Enhanced recovery of lyophilized peptides in shotgun proteomics by using an LC‐ESI‐MS compatible surfactant

LC‐ESI/MS/MS‐based shotgun proteomics is currently the most commonly used approach for the identification and quantification of proteins in large‐scale studies of biomarker discovery. In the past several years, the shotgun proteomics technologies have been refined toward further enhancement of proteome coverage. In the complex series of protocols involved in shotgun proteomics, however, loss of proteolytic peptides during the lyophilization step prior to the LC/MS/MS injection has been relatively neglected despite the fact that the dissolution of the hydrophobic peptides in lyophilized samples is difficult in 0.05–0.1% TFA or formic acid, causing substantial loss of precious peptide samples. In order to prevent the loss of peptide samples during this step, we devised a new protocol using Invitrosol (IVS), a commercially available surfactant compatible with ESI‐MS; by dissolving the lyophilized peptides in IVS, we show improved recovery of hydrophobic peptides, leading to enhanced coverage of proteome. Thus, the use of IVS in the recovery step of lyophilized peptides will help the shotgun proteomics analysis by expanding the proteome coverage, which would significantly promote the discovery and development of new diagnostic markers and therapeutic targets.     

Comparison of gel‐based phosphoproteomic approaches to analyse scarce oviductal epithelial cell samples

The reversible change of the phosphorylation state of proteins regulates key cellular processes. In the present study, three different gel‐based approaches were compared with regard to their applicability to quantitatively analyse the phosphoproteome of scarce biological material obtained ex vivo. Our results show that the phosphoproteome characterisation of oviductal epithelial cells isolated from the female reproductive tract requires affinity enrichment and pre‐electrophoretic labelling using fluorescence dyes. Using this approach, 30 μg of enriched phosphoproteins proved to be sufficient for the phosphoproteome characterisation. In contrast, sequential fluorescence staining of 2D‐separated total cell lysates as well as sequential staining in conjunction with a pre‐enrichment step led to detection discrepancies and excluded further analysis steps. Information gained from this study provides a successful approach for the phosphoproteome analysis of scarce samples. In addition, the cellular processes taking place in the female reproductive tract can be monitored ex vivo.     

The challenge of the proteome dynamic range and its implications for in‐depth proteomics

The dynamic range of the cellular proteome approaches seven orders of magnitude—from one copy per cell to ten million copies per cell. Since a proteome's abundance distribution represents a nearly symmetric bell‐shape curve on the logarithmic copy number scale, detection of half of the expressed cellular proteome, i.e. approximately 5000 proteins, should be a relatively straightforward task with modern mass spectrometric instrumentation that exhibits four orders of magnitude of the dynamic range, while deeper proteome analysis should be progressively more difficult. Indeed, metaanalysis of 15 recent papers that claim detection of >5000 protein groups reveals that the half‐proteome analyses currently requires ≈5 h of chromatographic separation, while deeper analyses yield on average ≤20 new proteins per hour of chromatographic gradient. Therefore, a typical proteomics experiment consists of a “high‐content” part, with the detection rate of approximately 1000 proteins/h, and a “low‐content” tail with much lower rate of discovery and respectively, lower cost efficiency. This result calls for disruptive innovation in deep proteomics analysis.     

Glucosyltransferase‐dependent and ‐independent effects of TcdB on the proteome of HEp‐2 cells

Toxin B (TcdB) of the nosocomial pathogen C. difficile has been reported to exhibit a glucosyltransferase‐dependent and ‐independent effect on treated HEp‐2 cells at toxin concentration above 0.3 nM. In order to investigate and further characterize both effects epithelial cells were treated with wild type TcdB and glucosyltransferase‐deficient TcdB_NXN and their proteomes were analyzed by LC‐MS. Triplex SILAC labeling was used for quantification. Identification of 5212 and quantification of 4712 protein groups was achieved. Out of these 257 were affected by TcdB treatment, 92 by TcdB_NXN treatment and 49 by both. TcdB mainly led to changes in proteins that are related to “GTPase mediated signaling” and the “cytoskeleton” while “chromatin” and “cell cycle” related proteins were altered by both, TcdB and TcdB_NXN. The obtained dataset of HEp‐2 cell proteome helps us to better understand glucosyltransferase‐dependent and ‐independent mechanisms of TcdB and TcdB_NXN, particularly those involved in pyknotic cell death. All proteomics data have been deposited in the ProteomeXchange with the dataset identifier PXD006658 ( https://proteomecentral.proteomexchange.org/dataset/PXD006658 ).     

