适于小麦叶片蛋白质组分析的样品提取方法研究

以‘铭贤169'小麦苗期叶片为材料,分别采用传统的TCA/丙酮沉淀法、酚提取-甲醇/醋酸铵沉淀法以及改进的TCA/丙酮沉淀-酚/SDS联合抽提法提取叶片总蛋白,进行双向电泳分离和胶体考染,以建立适用于小麦蛋白质组分析的样品制备方法.结果表明:TCA/丙酮沉淀法较酚提取-甲醇/醋酸铵沉淀法获得的蛋白杂质较少,在二维电泳图谱中的蛋白点较酚抽提-甲醇/醋酸铵沉淀法提取的蛋白点清晰且多.相比于以上2种提取蛋白样品方法,改进的TCA/丙酮沉淀-酚/SDS联合抽提法提取的小麦叶片蛋白杂质少、二维电泳图谱上的点明显增多、分辨率较高.所选小麦的代表性蛋白点能获得成功鉴定.该方法可推广应用于水稻叶片蛋白质组分析的样品提取.     

Proteome profile of the developing maize (Zea mays L.) rachis

In this study, we performed the first high‐throughput proteomic analysis of developing rachis (cob) from maize genotype Mp313E. Using two proteomic approaches, 2‐DE and 2‐D LC, we identified 967 proteins. A 2‐D proteome reference map was established. Functional classification of identified proteins revealed that proteins involved in various cellular metabolisms, response to stimulus and transport, were the most abundant.     

A Dual‐Purpose Bromocoumarin Tag Enables Deep Profiling of the Cellular Cysteinome

Chemical proteomics enables comprehensive profiling of small molecules in complex proteomes. A critical component to understand the interactome of a small molecule is the precise location on a protein where the interaction takes place. Several approaches have been developed that take advantage of bio‐orthogonal chemistry and subsequent enrichment steps to isolate peptides modified by small molecules. These methods rely on target identification at the level of mass spectrometry making it difficult to interpret an experiment when modified peptides are not identified. Herein, an approach in which fluorescence‐triggered two‐dimensional chromatography enables the isolation of small molecule‐conjugated peptides prior to mass spectrometry analysis is described. In this study, a bromocoumarin moiety has been utilized that fluoresces and generates a distinct isotopic signature to locate and identify modified peptides. Profiling of a cellular cysteinome with the use of a bromocoumarin tag demonstrates that two‐dimensional fluorescence‐based chromatography separation can enable the identification of proteins containing reactive cysteine residues. Moreover, the method facilitates the interrogation of low abundance proteins with greater depth and sensitivity than a previously reported isotope‐targeted approach. Lastly, this workflow enables the identification of small‐molecule modified peptides from a protein‐of‐interest.     

The Sperm Proteome of the Echiuran Urechis unicinctus (Annelida,Echiura)

Sperm proteins presumably play critical roles in reproduction, but in many non‐model animals their identities are unknown. A total of 147 sperm proteins from the echiuran worm Urechis unicinctus, the first sperm proteome in the phylum Annelida, are reported. The echiuran sperm proteome can be classified into diverse functional groups: energy metabolism (31%), protein synthesis and degradation (18%), spermatogenesis and sperm motility (12%), signal pathway (11%), ion channel and transport proteins (6%), cytoskeleton (4%), immunity and stress responses (3%), and fertilization (1%). These results will facilitate studies of mechanisms of fertilization in echiurans, as well as comparative studies of reproduction and evolution across lophotrochozoans. Data are available via ProteomeXchange with identifier PXD009176.     

