Systems approaches to understanding cell signaling and gene regulation (original) (raw)
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Elucidating the regulation of complex signalling systems in plant cells
Biochemical Society Transactions, 2014
The pollen tube represents a model system for the study of tip growth, and the root provides a valuable system to study gene and signalling networks in plants. Here, using the two systems as examples, we discuss how to elucidate the regulation of complex signalling systems in plant cells. First, we discuss how hormones and related genes in plant root development form a complex interacting network, and their activities are interdependent. Therefore their roles in root development must be analysed as an integrated system, and elucidation of the regulation of each component requires the adaptation of a novel modelling methodology-regulation analysis. Second, hydrodynamics, cell wall and ion dynamics are all important properties that regulate plant cell growth. We discuss how regulation analysis can be applied to study the regulation of hydrodynamics, cell wall and ion dynamics, using pollen tube growth as a model system. Finally, we discuss future prospects for elucidating the regulation of complex signalling systems in plant cells.
ChemInform, 2005
The process of signal integration, which contributes to the regulation of multiple cellular activities, can be described in a digital language by a set of connected digital operations. In this article we delineate the basic concepts of cell signalling in the context of a logical description of information processing. Newly described instances of signal integration in plants are given as examples. The different advantages, limitations and predictive aspects of the digital modeling of signal transduction networks, as well as the minimal architecture of a computer database for plant signalling networks are discussed.
Systems Approaches to Identifying Gene Regulatory Networks in Plants
Annual Review of Cell and Developmental Biology, 2008
Complex gene regulatory networks are composed of genes, noncoding RNAs, proteins, metabolites, and signaling components. The availability of genome-wide mutagenesis libraries; large-scale transcriptome, proteome, and metabalome data sets; and new high-throughput methods that uncover protein interactions underscores the need for mathematical modeling techniques that better enable scientists to synthesize these large amounts of information and to understand the properties of these biological systems. Systems biology approaches can allow researchers to move beyond a reductionist approach and to both integrate and comprehend the interactions of multiple components within these systems. Descriptive and mathematical models for gene regulatory networks can reveal emergent properties of these plant systems. This review highlights methods that researchers are using to obtain large-scale data sets, and examples of gene regulatory networks modeled with these data. Emergent properties revealed by the use of these network models and perspectives on the future of systems biology are discussed.
Hubs and bottlenecks in plant molecular signalling networks
2010
Conditional control of plant cell function and development relies on appropriate signal perception, signal integration and processing. The development of high throughput technologies such as proteomics and interactomics has enabled the identification of protein interaction networks that mediate signal processing from inputs to appropriate outputs. Such networks can be depicted in graphical representations using nodes and edges allowing for the immediate visualization and analysis of the network's topology. Hubs are network elements characterized by many edges (often degree grade k ‡ 5) which confer a degree of topological importance to them. The review introduces the concept of networks, hubs and bottlenecks and describes four examples from plant science in more detail, namely hubs in the redox regulatory network of the chloroplast with ferredoxin, thioredoxin
Molecular Plant
Integration of internal and external cues into developmental programs is indispensable for growth and development of plants, which involves complex interplays among signaling pathways activated by the internal and external factors (IEFs). However, decoding these complex interplays is still challenging. Here, we present a web-based platform that identifies key regulators and Network models delineating Interplays among Developmental signaling (iNID) in Arabidopsis. iNID provides a comprehensive resource of 1) transcriptomes previously collected under the conditions treated with a broad spectrum of IEFs and 2) protein and genetic interactome data in Arabidopsis. In addition, iNID provides an array of tools for identifying key regulators and network models related to interplays among IEFs using transcriptome and interactome data. To demonstrate the utility of iNID, we investigated the interplays of 1) phytohormones and light and 2) phytohormones and biotic stresses. The results revealed...