Comparative analysis of soybean plasma membrane proteins under osmotic stress using gel‐based and LC MS/MS‐based proteomics approaches

To study the soybean plasma membrane proteome under osmotic stress, two methods were used: a gel‐based and a LC MS/MS‐based proteomics method. Two‐day‐old seedlings were subjected to 10% PEG for 2 days. Plasma membranes were purified from seedlings using a two‐phase partitioning method and their purity was verified by measuring ATPase activity. Using the gel‐based proteomics, four and eight protein spots were identified as up‐ and downregulated, respectively, whereas in the nanoLC MS/MS approach, 11 and 75 proteins were identified as up‐ and downregulated, respectively, under PEG treatment. Out of osmotic stress responsive proteins, most of the transporter proteins and all proteins with high number of transmembrane helices as well as low‐abundance proteins could be identified by the LC MS/MS‐based method. Three homologues of plasma membrane H⁺‐ATPase, which are transporter proteins involved in ion efflux, were upregulated under osmotic stress. Gene expression of this protein was increased after 12 h of stress exposure. Among the identified proteins, seven proteins were mutual in two proteomics techniques, in which calnexin was the highly upregulated protein. Accumulation of calnexin in plasma membrane was confirmed by immunoblot analysis. These results suggest that under hyperosmotic conditions, calnexin accumulates in the plasma membrane and ion efflux accelerates by upregulation of plasma membrane H⁺‐ATPase protein.     

Comparison of detergent‐based sample preparation workflows for LTQ‐Orbitrap analysis of the Escherichia coli proteome

This work presents a comparative evaluation of several detergent‐based sample preparation workflows for the MS‐based analysis of bacterial proteomes, performed using the model organism Escherichia coli. Initially, RapiGest‐ and SDS‐based buffers were compared for their protein extraction efficiency and quality of the MS data generated. As a result, SDS performed best in terms of total protein yields and overall number of MS identifications, mainly due to a higher efficiency in extracting high molecular weight (MW) and membrane proteins, while RapiGest led to an enrichment in periplasmic and fimbrial proteins. Then, SDS extracts underwent five different MS sample preparation workflows, including: detergent removal by spin columns followed by in‐solution digestion (SC), protein precipitation followed by in‐solution digestion in ammonium bicarbonate or urea buffer, filter‐aided sample preparation (FASP), and 1DE separation followed by in‐gel digestion. On the whole, about 1000 proteins were identified upon LC‐MS/MS analysis of all preparations (>1100 with the SC workflow), with FASP producing more identified peptides and a higher mean sequence coverage. Each protocol exhibited specific behaviors in terms of MW, hydrophobicity, and subcellular localization distribution of the identified proteins; a comparative assessment of the different outputs is presented.     

Exome‐based proteogenomics of HEK‐293 human cell line: Coding genomic variants identified at the level of shotgun proteome

Genomic and proteomic data were integrated into the proteogenomic workflow to identify coding genomic variants of Human Embryonic Kidney 293 (HEK‐293) cell line at the proteome level. Shotgun proteome data published by Geiger et al. (2012), Chick et al. (2015), and obtained in this work for HEK‐293 were searched against the customized genomic database generated using exome data published by Lin et al. (2014). Overall, 112 unique variants were identified at the proteome level out of ～1200 coding variants annotated in the exome. Seven identified variants were shared between all the three considered proteomic datasets, and 27 variants were found in any two datasets. Some of the found variants belonged to widely known genomic polymorphisms originated from the germline, while the others were more likely resulting from somatic mutations. At least, eight of the proteins bearing amino acid variants were annotated as cancer‐related ones, including p53 tumor suppressor. In all the considered shotgun datasets, the variant peptides were at the ratio of 1:2.5 less likely being identified than the wild‐type ones compared with the corresponding theoretical peptides. This can be explained by the presence of the so‐called “passenger” mutations in the genes, which were never expressed in HEK‐293 cells. All MS data have been deposited in the ProteomeXchange with the dataset identifier PXD002613 ( http://proteomecentral.proteomexchange.org/dataset/PXD002613 ).     