Proteome map of the neural complex of the tunicate Ciona intestinalis,the closest living relative to vertebrates

Ciona intestinalis (the common sea squirt) is the closest living chordate relative to vertebrates with cosmopolitan presence worldwide. It has a relatively simple nervous system and development, making it a widely studied alternative model system in neuroscience and developmental biology. The use of Ciona as a model organism has increased significantly after the draft genome was published. In this study, we describe the first proteome map of the neural complex of C. intestinalis. A total of 544 proteins were identified based on 1DE and 2DE FTMS/ITMSMS analyses. Proteins were annotated against the Ciona database and analyzed to predict their molecular functions, roles in biological processes, and position in constructed network pathways. The identified Ciona neural complex proteome was found to map onto vertebrate nervous system pathways, including cytoskeleton remodeling neurofilaments, cell adhesion through the histamine receptor signaling pathway, γ‐aminobutyric acid‐A receptor life cycle neurophysiological process, glycolysis, and amino acid metabolism. The proteome map of the Ciona neural complex is the first step toward a better understanding of several important processes, including the evolution and regeneration capacity of the Ciona nervous system.     

Proteome and phosphoproteome of Africanized and European honeybee venoms

Honey bee venom toxins trigger immunological, physiological, and neurological responses within victims. The high occurrence of bee attacks involving potentially fatal toxic and allergic reactions in humans and the prospect of developing novel pharmaceuticals make honey bee venom an attractive target for proteomic studies. Using label‐free quantification, we compared the proteome and phosphoproteome of the venom of Africanized honeybees with that of two European subspecies, namely Apis mellifera ligustica and A. m. carnica. From the total of 51 proteins, 42 were common to all three subspecies. Remarkably, the toxins melittin and icarapin were phosphorylated. In all venoms, icarapin was phosphorylated at the ²⁰⁵Ser residue, which is located in close proximity to its known antigenic site. Melittin, the major toxin of honeybee venoms, was phosphorylated in all venoms at the ¹⁰Thr and ¹⁸Ser residues. ¹⁸Ser phosphorylated melittin—the major of its two phosphorylated forms—was less toxic compared to the native peptide.     

Mass Spectrometry‐Based Analysis of Time‐Resolved Proteome Quantification

The aspect of time is essential in biological processes and thus it is important to be able to monitor signaling molecules through time. Proteins are key players in cellular signaling and they respond to many stimuli and change their expression in many time‐dependent processes. Mass spectrometry (MS) is an important tool for studying proteins, including their posttranslational modifications and their interaction partners—both in qualitative and quantitative ways. In order to distinguish the different trends over time, proteins, modification sites, and interacting proteins must be compared between different time points, and therefore relative quantification is preferred. In this review, the progress and challenges for MS‐based analysis of time‐resolved proteome dynamics are discussed. Further, aspects on model systems, technologies, sampling frequencies, and presentation of the dynamic data are discussed.     

New protein isoforms identified within Arabidopsis thaliana seed oil bodies combining chymotrypsin/trypsin digestion and peptide fragmentation analysis

Plant seed oil bodies, subcellular lipoprotein inclusions providing storage reserves, are composed of a neutral lipid core surrounded by a phospholipid monolayer with several integrated proteins that play a significant role in stabilization of the particles and probably also in lipid mobilization. Oil bodies' proteins are generally very hydrophobic, due to the long uncharged sequences anchoring them into the lipid core, which makes them extremely difficult to handle and to digest successfully. Although oil bodies have been intensively studied during last decades, not all their proteins have been identified yet. To overcome the problems connected with their identification, a method based on SDS-PAGE, in-gel digestion and LC-MS/MS analysis was used. Digestion was carried out with trypsin and chymotrypsin, single or in combination, which increased significantly the number of identified peptides, namely the hydrophobic ones. Thanks to this methodology it was possible to achieve an extensive coverage of proteins studied, to analyze their N-terminal modifications and moreover, to detect four new oil bodies' protein isoforms, which demonstrates the complexity of oil bodies' protein composition.     

