of the web of all protein interactions. The involvement in disease processes of human proteins undergoing PTMs was also found associated with characteristic protein interaction network properties. Our study highlights common and specific roles of the various PTM types in the orchestration of molecular interactions in cells.

Phosphopeptide profiling of receptor kinase mutants

The family of transmembrane receptor kinase is the largest protein kinase family in Arabidopsis. However many of these kinases have yet uncharacterized functions and little is known about direct substrates of these kinases. Here, we present a large-scale phosphoproteomics method involving label-free quantitation-based comparative phosphopeptide profiling of knockout mutants in receptor-like kinases. This approach, among other physiological and cell biological experiments, is one step in understanding the functional roles of plant kinases in the context of their signaling networks.

Databases for plant phosphoproteomics

Phosphorylation is the most studied posttranslational modification involved in signal transduction in stress responses, development, and growth. In the recent years large-scale phosphoproteomic studies were carried out using various model plants and several growth and stress conditions. Here we present an overview of online resources for plant phosphoproteomic databases: PhosPhAt as a resource for Arabidopsis phosphoproteins, P3DB as a resource expanding to crop plants, and Medicago PhosphoProtein Database as a resource for the model plant Medicago trunculata.

Computational phosphorylation network reconstruction: methods and resources

The succession of protein activation and deactivation mediated by phosphorylation and dephosphorylation events constitutes a key mechanism of molecular information transfer in cellular systems. To deduce the details of those molecular information cascades and networks has been a central goal pursued by both experimental and computational approaches. Many computational network reconstruction methods employing an array of different statistical learning methods have been developed to infer phosphorylation networks based on different types of molecular data sets such as protein sequence, protein structure, or phosphoproteomics data. In this chapter, different computational network inference methods and resources for biological network reconstruction with a particular focus on phosphorylation networks are surveyed.