Protein extraction from plant tissues for 2DE and its application in proteomic analysis

Plant tissues contain large amounts of secondary compounds that significantly interfere with protein extraction and 2DE analysis. Thus, sample preparation is a crucial step prior to 2DE in plant proteomics. This tutorial highlights the guidelines that need to be followed to perform an adequate total protein extraction before 2DE in plant proteomics. We briefly describe the history, development, and feature of major sample preparation methods for the 2DE analysis of plant tissues, that is, trichloroacetic acid/acetone precipitation and phenol extraction. We introduce the interfering compounds in plant tissues and the general guidelines for tissue disruption, protein precipitation and resolubilization. We describe in details the advantages, limitations, and application of the trichloroacetic acid/acetone precipitation and phenol extraction methods to enable the readers to select the appropriate method for a specific species, tissue, or cell type. The current applications of the sample preparation methods in plant proteomics in the literature are analyzed. A comparative proteomic analysis between male and female plants of Pistacia chinensis is used as an example to represent the sample preparation methodology in 2DE‐based proteomics. Finally, the current limitations and future development of these sample preparation methods are discussed. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP17).     

A proteomic analysis of maize chloroplast biogenesis

Proteomics studies to explore global patterns of protein expression in plant and green algal systems have proliferated within the past few years. Although most of these studies have involved mapping of the proteomes of various organs, tissues, cells, or organelles, comparative proteomics experiments have also led to the identification of proteins that change in abundance in various developmental or physiological contexts. Despite the growing use of proteomics in plant studies, questions of reproducibility have not generally been addressed, nor have quantitative methods been widely used, for example, to identify protein expression classes. In this report, we use the de-etiolation ("greening") of maize (Zea mays) chloroplasts as a model system to explore these questions, and we outline a reproducible protocol to identify changes in the plastid proteome that occur during the greening process using techniques of two-dimensional gel electrophoresis and mass spectrometry. We also evaluate hierarchical and nonhierarchical statistical methods to analyze the patterns of expression of 526 "high-quality," unique spots on the two-dimensional gels. We conclude that Adaptive Resonance Theory 2-a nonhierarchical, neural clustering technique that has not been previously applied to gene expression data-is a powerful technique for discriminating protein expression classes during greening. Our experiments provide a foundation for the use of proteomics in the design of experiments to address fundamental questions in plant physiology and molecular biology.     

Less label, more free: approaches in label-free quantitative mass spectrometry

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation.     

Proteomic studies in plants

Proteomics is a leading technology for the high-throughput analysis of proteins on a genome-wide scale. With the completion of genome sequencing projects and the development of analytical methods for protein characterization, proteomics has become a major field of functional genomics. The initial objective of proteomics was the large-scale identification of all protein species in a cell or tissue. The applications are currently being extended to analyze various functional aspects of proteins such as post-translational modifications, protein-protein interactions, activities and structures. Whereas the proteomics research is quite advanced in animals and yeast as well as Escherichia coli, plant proteomics is only at the initial phase. Major studies of plant proteomics have been reported on subcellular proteomes and protein complexes (e.g. proteins in the plasma membranes, chloroplasts, mitochondria and nuclei). Here several plant proteomics studies will be presented, followed by a recent work using multidimensional protein identification technology (MudPIT).     

Plasma membrane proteome in Arabidopsis and rice

Plant cells contain many membrane systems that are specially adapted to perform particular functions. In plant cells, the processing of signals that are involved in responses to biotic and abiotic stressors occurs in the plasma membrane. Therefore, characterization of the plasma membrane proteome can provide new insights into the functions of various plant membrane systems. Plant plasma membrane proteomics can also provide valuable information for plant-specific biological investigations. Despite recent advances in preparative and analytical techniques for plant plasma membrane proteins, the characterization of these proteins, particularly the hydrophobic ones, remains challenging. In this review, plant plasma membrane proteomics data compiled from the literature on Arabidopsis thaliana are presented. Initial attempts to determine the physiological significance of some proteins identified from plasma membrane proteomics in rice and other plants are also described from the results of our research.     

Supporting tool suite for production proteomics

SUMMARY: The large amount of data produced by proteomics experiments requires effective bioinformatics tools for the integration of data management and data analysis. Here we introduce a suite of tools developed at Vanderbilt University to support production proteomics. We present the Backup Utility Service tool for automated instrument file backup and the ScanSifter tool for data conversion. We also describe a queuing system to coordinate identification pipelines and the File Collector tool for batch copying analytical results. These tools are individually useful but collectively reinforce each other. They are particularly valuable for proteomics core facilities or research institutions that need to manage multiple mass spectrometers. With minor changes, they could support other types of biomolecular resource facilities.     

