Proteomics of protein secretion by Bacillus subtilis: separating the "secrets" of the secretome.

Secretory proteins perform a variety of important "remote-control" functions for bacterial survival in the environment. The availability of complete genome sequences has allowed us to make predictions about the composition of bacterial machinery for protein secretion as well as the extracellular complement of bacterial proteomes. Recently, the power of proteomics was successfully employed to evaluate genome-based models of these so-called secretomes. Progress in this field is well illustrated by the proteomic analysis of protein secretion by the gram-positive bacterium Bacillus subtilis, for which approximately 90 extracellular proteins were identified. Analysis of these proteins disclosed various "secrets of the secretome," such as the residence of cytoplasmic and predicted cell envelope proteins in the extracellular proteome. This showed that genome-based predictions reflect only approximately 50% of the actual composition of the extracellular proteome of B. subtilis. Importantly, proteomics allowed the first verification of the impact of individual secretion machinery components on the total flow of proteins from the cytoplasm to the extracellular environment. In conclusion, proteomics has yielded a variety of novel leads for the analysis of protein traffic in B. subtilis and other gram-positive bacteria. Ultimately, such leads will serve to increase our understanding of virulence factor biogenesis in gram-positive pathogens, which is likely to be of high medical relevance.     

From the genome sequence to the protein inventory of Bacillus subtilis

Owing to the low number of proteins necessary to render a bacterial cell viable, bacteria are extremely attractive model systems to understand how the genome sequence is translated into actual life processes. One of the most intensively investigated model organisms is Bacillus subtilis. It has attracted world-wide research interest, addressing cell differentiation and adaptation on a molecular scale as well as biotechnological production processes. Meanwhile, we are looking back on more than 25 years of B. subtilis proteomics. A wide range of methods have been developed during this period for the large-scale qualitative and quantitative proteome analysis. Currently, it is possible to identify and quantify more than 50% of the predicted proteome in different cellular subfractions. In this review, we summarize the development of B. subtilis proteomics during the past 25 years.     

Proteomics of Protein Secretion by Bacillus subtilis: Separating the “Secrets” of the Secretome

Secretory proteins perform a variety of important “remote-control” functions for bacterial survival in the environment. The availability of complete genome sequences has allowed us to make predictions about the composition of bacterial machinery for protein secretion as well as the extracellular complement of bacterial proteomes. Recently, the power of proteomics was successfully employed to evaluate genome-based models of these so-called secretomes. Progress in this field is well illustrated by the proteomic analysis of protein secretion by the gram-positive bacterium Bacillus subtilis, for which ~90 extracellular proteins were identified. Analysis of these proteins disclosed various “secrets of the secretome,” such as the residence of cytoplasmic and predicted cell envelope proteins in the extracellular proteome. This showed that genome-based predictions reflect only ~50% of the actual composition of the extracellular proteome of B. subtilis. Importantly, proteomics allowed the first verification of the impact of individual secretion machinery components on the total flow of proteins from the cytoplasm to the extracellular environment. In conclusion, proteomics has yielded a variety of novel leads for the analysis of protein traffic in B. subtilis and other gram-positive bacteria. Ultimately, such leads will serve to increase our understanding of virulence factor biogenesis in gram-positive pathogens, which is likely to be of high medical relevance.     

A Proteomic View of an Important Human Pathogen – Towards the Quantification of the Entire Staphylococcus aureus Proteome

