Characterization of the mouse brain proteome using global proteomic analysis complemented with cysteinyl-peptide enrichment

We report a global proteomic approach for analyzing brain tissue and for the first time a comprehensive characterization of the whole mouse brain proteome. Preparation of the whole brain sample incorporated a highly efficient cysteinyl-peptide enrichment (CPE) technique to complement a global enzymatic digestion method. Both the global and the cysteinyl-enriched peptide samples were analyzed by SCX fractionation coupled with reversed phase LC-MS/MS analysis. A total of 48,328 different peptides were confidently identified (>98% confidence level), covering 7792 nonredundant proteins ( approximately 34% of the predicted mouse proteome). A total of 1564 and 1859 proteins were identified exclusively from the cysteinyl-peptide and the global peptide samples, respectively, corresponding to 25% and 31% improvements in proteome coverage compared to analysis of only the global peptide or cysteinyl-peptide samples. The identified proteins provide a broad representation of the mouse proteome with little bias evident due to protein pI, molecular weight, and/or cellular localization. Approximately 26% of the identified proteins with gene ontology (GO) annotations were membrane proteins, with 1447 proteins predicted to have transmembrane domains, and many of the membrane proteins were found to be involved in transport and cell signaling. The MS/MS spectrum count information for the identified proteins was used to provide a measure of relative protein abundances. The mouse brain peptide/protein database generated from this study represents the most comprehensive proteome coverage for the mammalian brain to date, and the basis for future quantitative brain proteomic studies using mouse models. The proteomic approach presented here may have broad applications for rapid proteomic analyses of various mouse models of human brain diseases.     

Evaluation on the effect of different in-gel peptide isoelectric focusing parameters in global proteomic profiling

Peptide isoelectric focusing (IEF) is a common technique used in two-dimensional liquid chromatography tandem mass spectrometry (2D–LC–MS/MS) proteomic workflow, in which the tryptic peptide is first pre-fractionated based on pI values before being subjected to reverse phase LC–MS analysis. Although this method has been widely used by many research groups, a systemic study on the optimal conditions and fundamental parameters influencing the experimental outcomes has been lacking, including the effect of peptide extraction methods, the extent of pre-fractionation, and the choice of pH range. In this study, we compared the effect of different parameters on the numbers of peptides and proteins identified using two complex mouse proteomes. The results indicated that extraction of peptides from immobilized pH gradient (IPG) strips by sequential elution of increasingly organic solvents provided the highest number of peptide identification. In addition, we showed that approximately 45 more unique proteins were identified for every additional fraction collected during peptide IEF. Although narrow pH ranges provided higher resolution in peptide separation as expected, different pH ranges yielded similar numbers of peptide and protein identification. Overall, we demonstrated that the extraction solvent influenced the numbers of peptide and protein identification and quantitatively demonstrated the advantage of extensive fractionation and the performance of different pH ranges in practice.     

Comparative proteomic analysis of trophoblast cell models reveals their differential phenotypes,potential uses,and limitations

Trophoblastic cell lines are widely used in in vitro studies of placental function as a surrogate for primary trophoblasts. To date, no reference proteomics dataset exists to directly compare the shared and unique characteristics of these cells. Here, we performed comparative proteomic profiling of the BeWo and HTR8/SVneo cell lines using label‐free quantitative MS. A total of 1557 proteins were identified, which included 338 uniquely attributed to BeWo cells, and a further 304 specifically identified in HTR8/SVneo cells. Raw data are available via ProteomeXchange, identifier PDX005045. Of the 915 proteins expressed by both cell lines, 105 were of higher abundance in BeWo cells, while 199 proteins had a significantly higher expression in HTR8/SVneo cells. Comparative GO of unique and upregulated proteins revealed principal differences in cell junction/adhesion, catenin complex, spindle and microtubule associated complex, as well as cell differentiation. Our data indicate that BeWo cells express an epithelial proteome more characteristic of villous trophoblasts, whereas HTR8/SVneo cells embrace a mesenchymal phenotype, more characteristic of extravillous trophoblasts. This novel comparative proteomic profiling of these trophoblastic cell lines provides a useful platform for future investigations of placental function.     