Challenges for proteomics core facilities

Many analytical techniques have been executed by core facilities established within academic, pharmaceutical and other industrial institutions. The centralization of such facilities ensures a level of expertise and hardware which often cannot be supported by individual laboratories. The establishment of a core facility thus makes the technology available for multiple researchers in the same institution. Often, the services within the core facility are also opened out to researchers from other institutions, frequently with a fee being levied for the service provided. In the 1990s, with the onset of the age of genomics, there was an abundance of DNA analysis facilities, many of which have since disappeared from institutions and are now available through commercial sources. Ten years on, as proteomics was beginning to be utilized by many researchers, this technology found itself an ideal candidate for being placed within a core facility. We discuss what in our view are the daily challenges of proteomics core facilities. We also examine the potential unmet needs of the proteomics core facility that may also be applicable to proteomics laboratories which do not function as core facilities.     

An assessment of software solutions for the analysis of mass spectrometry based quantitative proteomics data

Over the past decade, a series of experimental strategies for mass spectrometry based quantitative proteomics and corresponding computational methodology for the processing of the resulting data have been generated. We provide here an overview of the main quantification principles and available software solutions for the analysis of data generated by liquid chromatography coupled to mass spectrometry (LC-MS). Three conceptually different methods to perform quantitative LC-MS experiments have been introduced. In the first, quantification is achieved by spectral counting, in the second via differential stable isotopic labeling, and in the third by using the ion current in label-free LC-MS measurements. We discuss here advantages and challenges of each quantification approach and assess available software solutions with respect to their instrument compatibility and processing functionality. This review therefore serves as a starting point for researchers to choose an appropriate software solution for quantitative proteomic experiments based on their experimental and analytical requirements.     

Quantitative plant proteomics

Quantitation is an inherent requirement in comparative proteomics and there is no exception to this for plant proteomics. Quantitative proteomics has high demands on the experimental workflow, requiring a thorough design and often a complex multi-step structure. It has to include sufficient numbers of biological and technical replicates and methods that are able to facilitate a quantitative signal read-out. Quantitative plant proteomics in particular poses many additional challenges but because of the nature of plants it also offers some potential advantages. In general, analysis of plants has been less prominent in proteomics. Low protein concentration, difficulties in protein extraction, genome multiploidy, high Rubisco abundance in green tissue, and an absence of well-annotated and completed genome sequences are some of the main challenges in plant proteomics. However, the latter is now changing with several genomes emerging for model plants and crops such as potato, tomato, soybean, rice, maize and barley. This review discusses the current status in quantitative plant proteomics (MS-based and non-MS-based) and its challenges and potentials. Both relative and absolute quantitation methods in plant proteomics from DIGE to MS-based analysis after isotope labeling and label-free quantitation are described and illustrated by published studies. In particular, we describe plant-specific quantitative methods such as metabolic labeling methods that can take full advantage of plant metabolism and culture practices, and discuss other potential advantages and challenges that may arise from the unique properties of plants.     

Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease

Given superior analytical features, MS proteomics is well suited for the basic investigation and clinical diagnosis of human disease. Modern MS enables detailed functional characterization of the pathogenic biochemical processes, as achieved by accurate and comprehensive quantification of proteins and their regulatory chemical modifications. Here, we describe how high‐accuracy MS in combination with high‐resolution chromatographic separations can be leveraged to meet these analytical requirements in a mechanism‐focused manner. We review the quantification methods capable of producing accurate measurements of protein abundance and posttranslational modification stoichiometries. We then discuss how experimental design and chromatographic resolution can be leveraged to achieve comprehensive functional characterization of biochemical processes in complex biological proteomes. Finally, we describe current approaches for quantitative analysis of a common functional protein modification: reversible phosphorylation. In all, current instrumentation and methods of high‐resolution chromatography and MS proteomics are poised for immediate translation into improved diagnostic strategies for pediatric and adult diseases.     

Plant proteome analysis: a 2004-2006 update

Since the appearance of the review entitled "Plant Proteome Analysis" in Proteomics in February 2004 (Cánovas, F. M., Dumas-Gaudot, E., Recorbert, G., Jorrín, J. et al., Proteomics 2004, 4, 285-298), about 200 original articles focusing on plant proteomics have been published. Although this represents less than 1% of the global proteomics output during this period, it nevertheless reflects an increase in activity over the period 1999-2004. These papers concern the proteome of at least 35 plant species but have concentrated mainly on thale cress (Arabidopsis thaliana) and rice (Oryza sativa). The scientific objectives have ranged from a proteomic analysis of organs, tissues, cell suspensions, or subcellular fractions to the study of plant development and response to various stresses. A number of contributions have covered PTMs and protein interactions. The dominant analytical platform has been 2-DE coupled to MS, but "second generation" techniques such as DIGE, multidimensional protein identification technology, isotope-coded affinity tags, and stable isotope labeling by amino acids in cell culture have begun to make an impact. This review aims to provide an update of the contribution of proteomics to plant biology during the period 2004-2006, and is divided into six sections: introduction, subcellular proteomes, plant development, responses to biotic and abiotic stresses, PTMs, and protein interactions. The conclusions summarize a view of the major pitfalls and challenges of plant proteomics.     