The genome sequence is the “blue-print of life,” but proteomics provides the link to the actual physiology of living cells. Because of their low complexity bacteria are excellent model systems to identify the entire protein assembly of a living organism. Here we show that the majority of proteins expressed in growing and non-growing cells of the human pathogen Staphylococcus aureus can be identified and even quantified by a metabolic labeling proteomic approach. S. aureus has been selected as model for this proteomic study, because it poses a major risk to our health care system by combining high pathogenicity with an increasing frequency of multiple antibiotic resistance, thus requiring the development of new anti-staphylococcal therapy strategies. Since such strategies will likely have to target extracellular and surface-exposed virulence factors as well as staphylococcal survival and adaptation capabilities, we decided to combine four subproteomic fractions: cytosolic proteins, membrane-bound proteins, cell surface-associated and extracellular proteins, to comprehensively cover the entire proteome of S. aureus. This quantitative proteomics approach integrating data ranging from gene expression to subcellular localization in growing and non-growing cells is a proof of principle for whole-cell physiological proteomics that can now be extended to address physiological questions in infection-relevant settings. Importantly, with more than 1700 identified proteins (and 1450 quantified proteins) corresponding to a coverage of about three-quarters of the expressed proteins, our model study represents the most comprehensive quantification of a bacterial proteome reported to date. It thus paves the way towards a new level in understanding of cell physiology and pathophysiology of S. aureus and related pathogenic bacteria, opening new avenues for infection-related research on this crucial pathogen.     

Quantitative proteomics reveals dynamic changes in the plasma membrane during Arabidopsis immune signaling

The plant plasma membrane is a crucial mediator of the interaction between plants and microbes. Understanding how the plasma membrane proteome responds to diverse immune signaling events will lead to a greater understanding of plant immunity and uncover novel targets for crop improvement. Here we report the results from a large scale quantitative proteomics study of plasma membrane-enriched fractions upon activation of the Arabidopsis thaliana immune receptor RPS2. More than 2300 proteins were identified in total, with 1353 proteins reproducibly identified across multiple replications. Label-free spectral counting was employed to quantify the relative protein abundance between different treatment samples. Over 20% of up-regulated proteins have known roles in plant immune responses. Significantly changing proteins include those involved in calcium and lipid signaling, membrane transport, primary and secondary metabolism, protein phosphorylation, redox homeostasis, and vesicle trafficking. A subset of differentially regulated proteins was independently validated during bacterial infection. This study presents the largest quantitative proteomics data set of plant immunity to date and provides a framework for understanding global plasma membrane proteome dynamics during plant immune responses.     

Towards the entire proteome of the model bacterium Bacillus subtilis by gel-based and gel-free approaches

With the emergence of mass spectrometry in protein science and the availability of complete genome sequences, proteomics has gone through a rapid development. The soil bacterium Bacillus subtilis, as one of the first DNA sequenced species, represents a model for Gram-positive bacteria and its proteome was extensively studied throughout the years. Having the final goal to elucidate how life really functions, one basic requirement is to know the entirety of cellular proteins. This review presents how far we have got in unraveling the proteome of B. subtilis. The application of gel-based and gel-free technologies, the analyses of different subcellular proteome fractions, and the pursuance of various physiological strategies resulted in a coverage of more than one-third of B. subtilis theoretical proteome.     

Towards a comprehensive understanding of Bacillus subtilis cell physiology by physiological proteomics

Using Bacillus subtilis as a model system for functional genomics, this review will provide insights how proteomics can be used to bring the virtual life of genes to the real life of proteins. Physiological proteomics will generate a new and broad understanding of cellular physiology because the majority of proteins synthesized in the cell can be visualized. From a physiological point of view two major proteome fractions can be distinguished: proteomes of growing cells and proteomes of nongrowing cells. In the main analytical window almost 50% of the vegetative proteome expressed in growing cells of B. subtilis were identified. This proteomic view of growing cells can be employed for analyzing the regulation of entire metabolic pathways and thus opens the chance for a comprehensive understanding of metabolism and growth processes of bacteria. Proteomics, on the other hand, is also a useful tool for analyzing the adaptational network of nongrowing cells that consists of several partially overlapping regulation groups induced by stress/starvation stimuli. Furthermore, proteomic signatures for environmental stimuli can not only be applied to predict the physiological state of cells, but also offer various industrial applications from fermentation monitoring up to the analysis of the mode of action of drugs. Even if DNA array technologies currently provide a better overview of the gene expression profile than proteome approaches, the latter address biological problems in which they can not be replaced by mRNA profiling procedures. This proteomics of the second generation is a powerful tool for analyzing global control of protein stability, the protein interaction network, protein secretion or post-translational modifications of proteins on the way towards the elucidation of the mystery of life.     

