基于质谱的BLAST方法在金鱼胚胎蛋白质鉴定中的应用

未知基因组及蛋白质序列数据库有限的物种的蛋白质组学分析是当前一些非模式生物物种蛋白质组学研究领域的瓶颈之一.基于同源性搜索的BLAST方法（MS BLAST）,是近年新发展起来的一种用于未知基因组的蛋白质鉴定的搜索工具,已成功应用于许多未知基因组物种的蛋白质鉴定.SPITC化学辅助方法是本实验室建立的一种改进的de novo质谱测序方法.采用MS BLAST方法对经Mascot软件数据库搜索未能鉴定到的19个金鱼胚胎蛋白质进行鉴定,其中12个蛋白质是直接测序后进行MS BLAST搜索得到的结果,另外7个蛋白质是联合MS BLAST和SPITC衍生方法得到的鉴定结果.实验结果证明,采用MS BLAST方法进行蛋白质的跨物种鉴定具有可行性和可靠性,给蛋白质的跨物种鉴定提供了一条新的途径.     

What can proteomic analyses contribute to understanding the molecular biology and clinical behavior of prostate cancer?

Identifying the proteins and their complex interactions that promote and/or sustain the aggressive malignant phenotype is essential for understanding key effectors of the molecular biology of prostate cancer. This is also essential for development of new clinical applications. A variety of proteomic techniques, ranging from mass spectrometry to new methods of multiplexing protein identification, have great potential for rapidly achieving these goals. However, in order to obtain meaningful results, these techniques must be applied within the context of our knowledge of the heterogeneity of prostate tissues and tumors, the impact of specimen processing on both the quality and quantity of proteins detected and a thorough understanding of prostate cell biology. Collaboration between the protein chemist and the prostate cell biologist will expedite progress in this important field.     

What can proteomic analyses contribute to understanding the molecular biology and clinical behavior of prostate cancer?

Identifying the proteins and their complex interactions that promote and/or sustain the aggressive malignant phenotype is essential for understanding key effectors of the molecular biology of prostate cancer. This is also essential for development of new clinical applications. A variety of proteomic techniques, ranging from mass spectrometry to new methods of multiplexing protein identification, have great potential for rapidly achieving these goals. However, in order to obtain meaningful results, these techniques must be applied within the context of our knowledge of the heterogeneity of prostate tissues and tumors, the impact of specimen processing on both the quality and quantity of proteins detected and a thorough understanding of prostate cell biology. Collaboration between the protein chemist and the prostate cell biologist will expedite progress in this important field.     

Identification and Characterization of Proteins Associated with Plant Tolerance to Heat Stress

Heat stress is a major abiotic stress limiting plant growth and productivity in many areas of the world. Understanding mechanisms of plant adaptation to heat stress would facilitate the development of heat-tolerant cultivars for improving productivity in warm climatic regions. Protein metabolism involving protein synthesis and degradation is one of the most sensitive processes to heat stress. Changes in the level and expression pattern of some proteins may play an important role in plant adaptation to heat stress. The identification of stress-responsive proteins and pathways has been facilitated by an increasing number of tools and resources, including two-dimensional electrophoresis and mass spectrometry, and the rapidly expanding nucleotide and amino acid sequence databases. Heat stress may induce or enhance protein expression or cause protein degradation. The induction of heat-responsive proteins, particularly heat shock proteins (HSPs), plays a key role in plant tolerance to heat stress. Protein degradation involving various proteases is also important in regulating plant responses to heat stress. This review provides an overview of recent research on proteomic profiling for the identification of heat-responsive proteins associated with heat tolerance, heat induction and characteristics of HSPs, and protein degradation in relation to plant responses to heat stress.     

Identification and Characterization of Proteins Associated with Plant Tolerance to Heat Stress

Heat stress is a major abiotic stress limiting plant growth and productivity in many areas of the world. Understanding mechanisms of plant adaptation to heat stress would facilitate the development of heat-tolerant cultivars for improving productivity in warm climatic regions. Protein metabolism involving protein synthesis and degradation is one of the most sensitive processes to heat stress. Changes in the level and expression pattern of some proteins may play an important role in plant adaptation to heat stress. The identification of stress-responsive proteins and pathways has been facilitated by an increasing number of tools and resources, including two-dimensional electrophoresis and mass spectrometry, and the rapidly expanding nucleotide and amino acid sequence databases. Heat stress may induce or enhance protein expression or cause protein degradation. The induction of heat-responsive proteins, particularly heat shock proteins (HSPs), plays a key role in plant tolerance to heat stress. Protein degradation involving various proteases is also important in regulating plant responses to heat stress. This review provides an overview of recent research on proteomic profiling for the identification of heat-responsive proteins associated with heat tolerance, heat induction and characteristics of HSPs, and protein degradation in relation to plant responses to heat stress.     

Computational methods for protein identification from mass spectrometry data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.     