非模式植物蛋白质组学研究进展

蛋白质组学研究是对基因组学研究的重要补充,它是在蛋白质水平定量、动态、整体性研究生物体。该文简要介绍了蛋白质组学的含义,蛋白质组学及植物蛋白质组学产生的科学背景,蛋白质组学的研究内容。概述了非模式植物蛋白质组学的研究进展,主要包括非模式植物个体及群体蛋白质组学,组织和器官蛋白质组学,亚细胞蛋白质组学,响应环境变化的蛋白质组学以及非模式植物生物环境因子的蛋白质组学的研究情况,同时对植物蛋白质组学的发展前景进行了展望。     

Proposal for a standard representation of two-dimensional gel electrophoresis data

The global analysis of proteins is now feasible due to improvements in techniques such as two-dimensional gel electrophoresis (2-DE), mass spectrometry, yeast two-hybrid systems and the development of bioinformatics applications. The experiments form the basis of proteomics, and present significant challenges in data analysis, storage and querying. We argue that a standard format for proteome data is required to enable the storage, exchange and subsequent re-analysis of large datasets. We describe the criteria that must be met for the development of a standard for proteomics. We have developed a model to represent data from 2-DE experiments, including difference gel electrophoresis along with image analysis and statistical analysis across multiple gels. This part of proteomics analysis is not represented in current proposals for proteomics standards. We are working with the Proteomics Standards Initiative to develop a model encompassing biological sample origin, experimental protocols, a number of separation techniques and mass spectrometry. The standard format will facilitate the development of central repositories of data, enabling results to be verified or re-analysed, and the correlation of results produced by different research groups using a variety of laboratory techniques.     

Recent progress in liquid chromatography-based separation and label-free quantitative plant proteomics

Recent innovations in liquid chromatography-mass spectrometry (LC-MS)-based methods have facilitated quantitative and functional proteomic analyses of large numbers of proteins derived from complex samples without any need for protein or peptide labelling. Regardless of its great potential, the application of these proteomics techniques to plant science started only recently. Here we present an overview of label-free quantitative proteomics features and their employment for analysing plants. Recent methods used for quantitative protein analyses by MS techniques are summarized and major challenges associated with label-free LC-MS-based approaches, including sample preparation, peptide separation, quantification and kinetic studies, are discussed. Database search algorithms and specific aspects regarding protein identification of non-sequenced organisms are also addressed. So far, label-free LC-MS in plant science has been used to establish cellular or subcellular proteome maps, characterize plant-pathogen interactions or stress defence reactions, and for profiling protein patterns during developmental processes. Improvements in both, analytical platforms (separation technology and bioinformatics/statistical analysis) and high throughput nucleotide sequencing technologies will enhance the power of this method.     

Time to articulate a vision for the future of plant proteomics - A global perspective: An initiative for establishing the International Plant Proteomics Organization (INPPO)

Given the essential role of proteomics in understanding the biology of plants, we are establishing a global plant proteomics organization to properly organize, preserve and disseminate collected information on plant proteomics. We call this organization 'International Plant Proteomics Organization (INPPO; http://www.inppo.com).' Ten initiatives of INPPO are outlined along with how to address them in multiple phases. As our vision is global, we sincerely hope the scientific communities around the world will come together to support and join INPPO.     

Mass spectrometry-based proteomics for the detection of plant pathogens

Plant diseases caused by fungi, oomycetes, viruses, and bacteria are devastating both to the economy and to the food supply of a nation. Therefore, the development of new, rapid methods to identify these pathogens is a highly important area of research that is of international concern. MS-based proteomics has become a powerful and increasingly popular approach to not only identify these pathogens, but also to better understand their biology. However, there is a distinction between identifying a pathogen protein and identifying a pathogen based upon the detection of one of its proteins and this must be considered before the general application of MS for plant pathogen detection is made. There has been a recent push in the proteomics community to make data from large-scale proteomics experiments publicly available in the form of a centralized repository. Such a resource could enable the use of MS as a universal plant pathogen detection technology.