Multidimensional analysis of the insoluble sub-proteome of Oceanobacillus iheyensis HTE831, an alkaliphilic and halotolerant deep-sea bacterium isolated from the Iheya ridge

We report the first proteomic analysis of the insoluble sub-proteome of the alkaliphilic and halotolerant deep-sea bacterium Oceanobacillus iheyensis HTE831. A multidimensional gel-based and gel-free analysis was utilised and a total of 4352 peptides were initially identified by automated MS/MS identification software. Automated curation of this list using PROVALT reduced our peptide list to 467 uniquely identified peptides that resulted in the positive identification of 153 proteins. These identified proteins were functionally classified and physiochemically characterised. Of 26 proteins identified as hypothetical conserved, we have assigned function to all but four. A total of 41 proteins were predicted to possess signal peptides. In silico investigation of these proteins allowed us to identify three of the five bacterial classes of signal peptide, namely: (i) twin-arginine translocation; (ii) Sec-type and (iii) lipoprotein transport. Our proteomic strategy has also allowed us to identify, at neutral pH, a number of proteins described previously as belonging to two putative transport systems believed to be of importance in the alkaliphilic adaptation of O. iheyensis HTE831.     

Comparison of 2-D LC and 3-D LC with post- and pre-tryptic-digestion SEC fractionation for proteome analysis of normal human liver tissue

The current "shotgun" proteomic analysis, strong cation exchange-RPLC-MS/MS system, is a widely used method for proteome research. Currently, it is not suitable for complicated protein sample analysis, like mammal tissues or cells. To increase the protein identification confidence and number, an additional separation dimension for sample fractionation is necessary to be coupled prior to current multi-dimensional protein identification technology (MudPIT). In this work, SEC was elaborately selected and applied for sample prefractionation in consideration of its non-bias against sample and variety of choice of mobile phases. The analysis of the global lysate of normal human liver tissue sample provided by the China Human Liver Proteome Project, were performed to compare the proteome coverage, sequence coverage (peptide per protein identification) and protein identification efficiency in MudPIT, 3-D LC-MS/MS identification strategy with preproteolytic and postproteolytic fractionation. It was demonstrated that 3-D LC-MS/MS utilizing protein level fractionation was the most effective method. A MASCOT search using the MS/MS results acquired by QSTAR(XL) identified 1622 proteins from 3-D LC-MS/MS identification approaches. A primary analysis on molecular weight, pI and grand average hydrophobicity value distribution of the identified proteins in different approaches was made to further evaluate the 3-D LC-MS/MS analysis strategy.     

High pH reversed‐phase chromatography as a superior fractionation scheme compared to off‐gel isoelectric focusing for complex proteome analysis

MS/MS is the technology of choice for analyzing complex protein mixtures. However, due to the intrinsic complexity and dynamic range present in higher eukaryotic proteomes, prefractionation is an important step to maximize the number of proteins identified. Off‐gel IEF (OG‐IEF) and high pH RP (Hp‐RP) column chromatography have both been successfully utilized as a first‐dimension peptide separation technique in shotgun proteomic experiments. Here, a direct comparison of the two methodologies was performed on ex vivo peripheral blood mononuclear cell lysate. In 12‐fraction replicate analysis, Hp‐RP resulted in more peptides and proteins identified than OG‐IEF fractionation. Distributions of peptide pIs and hydropathy did not reveal any appreciable bias in either technique. Resolution, defined here as the ability to limit a specific peptide to one particular fraction, was significantly better for Hp‐RP. This leads to a more uniform distribution of total and unique peptides for Hp‐RP across all fractions collected. These results suggest that fractionation by Hp‐RP over OG‐IEF is the better choice for typical complex proteome analysis.     

Analysis of the Pasteurella multocida outer membrane sub-proteome and its response to the in vivo environment of the natural host

This study describes the identification of outer membrane proteins (OMPs) of the bacterial pathogen Pasteurella multocida and an analysis of how the expression of these proteins changes during infection of the natural host. We analysed the sarcosine-insoluble membrane fractions, which are highly enriched for OMPs, from bacteria grown under a range of conditions. Initially, the OMP-containing fractions were resolved by 2-DE and the proteins identified by MALDI-TOF MS. In addition, the OMP-containing fractions were separated by 1-D SDS-PAGE and protein identifications were made using nano LC MS/MS. Using these two methods a total of 35 proteins was identified from samples obtained from organisms grown in rich culture medium. Six of the proteins were identified only by 2-DE MALDI-TOF MS, whilst 17 proteins were identified only by 1-D LC MS/MS. We then analysed the OMPs from P. multocida which had been isolated from the bloodstream of infected chickens (a natural host) or grown in iron-depleted medium. Three proteins were found to be significantly up-regulated during growth in vivo and one of these (Pm0803) was also up-regulated during growth in iron-depleted medium. After bioinformatic analysis of the protein matches, it was predicted that over one third of the combined OMPs predicted by the bioinformatics sub-cellular localisation tools PSORTB and Proteome Analyst, had been identified during this study. This is the first comprehensive proteomic analysis of the P. multocida outer membrane and the first proteomic analysis of how a bacterial pathogen modifies its outer membrane proteome during infection.     