Two-dimensional gel electrophoresis in bacterial proteomics

Two-dimensional gel electrophoresis (2-DE) is a gel-based technique widely used for analyzing the protein composition of biological samples. It is capable of resolving complex mixtures containing more than a thousand protein components into individual protein spots through the coupling of two orthogonal biophysical separation techniques: isoelectric focusing (first dimension) and polyacrylamide gel electrophoresis (second dimension). 2-DE is ideally suited for analyzing the entire expressed protein complement of a bacterial cell: its proteome. Its relative simplicity and good reproducibility have led to 2-DE being widely used for exploring proteomics within a wide range of environmental and medically-relevant bacteria. Here we give a broad overview of the basic principles and historical development of gel-based proteomics, and how this powerful approach can be applied for studying bacterial biology and physiology. We highlight specific 2-DE applications that can be used to analyze when, where and how much proteins are expressed. The links between proteomics, genomics and mass spectrometry are discussed. We explore how proteomics involving tandem mass spectrometry can be used to analyze (post-translational) protein modifications or to identify proteins of unknown origin by de novo peptide sequencing. The use of proteome fractionation techniques and non-gel-based proteomic approaches are also discussed. We highlight how the analysis of proteins secreted by bacterial cells (secretomes or exoproteomes) can be used to study infection processes or the immune response. This review is aimed at non-specialists who wish to gain a concise, comprehensive and contemporary overview of the nature and applications of bacterial proteomics.     

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.     

The mechanism of Pseudomonas aeruginosa outer membrane vesicle biogenesis determines their protein composition

Gram-negative bacteria produce outer membrane vesicles (OMVs) and contain bacterial cargo including nucleic acids and proteins. The proteome of OMVs can be altered by various factors including bacterial growth stage, growth conditions, and environmental factors. However, it is currently unknown if the mechanism of OMV biogenesis can determine their proteome. In this study, we examined whether the mechanisms of OMV biogenesis influenced the production and protein composition of Pseudomonas aeruginosa OMVs. OMVs were isolated from three P. aeruginosa strains that produced OMVs either by budding alone, by explosive cell lysis, or by both budding and explosive cell lysis. We identified that the mechanism of OMV biogenesis dictated OMV quantity. Furthermore, a global proteomic analysis comparing the proteome of OMVs to their parent bacteria showed significant differences in the identification of proteins in bacteria and OMVs. Finally, we determined that the mechanism of OMV biogenesis influenced the protein composition of OMVs, as OMVs released by distinct mechanisms of biogenesis differed significantly from one another in their proteome and functional enrichment analysis. Overall, our findings reveal that the mechanism of OMV biogenesis is a main factor that determines the OMV proteome which may affect their subsequent biological functions.     

Investigating pathogen biology at the level of the proteome

Bacterial infections are a major cause of morbidity and mortality throughout the world. By extending our understanding of the process of bacterial pathogenesis at the molecular level new strategies for their treatment and prevention can be developed. Proteomic technologies, along with other methods for global gene expression analysis, play an important role in understanding the mechanism(s) of bacterial pathogenesis. This review highlights the use of proteomics to identify protein biomarkers for virulent bacterial isolates and how these biomarkers can be correlated with the outcome of bacterial infection. Biomarker identification typically looks at the proteomes of bacteria grown under laboratory conditions. It is, however, the characterisation of the bacterial proteome during in vivo infection of its host that will eventually provide the most significant insights into bacterial pathogenesis. Although this area of research has significant technical challenges, a number of complementary proteome analytical approaches are being developed to identify and characterise the bacterial genes specifically expressed in vivo. Ultimately, the development of newly targeted therapies and vaccines using specific protein targets identified through proteomic analyses will be one of the major practical benefits arising from the proteomic analysis of bacterial pathogens.     