The power and the limitations of cross-species protein identification by mass spectrometry-driven sequence similarity searches

Mass spectrometry-driven BLAST (MS BLAST) is a database search protocol for identifying unknown proteins by sequence similarity to homologous proteins available in a database. MS BLAST utilizes redundant, degenerate, and partially inaccurate peptide sequence data obtained by de novo interpretation of tandem mass spectra and has become a powerful tool in functional proteomic research. Using computational modeling, we evaluated the potential of MS BLAST for proteome-wide identification of unknown proteins. We determined how the success rate of protein identification depends on the full-length sequence identity between the queried protein and its closest homologue in a database. We also estimated phylogenetic distances between organisms under study and related reference organisms with completely sequenced genomes that allow substantial coverage of unknown proteomes.     

Proteomic and phosphoproteomic analyses of NaCl stress-responsive proteins in Arabidopsis roots

Salt is one of the major abiotic stresses limiting the productivity and the geographical distribution of crops. To gain a better understanding of NaCl stress responses in model plant Arabidopsis roots, the protein changes in the abundance (Coomassie Brilliant Blue R-350 stain) and phosphorylation (Pro-Q Diamond stain) were examined using two-dimensional electrophoresis coupled with mass spectrometry (MS). Seventeen unique proteins differentially changed in abundance, phosphorylation, or both in response to NaCl. Nonsynchronous differences were found between total proteins and phosphorylated proteins. Protein synthesis, proteolysis, post-translational modifications, and isoforms might cause the differential protein redundancies. The identified proteins are involved in binding, catalysis, signal transduction, transport, metabolisms of cell wall and energy, and reactive oxygen species (ROS) scavenging and defense. These protein changes provide new avenues of investigation into the underlying salt stress response in Arabidopsis roots and demonstrate the advantages of proteomic approach in plant biology studies.     

Large-scale identification of proteins in human salivary proteome by liquid chromatography/mass spectrometry and two-dimensional gel electrophoresis-mass spectrometry

Human saliva contains a large number of proteins and peptides (salivary proteome) that help maintain homeostasis in the oral cavity. Global analysis of human salivary proteome is important for understanding oral health and disease pathogenesis. In this study, large-scale identification of salivary proteins was demonstrated by using shotgun proteomics and two-dimensinal gel electrophoresis-mass spectrometry (2-DE-MS). For the shotgun approach, whole saliva proteins were prefractionated according to molecular weight. The smallest fraction, presumably containing salivary peptides, was directly separated by capillary liquid chromatography (LC). However, the large protein fractions were digested into peptides for subsequent LC separation. Separated peptides were analyzed by on-line electrospray tandem mass spectrometry (MS/MS) using a quadrupole-time of flight mass spectrometer, and the obtained spectra were automatically processed to search human protein sequence database for protein identification. Additionally, 2-DE was used to map out the proteins in whole saliva. Protein spots 105 in number were excised and in-gel digested; and the resulting peptide fragments were measured by matrix-assisted laser desorption/ionization-mass spectrometry and sequenced by LC-MS/MS for protein identification. In total, we cataloged 309 proteins from human whole saliva by using these two proteomic approaches.     

Advances in quantitative proteomics via stable isotope tagging and mass spectrometry

The high-throughput identification and accurate quantification of proteins are essential components of proteomic strategies for studying cellular functions and processes. Techniques that are largely based on stable isotope protein or peptide labeling and automated tandem mass spectrometry are increasingly being applied in quantitative proteomic studies. Over the past year, significant progress has been made toward improving and diversifying these technologies with respect to the methods for stable isotope labeling, process automation and data processing and analysis. Advances in stable isotope protein labeling and recent biological studies that used stable isotope based quantitative proteomics techniques are reviewed.     

A versatile method for deciphering plant membrane proteomes

Proteomics is a very powerful approach to link the information contained in sequenced genomes, like that of Arabidopsis, to the functional knowledge provided by studies of plant cell compartments. This article summarizes the different steps of a versatile strategy that has been developed to decipher plant membrane proteomes. Initiated with envelope membranes from spinach chloroplasts, this strategy has been adapted to thylakoids, and further extended to a series of membranes from the model plant Arabidopsis: chloroplast envelope membranes, plasma membrane, and mitochondrial membranes. The first step is the preparation of highly purified membrane fractions from plant tissues. The second step in the strategy is the fractionation of membrane proteins on the basis of their physico-chemical properties. Chloroform/methanol extraction and washing of membranes with NaOH, NaCl or any other agent led to the simplification of the protein content of the fraction to be analysed. The next step is the genuine proteomic step, i.e. the separation of proteins by 1D-gel electrophoresis followed by in-gel proteolytic digestion of the polypeptides, analysis of the proteolytic peptides using mass spectrometry, and protein identification by searching through databases. The last step is the validation of the procedure by checking the subcellular location. The results obtained by using this strategy demonstrate that a combination of different proteomics approaches, together with bioinformatics, indeed provide a better understanding of the biochemical machinery of the different plant membranes at the molecular level.     

Focus on plant proteomics.