Shotgun proteome analysis utilising mixed mode (reversed phase‐anion exchange chromatography) in conjunction with reversed phase liquid chromatography mass spectrometry analysis

The 2‐D peptide separations employing mixed mode reversed phase anion exchange (MM (RP‐AX)) HPLC in the first dimension in conjunction with RP chromatography in the second dimension were developed and utilised for shotgun proteome analysis. Compared with strong cation exchange (SCX) typically employed for shotgun proteomic analysis, peptide separations using MM (RP‐AX) revealed improved separation efficiency and increased peptide distribution across the elution gradient. In addition, improved sample handling, with no significant reduction in the orthogonality of the peptide separations was observed. The shotgun proteomic analysis of a mammalian nuclear cell lysate revealed additional proteome coverage (2818 versus 1125 unique peptides and 602 versus 238 proteins) using the MM (RP‐AX) compared with the traditional SCX hyphenated to RP‐LC‐MS/MS. The MM analysis resulted in approximately 90% of the unique peptides identified present in only one fraction, with a heterogeneous peptide distribution across all fractions. No clustering of the predominant peptide charge states was observed during the gradient elution. The application of MM (RP‐AX) for 2‐D LC proteomic studies was also extended in the analysis of iTRAQ‐labelled HeLa and cyanobacterial proteomes using nano‐flow chromatography interfaced to the MS/MS. We demonstrate MM (RP‐AX) HPLC as an alternative approach for shotgun proteomic studies that offers significant advantages over traditional SCX peptide separations.     

Proteome characterization of the unsequenced psychrophile Pedobacter cryoconitis using 15N metabolic labeling, tandem mass spectrometry, and a new bioinformatic workflow

Organisms without a sequenced genome and lacking a complete protein database encounter an added level of complexity to protein identification and quantitation. De novo sequencing, new bioinformatics tools, and mass spectrometry (MS) techniques allow for advances in this area. Here, the proteomic characterization of an unsequenced psychrophilic bacterium, Pedobacter cryoconitis, is presented employing a novel workflow based on (15) N metabolic labelling, 2DE, MS/MS, and bioinformatics tools. Two bioinformatics pipelines, based on nitrogen constraint (N-constraint), ortholog searching, and de novo peptide sequencing with N-constraint similarity database search, are compared based on proteome coverage and throughput. Results demonstrate the effect of different growth temperatures (1°C, 20°C) and different carbon sources (glucose, maltose) on the proteome. Seventy-six and 69 proteins were identified and validated from the glucose- and maltose-grown bacterium, respectively, from which 21 and 22 were differentially expressed at different growth temperatures. Differentially expressed proteins are involved in stress response and carbohydrate metabolism, with higher expression at 20°C than at 1°C, while antioxidants were upregulated at 1°C. This study provides an alternative workflow to identify, validate, and quantify proteins from unsequenced organisms distantly related to other species in the protein database. Furthermore, it provides further understanding on bacterial adaptation mechanisms to cold environments, and a comparative proteomic analyses with other psychrophilic microorganisms.     

Proteomic Profile of Human Schwann Cells

Schwann cells (SC) are essential for the growth, maintenance, and regeneration of peripheral nerves, but the proteome of normal human SC is poorly defined. Here, a proteomic analysis by LC–MS/MS is performed to define the protein expression profile of primary human SC. A total of 19 557 unique peptides corresponding to 1553 individual proteins are identified. Ingenuity Pathway Analysis (IPA), Gene Ontology (GO), and Database for Annotation, Visualization, and Integrated Discovery (DAVID) are used to assign protein localization and function, and to define enriched pathways. EIF2, mTOR, and integrin signaling are among the most enriched pathways and the most enriched biological function is cell–cell adhesion, which is in agreement with the supportive role of SC in peripheral nerves. In addition, several nociceptors and synaptic proteins are identified and may contribute to the recently discovered role of SC in pain sensation and cancer progression. This proteome analysis of normal human SC constitutes a reference for future molecular explorations of physiological and pathological processes where SC are involved.     