Information-dependent LC-MS/MS acquisition with exclusion lists potentially generated on-the-fly: case study using a whole cell digest of Clostridium thermocellum

We have developed a real-time graphic-processor-unit-based search engine capable of high-quality peptide identifications in <500 μs per spectrum. The steps of peptide/protein identification, in-silico prediction of all possible tryptic peptides from these proteins, and the prediction of their expected retention times and m/z values take less than 5 s per cycle over ～3000 MS/MS spectra. This lays the foundation for information-dependent acquisition with exclusion lists generated on-the-fly, as the instrument continues to acquire data. While a complete evaluation of the dynamic exclusion system requires the participation from instrument vendors, we conducted a series of model experiments using a whole cell tryptic digestion of the bacterium Clostridium thermocellum. We ran a series of five iterative LC-MS/MS runs, adding a new exclusion list at each of four chromatographic "tripping points" - the elution times of the four standard peptides spiked into the sample. Retention times of these standard peptides were also used for real-time "chromatographic calibration." The dynamic exclusion approach gave a ≈ 5% increase in confident protein identification (for typical 2 h LC-MS/MS run), and reduced the average number of identified peptides per protein from 4.7 to 2.9. Its application to a two-times shorter gradient gave a ≈ 17% increase in proteins identified. Further improvements are possible for instruments with better mass accuracy, by employing a more accurate retention prediction algorithm and by developing better understanding of the possible chemical modifications and fragmentations produced during electrospray ionization.     

Proteomic profiles of human lung adeno and squamous cell carcinoma using super‐SILAC and label‐free quantification approaches

Nonsmall cell lung cancer (NSCLC) accounts for 85% of lung cancers, and is subdivided into two major histological subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC). There is an unmet need to further subdivide NSCLC according to distinctive molecular features that may be associated with responsiveness to therapies. Four primary tumor‐derived xenograft proteomes (two‐each ADC and SCC) were quantitatively compared by using a super‐SILAC labeling approach together with ultrahigh‐resolution MS. Proteins highly differentially expressed in the two subtypes were identified, including 30 that were validated in an independent cohort of 12 NSCLC primary tumor‐derived xenograft tumors whose proteomes were quantified by an alternative, label‐free shotgun MS methodology. The 30‐protein signature contains metabolism enzymes including phosphoglycerate dehydrogenase, which is more highly expressed in SCC, as well as a comprehensive set of cytokeratins and other components of the epithelial barrier, which is therefore distinctly different between ADC and SCC. These results demonstrate the utility of the super‐SILAC method for the characterization of primary tissues, and compatibility with datasets derived from different MS‐based platforms. The validation of proteome signatures of NSCLC subtypes supports the further development and application of MS‐based quantitative proteomics as a basis for precision classifications and treatments of tumors. All MS data have been deposited in the ProteomeXchange with identifier PXD000438 ( http://proteomecentral.proteomexchange.org/dataset/PXD000438 ).     

A proteome map of the pituitary melanotrope cell activated by black‐background adaptation of Xenopus laevis

Upon transfer of Xenopus laevis from a white to a black background, the melanotrope cells in the pituitary pars intermedia secrete α‐melanocyte‐stimulating hormone, which stimulates dispersion of melanin pigment in skin melanophores. This adaptive behavior is under the control of neurotransmitters and neuropeptides of hypothalamic origin. The α‐melanocyte‐stimulating hormone‐producing cells and their hypothalamic control system provide an interesting model to study proteins required for biosynthetic and secretory processes involved in peptide hormone production and for brain–pituitary signaling. We present a 2‐D PAGE‐based proteome map of melanotrope cells from black‐adapted animals, identifying 204 different proteins by MS analysis.     

PepDistiller: A quality control tool to improve the sensitivity and accuracy of peptide identifications in shotgun proteomics

In this study, we presented a quality control tool named PepDistiller to facilitate the validation of MASCOT search results. By including the number of tryptic termini, and integrating a refined false discovery rate (FDR) calculation method, we demonstrated the improved sensitivity of peptide identifications obtained from semitryptic search results. Based on the analysis of a complex data set, approximately 7% more peptide identifications were obtained using PepDistiller than using MASCOT Percolator. Moreover, the refined method generated lower FDR estimations than the percentage of incorrect target (PIT) fixed method applied in Percolator. Using a standard data set, we further demonstrated the increased accuracy of the refined FDR estimations relative to the PIT-fixed FDR estimations. PepDistiller is fast and convenient to use, and is freely available for academic access. The software can be downloaded from http://www.bprc.ac.cn/pepdistiller.     