Proteomics covers the systematic analysis of proteins expressed by a genome, from the identification of their primary amino-acid sequence to the determination of their relative amounts, their state of modification and association with other proteins or molecules of different types. Tremendous progress has been made in this field in the past few years, especially in plant biology, mostly due to major developments of mass spectrometry dedicated to protein analyses and advanced information technology. The aim of this special issue of Plant Physiology and Biochemistry devoted to Plant Proteomics is not to present a comprehensive coverage of this rapidly expanding field but to focus on the representation of some key aspects to illustrate the importance of proteomics in plant functional genomics.     

Accumulation of “Old Proteins” and the Critical Need for MS‐based Protein Turnover Measurements in Aging and Longevity

Aging and age‐related diseases are accompanied by proteome remodeling and progressive declines in cellular machinery required to maintain protein homeostasis (proteostasis), such as autophagy, ubiquitin‐mediated degradation, and protein synthesis. While many studies have focused on capturing changes in proteostasis, the identification of proteins that evade these cellular processes has recently emerged as an approach to studying the aging proteome. With advances in proteomic technology, it is possible to monitor protein half‐lives and protein turnover at the level of individual proteins in vivo. For large‐scale studies, these technologies typically include the use of stable isotope labeling coupled with MS and comprehensive assessment of protein turnover rates. Protein turnover studies have revealed groups of highly relevant long‐lived proteins (LLPs), such as the nuclear pore complexes, extracellular matrix proteins, and protein aggregates. Here, the role of LLPs during aging and age‐related diseases and the methods used to identify and quantify their changes are reviewed. The methods available to conduct studies of protein turnover, used in combination with traditional proteomic methods, will enable the field to perform studies in a systems biology context, as changes in proteostasis may not be revealed in studies that solely measure differential protein abundances.     

Proteomic analysis of rutin-induced secreted proteins from Aspergillus flavus

Few studies have been conducted to identify the extracellular proteins and enzymes secreted by filamentous fungi, particularly with respect to dispensable metabolic pathways. Proteomic analysis has proven to be the most powerful method for identification of proteins in complex mixtures and is suitable for the study of the alteration of protein expression under different environmental conditions. The filamentous fungus Aspergillus flavus can degrade the flavonoid rutin as the only source of carbon via an extracellular enzyme system. In this study, a proteomic analysis was used to differentiate and identify the extracellular rutin-induced and non-induced proteins secreted by A. flavus. The secreted proteins were analyzed by two-dimensional electrophoresis and MALDI-TOF mass spectrometry. While 15 rutin-induced proteins and 7 non-induced proteins were identified, more than 90 protein spots remain unidentified, indicating that these proteins are either novel proteins or proteins that have not yet been sequenced.     

Mass spectrometry and database search in the analysis of proteins from the fungus Pleurotus ostreatus

Tandem mass spectrometry is a method of choice for rapid analysis in proteomics. Identification and characterization of proteins from organisms with sequenced genomes is today a routine procedure as will be identification of proteins from organisms with unsequenced genomes with new developing tools. Here, we report the use of isotopic labeling with electrospray ionisation (ESI)-tandem mass spectrometry for de novo sequencing in combination with database search taking advantage of different programs for identification of fungal proteins. Using this approach we could identify the proteins of interest. Nevertheless, the identification of a novel protein responsible for the conversion of testosterone into androstenedione was still a difficult task, mostly due to the low homology of steroid transforming enzymes, especially those from microorganisms. Protein p27 was identified as the vanillate O-demethylase oxidoreductase, p33 and p36 as two isoenzymes of malate dehydrogenase, and p45 as citrate synthase. By rechecking the sequences using additional programs it could be shown that the protein p36 has a higher local homology to the steroid-transforming enzyme than to the malate dehydrogenase. Therefore, we assume that p36 is a pluripotent enzyme most probably responsible for the 17beta-hydroxysteroid dehydrogenase activity.     

对脂肪滴的新认识

早在 1674 年, van Leeuwenhoeck 就首次在牛奶里发现了脂肪滴 . 从那以后, 300 多年过去了,有关脂肪滴的许多根本问题仍然没有得到解决 . 迄今,除有为数不多的几个脂肪滴表面蛋白被发现外,人类对脂肪滴的认识仍停留在其作为中性脂贮存器上 . 为了更好地认识脂肪滴,我们以及其他几个研究小组分别从不同细胞中纯化了脂肪滴,然后使用质谱蛋白分析对这些脂肪滴的蛋白质进行了蛋白质组学研究,从中发现了两组非常有意义的功能蛋白 . 一组是与脂肪合成及代谢有关的酶,另一组则是与膜转运有关的蛋白质 . 尽管这些实验使用了不同的细胞,而且是由不同实验室分别完成的,但结果却非常相似 . 这些发现表明,脂肪滴有可能是一种具有生理代谢活性的非常复杂的细胞器 . 同时,它有可能参与细胞内的脂肪合成、代谢及转运 . 这篇综述将重点介绍近年来的脂肪滴蛋白质组学研究进展,以及由此推测的脂肪滴的生理功能 . 如果读者希望了解脂肪滴的其他方面内容,请阅读 Denis Murphy 发表于 2001 年的一篇非常完整的综述 .     

Targeting protein-protein interactions for parasite control

Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs) offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank). EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite) and B. malayi (H. sapiens parasite), which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly applicable.