Expanding the mouse embryonic stem cell proteome: Combining three proteomic approaches

The current study used three different proteomic strategies, which differed by their extent of intact protein separation, to examine the proteome of a pluripotent mouse embryonic stem cell line, R1. Proteins from whole‐cell lysates were subjected either to 2‐D‐LC, or 1‐DE, or were unfractionated prior to enzymatic digestion and subsequent analysis by MS. The results yielded 1895 identified non‐redundant proteins and, for 128 of these, the specific isoform could be determined based on detection of an isoform‐specific peptide. When compared with two previously published proteomic studies that used the same cell line, the current study reveals 612 new proteins.     

A peptide resource for the analysis of Staphylococcus aureus in host–pathogen interaction studies

Staphylococcus aureus is an opportunistic human pathogen, which can cause life‐threatening disease. Proteome analyses of the bacterium can provide new insights into its pathophysiology and important facets of metabolic adaptation and, thus, aid the recognition of targets for intervention. However, the value of such proteome studies increases with their comprehensiveness. We present an MS–driven, proteome‐wide characterization of the strain S. aureus HG001. Combining 144 high precision proteomic data sets, we identified 19 109 peptides from 2088 distinct S. aureus HG001 proteins, which account for 72% of the predicted ORFs. Peptides were further characterized concerning pI, GRAVY, and detectability scores in order to understand the low peptide coverage of 8.7% (19 109 out of 220 245 theoretical peptides). The high quality peptide‐centric spectra have been organized into a comprehensive peptide fragmentation library (SpectraST) and used for identification of S. aureus‐typic peptides in highly complex host–pathogen interaction experiments, which significantly improved the number of identified S. aureus proteins compared to a MASCOT search. This effort now allows the elucidation of crucial pathophysiological questions in S. aureus‐specific host–pathogen interaction studies through comprehensive proteome analysis. The S. aureus‐specific spectra resource developed here also represents an important spectral repository for SRM or for data‐independent acquisition MS approaches. All MS data have been deposited in the ProteomeXchange with identifier PXD000702 ( http://proteomecentral.proteomexchange.org/dataset/PXD000702 ).     

Improving basic and membrane protein MS detection of the culture filtrate proteins from Mycobacterium tuberculosis H37Rv by biomimetic affinity prefractionation

The culture filtrate proteins (CFPs) from Mycobacterium tuberculosis have been shown to induce protective immune responses in human and animal models, making them a promising source of candidate targets for tuberculosis drugs, vaccines, and diagnostics. The constituents of the M. tuberculosis CFP proteome are complex and vary with growth conditions. To effectively profile CFPs, gel‐based prefractionation is usually performed before MS analysis. In this study, we describe a novel prefractionation approach by which the proteome is divided into seven partially overlapping fractions by biomimetic affinity chromatography (BiAC) using a six‐column cascade. The LC‐MS/MS analysis of individual fractions identified a total of 541 CFPs, including 61 first‐time identifications. Notably, ～1/3 (20/61) of these novel CFPs are membrane proteins, among which nine proteins have 2–14 transmembrane domains. In addition, ～1/4 (14/61) of the CFPs are basic proteins with pI values greater than 9.0. Our data demonstrate that biomimetic affinity chromatography prefractionation markedly improves protein detection by LC‐MS/MS, and the coverage of basic and hydrophobic proteins in particular is remarkably increased.     

Chemical proteomic study of isoprenoid chain interactome with a synthetic photoaffinity probe

A chemical proteomic approach was developed for profiling the noncovalent interactome of isoprenoid chain in the yeast proteome. A chemical probe that harbors a biotin moiety and a photoreactive benzophenone group linked to the terminal of geranyl group was synthesized. Photoaffinity labeling was performed by incubating the Saccharomyces cerevisiae proteome and the probe under 365 nm UV light. Thirty proteins were identified by immobilized NeutraAvidin enrichment, on-bead digestion, online 2-D nano-LC/MS/MS identification and semi-quantitative proteomic analysis. As noted by Gene Ontology annotation, the identified proteins demonstrate a wide range of catalytic activity in several biological processes, especially in metabolism and biosynthesis. Further data analysis shows that hydrophobic binding of the synthetic probe is potentially the major interaction force leading to covalent labeling. These results argue that intracellular allosteric interactions conferred by the isoprenoid chain of the corresponding chemical structures may be widespread at an interactomic level.     

