Cyclin dependent protein kinases and stress responses in plants

Plants have to adjust, grow and establish themselves in various changing environmental conditions. Additionally, the sessile life-style of plants requires the development of response mechanisms for their adaptation in such environmental cues. Under biotic and abiotic stress, plant growth is negatively affected mainly as a result of cell cycle inhibition. The perception of stress involves the activation of signaling cascades that result in a prolonged S-phase and delayed entry into mitosis. Although the molecular interactions that link the cell cycle machinery to perception of stress are not fully understood, recent studies indicated the involvement of Cyclin Dependent Kinases (CDKs) in the plant response machinery. CDKs are core cell cycle regulators but their activity has been implicated in additional diverse cellular processes. Here we review the impact of different types of abiotic stress on plant cell cycle progression and CDK activity, and discuss the contribution of CDK function in the signaling control of stress tolerance.Key words: abiotic stress, cell cycle, CDK, cyclin     

Edge-based scoring and searching method for identifying condition-responsive protein-protein interaction sub-network

MOTIVATION: Current high-throughput protein-protein interaction (PPI) data do not provide information about the condition(s) under which the interactions occur. Thus, the identification of condition-responsive PPI sub-networks is of great importance for investigating how a living cell adapts to changing environments. RESULTS: In this article, we propose a novel edge-based scoring and searching approach to extract a PPI sub-network responsive to conditions related to some investigated gene expression profiles. Using this approach, what we constructed is a sub-network connected by the selected edges (interactions), instead of only a set of vertices (proteins) as in previous works. Furthermore, we suggest a systematic approach to evaluate the biological relevance of the identified responsive sub-network by its ability of capturing condition-relevant functional modules. We apply the proposed method to analyze a human prostate cancer dataset and a yeast cell cycle dataset. The results demonstrate that the edge-based method is able to efficiently capture relevant protein interaction behaviors under the investigated conditions. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

The core diseasome

Large amounts of protein-protein interaction (PPI) data are available. The human PPI network currently contains over 56?000 interactions between 11?100 proteins. It has been demonstrated that the structure of this network is not random and that the same wiring patterns in it underlie the same biological processes and diseases. In this paper, we ask if there exists a subnetwork of the human PPI network such that its topology is the key to disease formation and hence should be the primary object of therapeutic intervention. We demonstrate that such a subnetwork exists and can be obtained purely computationally. In particular, by successively pruning the entire human PPI network, we are left with a "core" subnetwork that is not only topologically and functionally homogeneous, but is also enriched in disease genes, drug targets, and it contains genes that are known to drive disease formation. We call this subnetwork the Core Diseasome. Furthermore, we show that the topology of the Core Diseasome is unique in the human PPI network suggesting that it may be the wiring of this network that governs the mutagenesis that leads to disease. Explaining the mechanisms behind this phenomenon and exploiting them remains a challenge.     

Exploring the protein–protein interaction landscape in plants

Protein–protein interactions (PPIs) represent an essential aspect of plant systems biology. Identification of key protein players and their interaction networks provide crucial insights into the regulation of plant developmental processes and into interactions of plants with their environment. Despite the great advance in the methods for the discovery and validation of PPIs, still several challenges remain. First, the PPI networks are usually highly dynamic, and the in vivo interactions are often transient and difficult to detect. Therefore, the properties of the PPIs under study need to be considered to select the most suitable technique, because each has its own advantages and limitations. Second, besides knowledge on the interacting partners of a protein of interest, characteristics of the interaction, such as the spatial or temporal dynamics, are highly important. Hence, multiple approaches have to be combined to obtain a comprehensive view on the PPI network present in a cell. Here, we present the progress in commonly used methods to detect and validate PPIs in plants with a special emphasis on the PPI features assessed in each approach and how they were or can be used for the study of plant interactions with their environment.     

Strategies towards high-quality binary protein interactome maps

Many processes in a cell depend on protein–protein interactions (PPIs) and perturbations of these interactions can lead to diseases. Comprehensive knowledge of PPI networks will not only give us information on how the cell is organized, but will also provide new drug targets. Current binary PPI networks are mainly generated by high-throughput yeast two-hybrid. Due to the small overlap of these maps, it has long been assumed that these maps are of low quality containing many false positives. However, by using an orthogonal two-hybrid method, MAPPIT (mammalian protein–protein interaction trap), these maps were shown to be of high quality suggesting that the limited overlap is likely due to low sensitivity and not to low specificity.     

Time-course network analysis reveals TNF-α can promote G1/S transition of cell cycle in vascular endothelial cells

MOTIVATION: Tumor necrosis factor-alpha (TNF-α), a major inflammatory cytokine, is closely related to several cardiovascular pathological processes. However, its effects on the cell cycle of vascular endothelial cells (VECs) have been the subject of some controversy. To investigate the molecular mechanism underlying this process, we constructed time-course protein-protein interaction (PPI) networks of TNF-α induced regulation of cell cycle in VECs using microarray datasets and genome-wide PPI datasets. Then, we analyzed the topological properties of the responsive PPI networks and calculated the node degree and node betweenness centralization of each gene in the networks. We found that p21, p27 and cyclinD1, key genes of the G1/S checkpoint, are in the center of responsive PPI networks and their roles in PPI networks are significantly altered with induction of TNF-α. According to the following biological experiments, we proved that TNF-α can promote G(1)/S transition of cell cycle in VECs and facilitate the cell cycle activation induced by vascular endothelial growth factor. CONTACT: shaoli@mail.tsinghua.edu.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Plant cell cycle transitions

Three decades have passed since the first recognition of restriction checkpoints in the plant cell cycle. Although many core cell cycle genes have been cloned, the mechanisms that control the G1-->S and G2-->M transitions in plants have only recently started to be understood. The cyclin-dependent kinases (CDKs) play a central role in the regulation of the cell cycle, and the activity of these kinases is steered by regulatory subunits, the cyclins. The activities of CDK-cyclin complexes are further controlled by an intricate panoply of monitoring mechanisms, which result in oscillating CDK activity during the division cycle. These fluctuations trigger transitions between the different stages of the cell cycle.     