Generation of accurate peptide retention data for targeted and data independent quantitative LC‐MS analysis: Chromatographic lessons in proteomics

The emergence of data‐independent quantitative LC‐MS/MS analysis protocols further highlights the importance of high‐quality reproducible chromatographic procedures. Knowing, controlling and being able to predict the effect of multiple factors that alter peptide RP‐HPLC separation selectivity is critical for successful data collection for the construction of ion libraries. Proteomic researchers have often regarded RP‐HPLC as a “black box”, while vast amount of research on peptide separation is readily available. In addition to obvious parameters, such as the type of ion‐pairing modifier, stationary phase and column temperature, we describe the “mysterious” effects of gradient slope, column size and flow rate on peptide separation selectivity. Retention time variations due to these parameters are governed by the linear solvent strength (LSS) theory on a peptide level by the value of its slope S in the basic LSS equation—a parameter that can be accurately predicted. Thus, the application of shallower gradients, higher flow rates, or smaller columns will each increases the relative retention of peptides with higher S‐values (long species with multiple positively charged groups). Simultaneous changes to these parameters that each drive shifts in separation selectivity in the same direction should be avoided. The unification of terminology represents another pressing issue in this field of applied proteomics that should be addressed to facilitate further progress.     

Mapping discontinuous protein‐binding sites via structure‐based peptide libraries: combining in silico and in vitro approaches

To perform their various functions, protein surfaces often have to interact with each other in a specific way. Usually, only parts of a protein are accessible and can act as binding sites. Because proteins consist of polypeptide chains that fold into complex three‐dimensional shapes, binding sites can be divided into two different types: linear sites that follow the primary amino acid sequence and discontinuous binding sites, which are made up of short peptide fragments that are adjacent in spatial proximity. Such discontinuous binding sites dominate protein–protein interactions, but are difficult to identify. To meet this challenge, we combined a computational, structure‐based approach and an experimental, high‐throughput method. SUPERFICIAL is a program that uses protein structures as input and generates peptide libraries to represent the protein's surface. A large number of the predicted peptides can be simultaneously synthesised applying the SPOT technology. The results of a binding assay subsequently help to elucidate protein–protein interactions; the approach is applicable to any kind of protein. The crystal structure of the complex of hen egg lysozyme with the well‐characterised murine IgG1 antibody HyHEL‐5 is available, and the complex is known to have a discontinuous binding site. Using SUPERFICIAL, the entire surface of lysozyme was translated into a peptide library that was synthesised on a cellulose membrane using the SPOT technology and tested against the HyHEL‐5 antibody. In this way, it was possible to identify two peptides (longest common sequence and peptide 19) that represented the discontinuous epitope of lysozyme. Copyright © 2012 John Wiley & Sons, Ltd.     

Extending the coverage of spectral libraries: A neighbor‐based approach to predicting intensities of peptide fragmentation spectra

Searching spectral libraries in MS/MS is an important new approach to improving the quality of peptide and protein identification. The idea relies on the observation that ion intensities in an MS/MS spectrum of a given peptide are generally reproducible across experiments, and thus, matching between spectra from an experiment and the spectra of previously identified peptides stored in a spectral library can lead to better peptide identification compared to the traditional database search. However, the use of libraries is greatly limited by their coverage of peptide sequences: even for well‐studied organisms a large fraction of peptides have not been previously identified. To address this issue, we propose to expand spectral libraries by predicting the MS/MS spectra of peptides based on the spectra of peptides with similar sequences. We first demonstrate that the intensity patterns of dominant fragment ions between similar peptides tend to be similar. In accordance with this observation, we develop a neighbor‐based approach that first selects peptides that are likely to have spectra similar to the target peptide and then combines their spectra using a weighted K‐nearest neighbor method to accurately predict fragment ion intensities corresponding to the target peptide. This approach has the potential to predict spectra for every peptide in the proteome. When rigorous quality criteria are applied, we estimate that the method increases the coverage of spectral libraries available from the National Institute of Standards and Technology by 20–60%, although the values vary with peptide length and charge state. We find that the overall best search performance is achieved when spectral libraries are supplemented by the high quality predicted spectra.     