The Generation of a Comprehensive Spectral Library for the Analysis of the Guinea Pig Proteome by SWATH‐MS

Advances in liquid chromatography‐mass spectrometry have facilitated the incorporation of proteomic studies to many biology experimental workflows. Data‐independent acquisition platforms, such as sequential window acquisition of all theoretical mass spectra (SWATH‐MS), offer several advantages for label‐free quantitative assessment of complex proteomes over data‐dependent acquisition (DDA) approaches. However, SWATH data interpretation requires spectral libraries as a detailed reference resource. The guinea pig (Cavia porcellus) is an excellent experimental model for translation to many aspects of human physiology and disease, yet there is limited experimental information regarding its proteome. To overcome this knowledge gap, a comprehensive spectral library of the guinea pig proteome is generated. Homogenates and tryptic digests are prepared from 16 tissues and subjected to >200 DDA runs. Analysis of >250 000 peptide‐spectrum matches resulted in a library of 73 594 peptides from 7666 proteins. Library validation is provided by i) analyzing externally derived SWATH files ( https://doi.org/10.1016/j.jprot.2018.03.023 ) and comparing peptide intensity quantifications; ii) merging of externally derived data to the base library. This furnishes the research community with a comprehensive proteomic resource that will facilitate future molecular‐phenotypic studies using (re‐engaging) the guinea pig as an experimental model of relevance to human biology. The spectral library and raw data are freely accessible in the MassIVE repository (MSV000083199).     

Detailed proteome analysis of growing cells of the planctomycete Rhodopirellula baltica SH1T

Rhodopirellula baltica SH1(T), which was isolated from the water column of the Kieler Bight, a bay in the southwestern Baltic Sea, is a marine aerobic, heterotrophic representative of the ubiquitous bacterial phylum Planctomycetes. We analyzed the R. baltica proteome by applying different preanalytical protein as well as peptide separation techniques (1-D and 2-DE, HPLC separation) prior to MS. That way, we could identify a total of 1115 nonredundant proteins from the intracellular proteome and from different cell wall protein fractions. With the contribution of 709 novel proteins resulting from this study, the current comprehensive R. baltica proteomic dataset consists of 1267 unique proteins (accounting for 17.3% of the total putative protein-coding ORFs), including 261 proteins with a predicted signal peptide. The identified proteins were functionally categorized using Clusters of Orthologous Groups (COGs), and their potential cellular locations were predicted by bioinformatic tools. A unique protein family that contains several YTV domains and is rich in cysteine and proline was found to be a component of the R. baltica proteinaceous cell wall. Based on this comprehensive proteome analysis a global schema of the major metabolic pathways of growing R. baltica cells was deduced.     

Separation and identification of soybean leaf proteins by two-dimensional gel electrophoresis and mass spectrometry

To establish a proteomic reference map for soybean leaves, we separated and identified leaf proteins using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS). Tryptic digests of 260 spots were subjected to peptide mass fingerprinting (PMF) by matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) MS. Fifty-three of these protein spots were identified by searching NCBInr and SwissProt databases using the Mascot search engine. Sixty-seven spots that were not identified by MALDI-TOF-MS analysis were analyzed with liquid chromatography tandem mass spectrometry (LC-MS/MS), and 66 of these spots were identified by searching against the NCBInr, SwissProt and expressed sequence tag (EST) databases. We have identified a total of 71 unique proteins. The majority of the identified leaf proteins are involved in energy metabolism. The results indicate that 2D-PAGE, combined with MALDI-TOF-MS and LC-MS/MS, is a sensitive and powerful technique for separation and identification of soybean leaf proteins. A summary of the identified proteins and their putative functions is discussed.     

In-Depth Characterization of Sheep (Ovis aries) Milk Whey Proteome and Comparison with Cow (Bos taurus)

An in-depth proteomic study of sheep milk whey is reported and compared to the data available in the literature for the cow whey proteome. A combinatorial peptide ligand library kit (ProteoMiner) was used to normalize protein abundance in the sheep whey proteome followed by an in-gel digest of a 1D-PAGE display and an in-solution digestion followed by OFFGEL isoelectric focusing fractionation. The peptide fractions obtained were then analyzed by LC-MS/MS. This enabled identification of 669 proteins in sheep whey that, to our knowledge, is the largest inventory of sheep whey proteins identified to date. A comprehensive list of cow whey proteins currently available in the literature (783 proteins from unique genes) was assembled and compared to the sheep whey proteome data obtained in this study (606 proteins from unique genes). This comparison revealed that while the 233 proteins shared by the two species were significantly enriched for immune and inflammatory responses in gene ontology analysis, proteins only found in sheep whey in this study were identified that take part in both cellular development and immune responses, whereas proteins only found in cow whey in this study were identified to be associated with metabolism and cellular growth.     

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.