Cell cycle analysis of tumour-derived cultures ofCrepis capillaris: A kinetic analogy with proliferation of animal tumour cells

Summary Analysis of the cell cycle by three methods has revealed unusual kinetics of proliferation in tumour derived suspensions ofCrepis capillaris. The different methods of analysis yield different estimates of cycle phase durations, and such discrepancies have been explained in terms of low growth fractions with rapid total cycle traverse. Specifically, confidence in the estimation of G₂ duration by the fraction of labelled mitosis analysis, and comparison with shorter G₂ estimates obtained by the two other methods, suggests that cells drop out in G₁. However, cells which do not drop out of the proliferative compartment traverse G₁ extremely rapidly. Extremely short cell cycle durations in which the G₁ phase is virtually non-existent are uncharacteristic of plant cell suspension cultures, in which the G₁ phase has previously been shown to be extended as compared with meristematic root tip cells. A model has been proposed in which a central core of rapidly dividing cells continuously loses cells into a subpopulation of resting or G₀ cells with the G₁ DNA content. Similarities between plant and animal tumours with respect to cell growth and division are discussed.     

Dynamic Circadian Protein–Protein Interaction Networks Predict Temporal Organization of Cellular Functions

Essentially all biological processes depend on protein–protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (∼24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner.     

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation

Protein-protein interactions (PPIs) constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC) as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs) and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.     

A common neighbor based technique to detect protein complexes in PPI networks

Detection of protein complexes by analyzing and understanding PPI networks is an important task and critical to all aspects of cell biology. We present a technique called PROtein COmplex DEtection based on common neighborhood (PROCODE) that considers the inherent organization of protein complexes as well as the regions with heavy interactions in PPI networks to detect protein complexes. Initially, the core of the protein complexes is detected based on the neighborhood of PPI network. Then a merging strategy based on density is used to attach proteins and protein complexes to the core-protein complexes to form biologically meaningful structures. The predicted protein complexes of PROCODE was evaluated and analyzed using four PPI network datasets out of which three were from budding yeast and one from human. Our proposed technique is compared with some of the existing techniques using standard benchmark complexes and PROCODE was found to match very well with actual protein complexes in the benchmark data. The detected complexes were at par with existing biological evidence and knowledge.     

A new class of reversible cell cycle inhibitors

The effects of three compounds on the cell cycle of HL-60 promyeloid leukemia cells has been examined. Ciclopirox olamine, an antifungal agent, and the compound Hoechst 768159 reversibly block the cell cycle at a point occurring roughly 1 h before the arrest mediated by aphidicolin, an inhibitor of DNA polymerase alpha activity, which acts in early S phase. Similar results are also obtained with the compound mimosine, a plant amino acid. Based on these data, it is concluded that all three agents inhibit cell cycle traverse at or very near the G1/S phase boundary and identify a previously undefined reversible cell cycle arrest point.     

Localisation of <Emphasis Type="Italic">Arabidopsis</Emphasis> NDPK2—revisited

Phytochromes are light responsive photoreceptors in plants that influence development and differentiation during the entire plant life cycle. Plant nucleoside diphosphate kinase 2 (NDPK2) has been reported to be a component of the light-mediated signalling cascade and to interact physically with phytochrome A in the cytosol. By using diverse methods as in vitro imports, in vivo localisation of GFP-fusion proteins and immuno blotting of plant cell fractions we clearly localise NDPK2 only to chloroplasts but not to the cytosol, demonstrating that although high affinity protein–protein interactions can occur in vitro, their physiological relevance can be artificial if the proteins are localised to different cell compartments in vivo.     

Control of division and differentiation of plant stem cells and their derivatives

The core mechanism of the plant cell cycle is conserved with all other eukaryotes but several aspects are unique to plant cells. Key characteristics of plant development include indeterminate growth and repetitive organogenesis derived from stem cell pools and they may explain the existence of the high number of cell cycle regulators in plants. In this review, we give an overview of the plant cell cycle and its regulatory components. Furthermore, we discuss the cell cycle aspects of plant stem cell maintenance and how the cell cycle relates to cellular differentiation during development. We exemplify this transition by focusing on organ initiation in the shoot.     

Insights into the G1/S transition in plants

The G1/S transition generally represents the principal point of commitment to cell division. Many of the components of the cell cycle core machinery regulating the G1/S transition in plants have been recently identified. Although plant regulators of the G1/S transition display structural and biochemical homologies with their animal counterparts, their functions in integrating environmental stimuli and the developmental program within cell cycle progression are often plant-specific. In this review, recent progress in understanding the role of plant G1/S transition regulators is presented. Emerging evidence concerning the mechanisms of G1/S control in response to factors triggering the cell cycle and the integration of these mechanisms with plant development is also discussed.