种子蛋白质组的研究进展

蛋白质组学是通过对全套蛋白质动态的研究, 来阐明生物体、组织、细胞和亚细胞全部蛋白质的表达模式及功能模式。大量可用的核苷酸序列信息和灵敏高速的质谱鉴定技术, 使得蛋白质组学方法为分析模式植物和农作物的复杂功能开辟了新的途径。目前, 种子蛋白质组研究主要集中在两个方面: 一方面是鉴定尽可能多的蛋白, 以创建种子特定生命时期的蛋白质组参照图谱; 另一方面主要集中在差异蛋白质组, 通过比较分析不同蛋白质组, 以探明关键功能蛋白。该文综述了近年来种子蛋白质组的研究进展, 内容包括种子发育过程中蛋白质组的变化, 与种子休眠/萌发相关的蛋白质组、翻译后修饰蛋白质组、细胞与亚细胞差异蛋白质组以及环境因子对种子蛋白质组的影响; 并对种子蛋白质组研究的热点问题进行了展望。     

种子蛋白质组的研究进展

蛋白质组学是通过对全套蛋白质动态的研究,来阐明生物体、组织、细胞和亚细胞全部蛋白质的表达模式及功能模式。大量可用的核苷酸序列信息和灵敏高速的质谱鉴定技术,使得蛋白质组学方法为分析模式植物和农作物的复杂功能开辟了新的途径。目前,种子蛋白质组研究主要集中在两个方面：一方面是鉴定尽可能多的蛋白,以创建种子特定生命时期的蛋白质组参照图谱;另一方面主要集中在差异蛋白质组,通过比较分析不同蛋白质组,以探明关键功能蛋白。该文综述了近年来种子蛋白质组的研究进展,内容包括种子发育过程中蛋白质组的变化,与种子休眠/萌发相关的蛋白质组、翻译后修饰蛋白质组、细胞与亚细胞差异蛋白质组以及环境因子对种子蛋白质组的影响;并对种子蛋白质组研究的热点问题进行了展望。     

Rejuvenating rice proteomics: facts, challenges, and visions

Proteomics is progressing at an unprecedented pace, as can be exemplified by the progress in model organisms such as yeast, bacteria, and mammals. Proteomics research in plants, however, has not progressed at the same pace. Unscrambling of the genome sequences of the dicotyledoneous Arabidopsis thaliana (L.) and monocotyledoneous rice (Oryza sativa L.) plant species, respectively, has made them accessible reference organisms to study plant proteomics. Study of these two reference plants is expected to unravel the mystery of plant biology. Rice, a critically important food crop on the earth, has been termed a "cornerstone" and the "Rosetta stone" for functional genomics of cereal crops. Here, we look at the progress in unraveling rice proteomes and present the facts, challenges, and vision. The text is divided into two major parts: the first part presents the facts and the second part discusses the challenges and vision. The facts include the technology and its use in developing proteomes, which have been critically and constructively reviewed. The challenges and vision deal with the establishment of technologies to exhaustively investigate the protein components of a proteome, to generate high-resolution gel-based reference maps, and to give rice proteomics a functional dimension by studying PTMs and isolation of multiprotein complexes. Finally, we direct a vision on rice proteomics. This is our third review in series on rice proteomics, which aims to stimulate an objective discussion among rice researchers and to understand the necessity and impact of unraveling rice proteomes to their full potential.     

Promise of multiphoton detection in discovery and diagnostic proteomics

Proteomics has lacked adequate methods for handling the complexity (hundreds of thousands of different proteins) and range of protein concentrations (> or =10(6)) of eukaryotic proteomes. New multiphoton-detection methods for ultrasensitive detection of proteins produce 10,000-fold gains in sensitivity and allow highly quantitative, linear detection of 50 zmol (30,000 molecules) to 500 fmol of proteins in complex samples. The potential of multiphoton detection in top-down proteomics analyses is illustrated with applications in monitoring proteomes in very small numbers of cells, in identifying and monitoring complex functional isoforms of cancer-related proteins, and in super-sensitive immunoassays of serum proteins for high-performance detection of cancer.     