Editorial: New Horizons in Plant Cell Signaling
International Journal of Molecular Sciences, 2022
Responding to environmental stimuli with appropriate molecular mechanisms is essential to all life forms and particularly so in sessile organisms such as plants. To this end, plants have evolved both rapid early mechanisms such as the activation of channels and kinases directly or indirectly through protein sensors, as well as the slower systemic adaptive responses that include changes in their transcriptomes and proteomes. To enable these processes and concomitantly tune their responses to the environment, complex cellular-signaling mechanisms have evolved, some of which have no homologues in animals. This Special Issue aims to broaden the current understanding of plant cell signaling, specifically highlighting recent and exciting discoveries such as the identification of novel signaling molecules and mechanisms that participate across all stages of plant growth and development, and in cellular and biological processes triggered by abiotic and biotic stresses.
Systems Biology Update: Cell Type-Specific Transcriptional Regulatory Networks
2009
Plant cells use regulatory networks composed of numerous components, such as DNA, RNA, proteins, and small molecules, to regulate multiple biological processes, allowing plants to adapt to changing environments or to respond to developmental cues. The availability of high-throughput experimental methods enables researchers to determine the expression levels for thousands of genes and protein protein or protein DNA interactions. Systems biology approaches can allow scientists to integrate these large amounts of information and to understand the properties of these biological systems in specific cells or tissues. Dynamic mathematical modeling approaches used to characterize plant transcriptional networks can reveal emergent properties of these networks. This review highlights some currently available methodologies used to obtain systems-scale data such as Laser Capture Microdissection (LCM), Fluorescent Activated Cell Sorting (FACS), ChIP-on-chip, proteomics, and modeling approaches that are most useful to explore plant transcriptional networks at the cellular level. We also provide two examples of transcriptional networks in single cell types and detail how such methods and data sets have been used to map and reveal emergent properties of gene regulatory networks that regulate cell identity specification.
Systems Biology: Principles and Applications in Plant Research
Plant Systems Biology, 2009
We cannot solve our problems with the same thinking we used when we created them' Albert Einstein Abstract: Plants have played a major role in the geochemical and climatic evolution of our planet. Today, in addition to their fundamental ecological importance plants are essential for humans as the main source of food, provide raw materials for many types of industry and chemicals for medical applications. It is thus daunting to realize how little we understand about plant systems. To date, only approximately 15% of the genes of Arabidopsis thaliana, the most explored model system for plant biologists, have been characterized experimentally. Systems biology offers the opportunity to increase our understanding of plants as living organisms, by generating a holistic view of the organism grounded at the molecular level. In this chapter, we discuss the basics of systems biology, the data and tools we need for systems research and how it can be used to produce an integrated view of plant biology. We finish with a discussion of case studies, published examples of plant systems biology research and their impact on our knowledge of plants as integrated systems.
Systems Analysis of Plant Functional, Transcriptional, Physical Interaction, and Metabolic Networks
The Plant Cell, 2012
Physiological responses, developmental programs, and cellular functions rely on complex networks of interactions at different levels and scales. Systems biology brings together high-throughput biochemical, genetic, and molecular approaches to generate omics data that can be analyzed and used in mathematical and computational models toward uncovering these networks on a global scale. Various approaches, including transcriptomics, proteomics, interactomics, and metabolomics, have been employed to obtain these data on the cellular, tissue, organ, and whole-plant level. We summarize progress on gene regulatory, cofunction, protein interaction, and metabolic networks. We also illustrate the main approaches that have been used to obtain these networks, with specific examples from Arabidopsis thaliana, and describe the pros and cons of each approach.
Transcriptome-based Gene Networks for Systems-level Analysis of Plant Gene Functions
2017
Present day genomic technologies are evolving at an unprecedented rate, allowing interrogation of cellular activities with increasing breadth and depth. However, we know very little about how the genome functions and what the identified genes do. The lack of functional annotations of genes greatly limits the post-analytical interpretation of new high throughput genomic datasets. For plant biologists, the problem is much severe. Less than 50% of all the identified genes in the model plant Arabidopsis thaliana, and only about 20% of all genes in the crop model Oryza sativa have some aspects of their functions assigned. Therefore, there is an urgent need to develop innovative methods to predict and expand on the currently available functional annotations of plant genes. With open-access catching the ‘pulse’ of modern day molecular research, an integration of the copious amount of transcriptome datasets allows rapid prediction of gene functions in specific biological contexts, which pro...