Proteome profile of spinneret from the silkworm,Bombyx mori

The silkworm spinneret is an important tissue for silk fibrillogenesis and spinning. All biochemical processes during silk fibrillogenesis are correlated with silk properties. Understanding the role of spinneret in silk fibrillogenesis may help to reveal the mechanism of silk fibrillogenesis as well as improve silk quality for commercial purposes. Thus, we profiled the proteome of silkworm spinneret. A total of 1572 proteins and 232 differential abundance proteins were identified. Silk fibrillogenesis‐related proteins, such as cuticle proteins, ion‐transporting proteins, muscular proteins, and energy metabolic proteins, were abundant in spinneret. Metabolic pathway and GO enrichment analyses revealed that the identified proteins were involved in energy metabolism, chitin binding, and cuticle construction. Active energy metabolism may provide abundant energy for the muscle contraction as well as ion and water exchange. The chitin binding and cuticle construction process may provide sufficient shear forces for silk formation. Our data suggest that silkworm spinneret provides a suitable physiological and biochemical environment for silk fibrillogenesis. These proteins are potential targets for improving silk quality in the silk industry. Data are available via ProteomeXchange with identifier PXD004455.     

Proteome analysis of Arabidopsis thaliana by two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionisation-time of flight mass spectrometry

In the present study we show results of a large-scale proteome analysis of the recently sequenced plant Arabidopsis thaliana. On the basis of a previously published sequential protein extraction protocol, we prepared protein extracts from eight different A. thaliana tissues (primary leaf, leaf, stem, silique, seedling, seed, root, and inflorescence) and analysed these by two-dimensional gel electrophoresis. A total of 6000 protein spots, from three of these tissues, namely primary leaf, silique and seedling, were excised and the contained proteins were analysed by matrix assisted laser desorption/ionisation time of flight mass spectrometry peptide mass fingerprinting. This resulted in the identification of the proteins contained in 2943 spots, which were found to be products of 663 different genes. In this report we present and discuss the methodological and biological results of our plant proteome analysis.     

高通量植物蛋白质组学研究方法

模式植物拟南芥和水稻的基因组测序,使得大规模、高通量的研究方法在基因组和蛋白质组研究中日趋重要。本文综述双向电泳、质谱、蛋白质微阵列、抗体、酵母双杂交系统以及一些新型高通量方法研究进展及其在植物蛋白质组研究中的应用。     

Elemental formula annotation of polar and lipophilic metabolites using (13) C, (15) N and (34) S isotope labelling, in combination with high-resolution mass spectrometry

The unbiased and comprehensive analysis of metabolites in any organism presents a major challenge if proper peak annotation and unambiguous assignment of the biological origin of the peaks are required. Here we provide a comprehensive multi-isotope labelling-based strategy using fully labelled (13) C, (15) N and (34) S plant tissues, in combination with a fractionated metabolite extraction protocol. The extraction procedure allows for the simultaneous extraction of polar, semi-polar and hydrophobic metabolites, as well as for the extraction of proteins and starch. After labelling and extraction, the metabolites and lipids were analysed using a high-resolution mass spectrometer providing accurate MS and all-ion fragmentation data, providing an unambiguous readout for every detectable isotope-labelled peak. The isotope labelling assisted peak annotation process employed can be applied in either an automated database-dependent or a database-independent analysis of the plant polar metabolome and lipidome. As a proof of concept, the developed methods and technologies were applied and validated using Arabidopsis thaliana leaf and root extracts. Along with a large repository of assigned elemental compositions, which is provided, we show, using selected examples, the accuracy and reliability of the developed workflow.     