Promise of multiphoton detection in discovery and diagnostic proteomics

Proteomics has lacked adequate methods for handling the complexity (hundreds of thousands of different proteins) and range of protein concentrations (≥10⁶) of eukaryotic proteomes. New multiphoton-detection methods for ultrasensitive detection of proteins produce 10,000-fold gains in sensitivity and allow highly quantitative, linear detection of 50 zmol (30,000 molecules) to 500 fmol of proteins in complex samples. The potential of multiphoton detection in top-down proteomics analyses is illustrated with applications in monitoring proteomes in very small numbers of cells, in identifying and monitoring complex functional isoforms of cancer-related proteins, and in super-sensitive immunoassays of serum proteins for high-performance detection of cancer.     

Plant cell organelle proteomics in response to abiotic stress

Proteomics is one of the finest molecular techniques extensively being used for the study of protein profiling of a given plant species experiencing stressed conditions. Plants respond to a stress by alteration in the pattern of protein expression, either by up-regulating of the existing protein pool or by the synthesizing novel proteins primarily associated with plants antioxidative defense mechanism. Improved protein extraction protocols and advance techniques for identification of novel proteins have been standardized in different plant species at both cellular and whole plant level for better understanding of abiotic stress sensing and intracellular stress signal transduction mechanisms. In contrast, an in-depth proteome study of subcellular organelles could generate much detail information about the intrinsic mechanism of stress response as it correlates the possible relationship between the protein abundance and plant stress tolerance. Although a wealth of reviews devoted to plant proteomics are available, review articles dedicated to plant cell organelle proteins response under abiotic stress are very scanty. In the present review, an attempt has been made to summarize all significant contributions related to abiotic stresses and their impacts on organelle proteomes for better understanding of plants abiotic stress tolerance mechanism at protein level. This review will not only provide new insights into the plants stress response mechanisms, which are necessary for future development of genetically engineered stress tolerant crop plants for the benefit of humankind, but will also highlight the importance of studying changes in protein abundance within the cell organelles in response to abiotic stress.     

Organellar proteomics: turning inventories into insights

Subcellular organization is yielding to large-scale analysis. Researchers are now applying robust mass-spectrometry-based proteomics methods to obtain an inventory of biochemically isolated organelles that contain hundreds of proteins. High-resolution methods allow accurate protein identification, and novel algorithms can distinguish genuine from co-purifying components. Organellar proteomes have been analysed by bioinformatic methods and integrated with other large-scale data sets. The dynamics of organelles can also be studied by quantitative proteomics, which offers powerful methods that are complementary to fluorescence-based microscopy. Here, we review the emerging trends in this rapidly expanding area and discuss the role of organellar proteomics in the context of functional genomics and systems biology.     

Methods of quantitative proteomics and their application to plant organelle characterization

Many cell biologists wish to know the subcellular localization of proteins of interest. Proteomics methods have the potential to describe the entire protein content of organelles. However, practical limitations in organelle isolation and analysis of low abundance proteins have meant that organelle proteomics has had, until recently, only limited success. Some examples of quantitative proteomic methods and their use in the study of plant organelle proteomes are discussed here. It is concluded that 2D-difference gel electrophoresis (2D-DIGE) as well as differential isotope tagging strategies coupled to non-gel-based LC-MS are proving useful in this area of research.     