Proteomic,functional and motif‐based analysis of C‐terminal Src kinase‐interacting proteins

C‐terminal Src kinase (Csk) that functions as an essential negative regulator of Src family tyrosine kinases (SFKs) interacts with tyrosine‐phosphorylated molecules through its Src homology 2 (SH2) domain, allowing it targeting to the sites of SFKs and concomitantly enhancing its kinase activity. Identification of additional Csk‐interacting proteins is expected to reveal potential signaling targets and previously undescribed functions of Csk. In this study, using a direct proteomic approach, we identified 151 novel potential Csk‐binding partners, which are associated with a wide range of biological functions. Bioinformatics analysis showed that the majority of identified proteins contain one or several Csk‐SH2 domain‐binding motifs, indicating a potentially direct interaction with Csk. The interactions of Csk with four proteins (partitioning defective 3 (Par3), DDR1, SYK and protein kinase C iota) were confirmed using biochemical approaches and phosphotyrosine 1127 of Par3 C‐terminus was proved to directly bind to Csk‐SH2 domain, which was consistent with predictions from in silico analysis. Finally, immunofluorescence experiments revealed co‐localization of Csk with Par3 in tight junction (TJ) in a tyrosine phosphorylation‐dependent manner and overexpression of Csk, but not its SH2‐domain mutant lacking binding to phosphotyrosine, promoted the TJ assembly in Madin‐Darby canine kidney cells, implying the involvement of Csk‐SH2 domain in regulating cellular TJs. In conclusion, the newly identified potential interacting partners of Csk provided new insights into its functional diversity in regulation of numerous cellular events, in addition to controlling the SFK activity.     

Evaluation of empirical rule of linearly correlated peptide selection (ERLPS) for proteotypic peptide‐based quantitative proteomics

Precise protein quantification is essential in comparative proteomics. Currently, quantification bias is inevitable when using proteotypic peptide‐based quantitative proteomics strategy for the differences in peptides measurability. To improve quantification accuracy, we proposed an “empirical rule for linearly correlated peptide selection (ERLPS)” in quantitative proteomics in our previous work. However, a systematic evaluation on general application of ERLPS in quantitative proteomics under diverse experimental conditions needs to be conducted. In this study, the practice workflow of ERLPS was explicitly illustrated; different experimental variables, such as, different MS systems, sample complexities, sample preparations, elution gradients, matrix effects, loading amounts, and other factors were comprehensively investigated to evaluate the applicability, reproducibility, and transferability of ERPLS. The results demonstrated that ERLPS was highly reproducible and transferable within appropriate loading amounts and linearly correlated response peptides should be selected for each specific experiment. ERLPS was used to proteome samples from yeast to mouse and human, and in quantitative methods from label‐free to O18/O16‐labeled and SILAC analysis, and enabled accurate measurements for all proteotypic peptide‐based quantitative proteomics over a large dynamic range.     

Screening of Ole e 1 polymorphism among olive cultivars by peptide mapping and N‐glycopeptide analysis

In the present paper, we have used 2‐DE coupled to MS analysis to examine the molecular variability of the Ole e 1 allergen in three olive cultivars (cvs). Our results confirmed that the predicted polymorphism of Ole e 1 at cDNA level is extended to the expressed protein. The profiles of both the Ole e 1 peptides and the N‐glycan variants significantly changed among cvs. We observed that Picual and Arbequina cvs presented the highest and lowest degree of Ole e 1 polymorphism, respectively. Some of these peptides and N‐glycans were distributed in a cv‐specific manner. The putative implications of this molecular polymorphism in the development of the allergy symptoms are discussed.     

Comparative analysis of OFFGel,strong cation exchange with pH gradient,and RP at high pH for first‐dimensional separation of peptides from a membrane‐enriched protein fraction

The analysis and quantitation of membrane proteins have proved challenging for proteomics. Although several approaches have been introduced to complement gel‐based analysis of intact proteins, the literature is rather limited in comparing major emerging approaches. Peptide fractionation using IEF (OFFGel), strong cation exchange HPLC using a pH gradient (SCX‐pG), and RP HPLC at high pH, have been shown to increase peptide and protein identification over classic MudPIT approaches. This article compares these three approaches for first‐dimensional separation of peptides using a detergent phase (Triton X‐114) enriched membrane fraction from mouse cortical brain tissue. Results indicate that RP at high pH (pH 10) was superior for the identification of more peptides and proteins in comparison to the OFFGel or the SCX‐pG approaches. In addition, gene ontology analysis (GOMiner) revealed that RP at high pH (pH 10) successfully identified an increased number of proteins with “membrane” ontology, further confirming its suitability for membrane protein analysis, in comparison to SCX‐pG and OFFGel techniques.