Unraveling persistent host cell infection with Coxiella burnetii by quantitative proteomics

The interaction between the immune system and invading bacteria is sufficient to eradicate microorganisms for the majority of bacterial infections, but suppression of the microbicidal response leads to reactivation or chronic evolution of infections and to bacterial persistence. To identify the cellular pathways affected by bacterial persistence, we applied the MS-driven combined fractional diagonal chromatography (COFRADIC) proteomics technique for a comparative study of protein expression in the C. burnetii strains Nine Mile (NM) and its respective strain (NMper) isolated from 18 months persistently infected cell cultures. In total, three different proteome comparisons were performed with the total bacterial proteome, potentially secreted bacterial proteins, and the eukaryotic infected proteome being assessed. Our results revealed that among the 547 identified bacterial proteins, 53 had significantly altered levels of expression and indicated potential metabolic differences between the two strains. Regarding differences in the secreted proteins between both strains and different modulation of the host cell, machineries reflect at least large rearrangements of both bacterial and eukaryotic proteomes during the persistent model of infection when compared to the acute one, which emphasizes that C. burnetii orchestrates a vast number of different bacterial and eukaryotic host cell processes to persist within its host.     

The utility of proteases in proteomics,from sequence profiling to structure and function analysis

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.     

SNAP-tag based proteomics approach for the study of the retrograde route

Proteomics is a powerful technique for protein identification at large scales. A number of proteomics approaches have been developed to study the steady state composition of intracellular compartments. Here, we report a novel vectorial proteomics strategy to identify plasma membrane proteins that undergo retrograde transport to the trans-Golgi network (TGN). This strategy is based on the covalent modification of the plasma membrane proteome with a membrane impermeable benzylguanine derivative. Benzylguanine-tagged plasma membrane proteins that are subsequently targeted to the retrograde route are covalently captured by a TGN-localized SNAP-tagged fusion protein, which allows for their identification. The approach was validated step-by-step using a well explored retrograde cargo protein, the B-subunit of Shiga toxin. It was then extended to the proteomics format. Among other hits we found one of the historically first identified cargo proteins that undergo retrograde transport, which further validated our approach. Most of the other hits were kinases, receptors or transporters. In conclusion, we have pioneered a vectorial proteomics approach that complements traditional methods for the study of retrograde protein trafficking. This approach is of generic nature and could in principle be extended to other endocytic pathways.     

双向电泳结合质谱分析长双歧杆菌XY01分泌蛋白质图谱

菌体的分泌蛋白质在宿主和菌体的相互作用之间起着重要的作用. 本研究采用双向凝胶电泳的方法建立了长双歧杆菌XY01分泌蛋白质图谱,通过MALDI-TOF/TOF质 谱鉴定和数据库搜索,对鉴定到的分泌蛋白进行了分析. 共检测到21个蛋白质点, 成功鉴定18个蛋白质点,分别代表14个不同的蛋白质,等电点分布在4.5～7.0之间 ,分子质量分布在20 ～65 kD之间;通过COGs分类和功能分析,信号肽和细胞定位及KEGG代谢通路分析. 结果表明,这些蛋白质对菌体细胞壁/膜的形成、生物信号传导和物质代谢等起着重要作用. 研究结果为长双歧杆菌蛋白质组学和基因组学的研究提供了参考.     

Mouse models for neurodegenerative diseases and a theory of proteomics

Proteome analysis is usually performed by separating complex cellular protein extracts by two‐dimensional‐electrophoresis followed by protein identification using mass spectrometry. In this way proteins are compared from normal and diseased tissue in order to detect disease related protein changes. In a strict sense, however, this procedure cannot be called proteome analysis: the tools of proteomics are used just to detect some interesting proteins which are then investigated by protein chemistry as usual. Real proteome research would be studying the cellular proteome as a whole, its composition, organization and its kind of action. At present however, we have no idea how a proteome works as a whole; we have not even a theory about that. If we would know how the proteome of a cell type is arranged, we probably would alter our strategy to detect and analyze disease‐related proteins. I will present a theory of proteomics and show some results from our laboratory which support this theory. The results come from investigations of the mouse brain proteome and include mouse models for neurodegenerative diseases.     