Quantitative profile of five murine core proteomes using label-free functional proteomics

Analysis of primary animal and human tissues is key in biological and biomedical research. Comparative proteomics analysis of primary biological material would benefit from uncomplicated experimental work flows capable of evaluating an unlimited number of samples. In this report we describe the application of label-free proteomics to the quantitative analysis of five mouse core proteomes. We developed a computer program and normalization procedures that allow exploitation of the quantitative data inherent in LC-MS/MS experiments for relative and absolute quantification of proteins in complex mixtures. Important features of this approach include (i) its ability to compare an unlimited number of samples, (ii) its applicability to primary tissues and cultured cells, (iii) its straightforward work flow without chemical reaction steps, and (iv) its usefulness not only for relative quantification but also for estimation of absolute protein abundance. We applied this approach to quantitatively characterize the most abundant proteins in murine brain, heart, kidney, liver, and lung. We matched 8,800 MS/MS peptide spectra to 1,500 proteins and generated 44,000 independent data points to profile the approximately 1,000 most abundant proteins in mouse tissues. This dataset provides a quantitative profile of the fundamental proteome of a mouse, identifies the major similarities and differences between organ-specific proteomes, and serves as a paradigm of how label-free quantitative MS can be used to characterize the phenotype of mammalian primary tissues at the molecular level.     

Crop proteomics: aim at sustainable agriculture of tomorrow

The advent of proteomics has made it possible to identify a broad spectrum of proteins in living systems. This capability is especially useful for crops as it may give clues not only about nutritional value, but also about yield and how these factors are affected by adverse conditions. In this review, we describe the recent progress in crop proteomics and highlight the achievements made in understanding the proteomes of major crops. The major emphasis will be on crop responses to abiotic stresses. Rigorous genetic testing of the role of possibly important proteins can be conducted. The increasing ease with the DNA, mRNA and protein levels can be conducted and connected suggests that proteomics data will not be difficult to apply to practical crop breeding.     

Targeted proteomics on its way to discovery

For a long time, targeted and discovery proteomics covered different corners of the detection spectrum, with targeted proteomics focused on small target sets. This changed with the recent advances in highly multiplexed analysis. While discovery proteomics still pushes higher numbers of identified and quantified proteins, the advances in targeted proteomics rose to cover large parts of less complex proteomes or proteomes with low protein detection counts due to dynamic range restrictions, like the blood proteome. These new developments will impact, especially on the field of biomarker discovery and the possibility of using targeted proteomics for diagnostic purposes.     

Large-scale protein identification using mass spectrometry

Recent achievements in genomics have created an infrastructure of biological information. The enormous success of genomics promptly induced a subsequent explosion in proteomics technology, the emerging science for systematic study of proteins in complexes, organelles, and cells. Proteomics is developing powerful technologies to identify proteins, to map proteomes in cells, to quantify the differential expression of proteins under different states, and to study aspects of protein-protein interaction. The dynamic nature of protein expression, protein interactions, and protein modifications requires measurement as a function of time and cellular state. These types of studies require many measurements and thus high throughput protein identification is essential. This review will discuss aspects of mass spectrometry with emphasis on methods and applications for large-scale protein identification, a fundamental tool for proteomics.     

Avian proteomics: advances, challenges and new technologies

Proteomics is defined as an analysis of the full complement of proteins of a cell or tissue under given conditions. Avian proteomics, or more specifically chicken proteomics, has focussed on the study of individual tissues and organs of interest to specific researchers. Researchers have looked at skeletal muscle and growth, and embryonic development and have performed initial studies in avian disease. Traditional proteomics involves identifying and cataloguing proteins in a cell and identifying relative changes in populations between two or more states, be that physiological or disease-induced states. Recent advances in proteomic technologies have included absolute quantification, proteome simplification and the ability to determine the turnover of individual proteins in a global context. This review discusses the current developments in this relatively new field, new technologies and how they may be applied to biological questions, and the challenges faced by researchers in this ever-expanding and exciting field.     

Update and challenges on proteomics in rice

Rice is not only an important agricultural resource but also a model plant for biological research. Our previous review highlighted different aspects of the construction of rice proteome database, cataloguing rice proteins of different tissues and organelle, differential proteomics using 2-DE and functional characterization of some of the proteins identified (Komatsu, S., Tanaka, N., Proteomics 2005, 5, 938-949). In this review, the powerfulness and weaknesses of proteomic technologies as a whole and limitations of the currently used techniques in rice proteomics are discussed. The information obtained from these techniques regarding proteins modification, protein-protein interaction and the development of new methods for differential proteomics will aid in deciphering more precisely the functions of known and/or unknown proteins in rice.     