Quantitative Global Proteome and Lysine Succinylome Analyses Reveal the Effects of Energy Metabolism in Renal Cell Carcinoma

In light of the increasing incidence of renal cell carcinoma (RCC), its molecular mechanisms have been comprehensively explored in numerous recent studies. However, few studies focus on the influence of multi‐factor interactions during the occurrence and development of RCC. This study aims to investigate the quantitative global proteome and the changes in lysine succinylation in related proteins, seeking to facilitate a better understanding of the molecular mechanisms underlying RCC. LC‐MS/MS combined with bioinformatics analysis are used to quantitatively detect the perspectives at the global protein level. IP and WB analysis were conducted to further verify the alternations of related proteins and lysine succinylation. A total of 3,217 proteins and 1,238 lysine succinylation sites are quantified in RCC tissues, and 668 differentially expressed proteins and 161 differentially expressed lysine succinylation sites are identified. Besides, expressions of PGK1 and PKM2 at protein and lysine, succinylation levels are significantly altered in RCC tissues. Bioinformatics analysis indicates that the glycolysis pathway is a potential mechanism of RCC progression and lysine succinylation may plays a potential role in energy metabolism. These results can provide a new direction for exploring the molecular mechanism of RCC tumorigenesis.     

Proteome reference map of Drosophila melanogaster head

Drosophila melanogaster has been used as a genetic model organism to understand the fundamental molecular mechanisms in human biology including memory formation that has been reported involving protein synthesis and/or post-translational modification. In this study, we employed a proteomic platform based on fluorescent 2DE and MALDI-TOF MS to build a standard D. melanogaster head proteome map for proteome-proteome comparison. In order to facilitate the comparison, an interactive database has been constructed for systematically integrating and analyzing the proteomes from different conditions and further implicated to study human diseases related to D. melanogaster model. In summary, the fundamental head proteomic database and bioinformatic analysis will be useful for further elucidating the biological mechanisms such as memory formation and neurodegenerative diseases.     

Proteomic profiling of Cronobacter turicensis 3032, a food‐borne opportunistic pathogen

Members of the genus Cronobacter are opportunistic pathogens for neonates and are often associated with contaminated milk powder formulas. At present little is known about the virulence mechanisms or the natural reservoir of these organisms. The proteome of Cronobacter turicensis 3032, which has recently caused two deaths, was mapped aiming at a better understanding of physiology and putative pathogenic traits of this clinical isolate. Our analyses of extracellular, surface‐associated and whole‐cell proteins by two complementary proteomics approaches, 1D‐SDS‐PAGE combined with LC‐ESI‐MS/MS and 2D‐LC‐MALDI‐TOF/TOF MS, lead to the identification of 832 proteins corresponding to a remarkable 19% of the theoretically expressed protein complement of C. turicensis. The majority of the identified proteins are involved in central metabolic pathways, translation, protein folding and stability. Several putative virulence factors, whose expressions were confirmed by phenotypic assays, could be identified: a macrophage infectivity potentiator involved in C. turicensis persistence in host cells, a superoxide dismutase protecting the pathogen against reactive oxygen species and an enterobactin‐receptor protein for the uptake of siderophore‐bound iron. Most interestingly, a chitinase and a metalloprotease that might act against insects and fungi but no casein hydrolysing enzymes were found, suggesting that there is an environmental natural habitat of C. turicensis 3032.     

基于数据非依赖采集的蛋白质组质谱数据解析方法研究进展

数据非依赖采集（DIA）是蛋白质组学领域近年来快速发展的质谱采集技术，其通过无偏碎裂隔离窗口内的所有母离子采集二级谱图，理论上可实现蛋白质样品的深度覆盖，同时具有高通量、高重现性和高灵敏度的优点。现有的DIA数据采集方法可以分为全窗口碎裂方法、隔离窗口序列碎裂方法和四维DIA数据采集方法（4D-DIA）3大类。针对DIA数据的不同特点，主要数据解析方法包括谱库搜索方法、蛋白质序列库直接搜索方法、伪二级谱图鉴定方法和从头测序方法4大类。解析得到的肽段鉴定结果需要进行可信度评估，包括使用机器学习方法的重排序和对报告结果集合的假发现率估计两个步骤，实现对数据解析结果的质控。本文对DIA数据的采集方法、数据解析方法及软件和鉴定结果可信度评估方法进行了整理和综述，并展望了未来的发展方向。