Gene therapy approaches for Parkinson's disease

Proteome analysis is usually performed by separating complex cellular protein extracts by two-dimensional-electrophoresis followed by protein identification using mass spectrometry. In this way proteins are compared from normal and diseased tissue in order to detect disease related protein changes. In a strict sense, however, this procedure cannot be called proteome analysis: the tools of proteomics are used just to detect some interesting proteins which are then investigated by protein chemistry as usual. Real proteome research would be studying the cellular proteome as a whole, its composition, organization and its kind of action. At present however, we have no idea how a proteome works as a whole; we have not even a theory about that. If we would know how the proteome of a cell type is arranged, we probably would alter our strategy to detect and analyze disease-related proteins. I will present a theory of proteomics and show some results from our laboratory which support this theory. The results come from investigations of the mouse brain proteome and include mouse models for neurodegenerative diseases.     

Comparative proteomics to evaluate multi drug resistance in Escherichia coli

Drug resistance in food-borne bacterial pathogens is an almost inevitable consequence of the use of antimicrobial drugs, used either therapeutically or to avoid infections in food-producing animals. In the past decades, the spread and inappropriate use of antibiotics have caused a considerable increase of antibiotics to which bacteria have developed resistance and, moreover, bacteria are becoming resistant to more than one antibiotic simultaneously. Understanding mechanisms at the molecular level is extremely important to control multi-resistant strains and to develop new therapeutic strategies. In the present study, comparative proteomics was applied to characterize membrane and cytosolic proteome in order to investigate the regulation of protein expression in multi-resistance E. coli isolated from young never vaccinated water buffalo. Results highlighted differentially expressed proteins under multi drug resistance conditions giving new insights about mechanisms involved in resistance, as quorum sensing mechanisms, and suggesting possible novel bacterial targets to develop alternative antibiotic drugs.     

Immunoisolation and subfractionation of synaptic vesicle proteins

Within recent years, the advances in proteomics techniques have resulted in considerable novel insights into the protein expression patterns of specific tissues, cells, and organelles. The information acquired from large-scale proteomics approaches indicated, however, that the proteomic analysis of whole cells or tissues is often not suited to fully unravel the proteomes of individual organellar constituents or to identify proteins that are present at low copy numbers. In addition, the identification of hydrophobic proteins is still a challenge. Therefore, the development of techniques applicable for the enrichment of low-abundance membrane proteins is essential for a comprehensive proteomic analysis. In addition to the enrichment of particular subcellular structures by subcellular fractionation, the spectrum of techniques applicable for proteomics research can be extended toward the separation of integral and peripheral membrane proteins using organic solvents, detergents, and detergent-based aqueous two-phase systems with water-soluble polymers. Here, we discuss the efficacy of a number of experimental protocols. We demonstrate that the appropriate selection of physicochemical conditions results in the isolation of synaptic vesicles of high purity whose proteome can be subfractionated into integral membrane proteins and soluble proteins by several phase separation techniques.     

Liquid chromatography MALDI MS/MS for membrane proteome analysis

Membrane proteins play critical roles in many biological functions and are often the molecular targets for drug discovery. However, their analysis presents a special challenge largely due to their highly hydrophobic nature. We present a surfactant-aided shotgun proteomics approach for membrane proteome analysis. In this approach, membrane proteins were solubilized and digested in the presence of SDS followed by newly developed auto-offline liquid chromatography/matrix-assisted laser desorption ionization (LC/MALDI) tandem MS analysis. Because of high tolerance of MALDI to SDS, one-dimensional (1D) LC separation can be combined with MALDI for direct analysis of protein digests containing SDS, without the need for extensive sample cleanup. In addition, the heated droplet interface used in LC/MALDI can work with high flow LC separations, allowing a relatively large amount of protein digest to be used for 1D LC/MALDI which facilitates the detection of low abundance proteins. The proteome identification results obtained by LC/MALDI are compared to the gel electrophoresis/MS method as well as the shotgun proteomics method using 2D LC/electrospray ionization MS. It is demonstrated that, while LC/MALDI provides more extensive proteome coverage compared to the other two methods, these three methods are complementary to each other and a combination of these methods should provide a more comprehensive membrane proteome analysis.