Mammalian plasma membrane proteomics

Plasma membrane proteins serve essential functions for cells, interacting with both cellular and extracellular components, structures and signaling molecules. Additionally, plasma membrane proteins comprise more than two-thirds of the known protein targets for existing drugs. Consequently, defining membrane proteomes is crucial to understanding the role of plasma membranes in fundamental biological processes and for finding new targets for action in drug development. MS-based identification methods combined with chromatographic and traditional cell-biology techniques are powerful tools for proteomic mapping of proteins from organelles. However, the separation and identification of plasma membrane proteins remains a challenge for proteomic technology because of their hydrophobicity and microheterogeneity. Creative approaches to solve these problems and potential pitfalls will be discussed. Finally, a representative overview of the impressive achievements in this field will also be given.     

From protein catalogues towards targeted proteomics approaches in cereal grains

Due to their importance for human nutrition, the protein content of cereal grains has been a subject of intense study for over a century and cereal grains were not surprisingly one of the earliest subjects for 2D-gel-based proteome analysis. Over the last two decades, countless cereal grain proteomes, mostly derived using 2D-gel based technologies, have been described and hundreds of proteins identified. However, very little is still known about post-translational modifications, subcellular proteomes, and protein-protein interactions in cereal grains. Development of techniques for improved extraction, separation and identification of proteins and peptides is facilitating functional proteomics and analysis of sub-proteomes from small amounts of starting material, such as seed tissues. The combination of proteomics with structural and functional analysis is increasingly applied to target subsets of proteins. These “next-generation” proteomics studies will vastly increase our depth of knowledge about the processes controlling cereal grain development, nutritional and processing characteristics.     

Plastid proteomics

Plastids are essential organelles present in virtually all cells in plants and in green algae. The proteomes of plastids, and in particular of chloroplasts, have received significant amounts of attention in recent years. Various fractionation and mass spectrometry (MS) techniques have been applied to catalogue the chloroplast proteome and its membrane compartments. Neural network and hidden Markov models, in combination with experimentally derived filters, were used to try to predict the chloroplast subproteomes. Some of the many protein-protein interaction, as well as post-translational modifications have been characterized. Nevertheless, our understanding of the chloroplast proteome and its dynamics is very incomplete. Rapid improvements and wide-scale implementation of MS and new tools for comparative proteomics will undoubtedly accelerate this understanding in the near future. Proteomics studies often generate a large amount of data and these data are only meaningful if they can be easily accessed via the 'world-wide-web' and connected to other types of biological information. The plastid proteome data base (PPDB at http://www.ppdb.tc.cornell.edu/) and other web resources are discussed. This review will briefly summarize recent experimental and theoretical efforts, attempt to translate these data into the functions of the chloroplast and outline expectations and possibilities for (comparative) chloroplast proteomics.     

Viral proteomics: The emerging cutting-edge of virus research

Viruses replicate and proliferate in host cells while continuously adjusting to and modulating the host environment. They encode a wide spectrum of multifunctional proteins, which interplay with and modify proteins in host cells. Viral genomes were chronologically the first to be sequenced. However, the corresponding viral proteomes, the alterations of host proteomes upon viral infection, and the dynamic nature of proteins, such as post-translational modifications, enzymatic cleavage, and activation or destruction by proteolysis, remain largely unknown. Emerging high-throughput techniques, in particular quantitative or semi-quantitative mass spectrometry-based proteomics analysis of viral and cellular proteomes, have been applied to define viruses and their interactions with their hosts. Here, we review the major areas of viral proteomics, including virion proteomics, structural proteomics, viral protein interactomics, and changes to the host cell proteome upon viral infection.