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PubMed2004

Homology-based functional proteomics by mass spectrometry: application to the Xenopus microtubule-associated proteome.

The application of functional proteomics to important model organisms with unsequenced genomes is restricted because of the limited ability to identify proteins by conventional mass spectrometry (MS) methods. Here we applied MS and sequence-similarity database searching strategies to characterize the Xenopus laevis microtubule-associated proteome. We identified over 40 unique, and many novel, microtubule-bound proteins, as well as two macromolecular protein complexes involved in protein translation. This finding was corroborated by electron microscopy showing the presence of ribosomes on spindles assembled from frog egg extracts. Taken together, these results suggest that protein translation occurs on the spindle during meiosis in the Xenopus oocyte. These findings were made possible due to the application of sequence-similarity methods, which extended mass spectrometric protein identification capabilities by 2-fold compared to conventional methods.

Animals↗
PubMed2005

Large-scale evaluation of quantitative reproducibility and proteome coverage using acid cleavable isotope coded affinity tag mass spectrometry for proteomic profiling.

Strategies employing non-gel based methods for quantitative proteomic profiling such as isotope coded affinity tags coupled with mass spectrometry (ICAT-MS) are gaining attention as alternatives to two-dimensional gel electrophoresis (2-DE). We have conducted a large-scale investigation to determine the degree of reproducibility and depth of proteome coverage of a typical ICAT-MS experiment by measuring protein changes in Escherichia coli treated with triclosan, an inhibitor of fatty acid biosynthesis. The entire ICAT-MS experiment was conducted on four independent occasions where more than 24 000 peptides were quantitated using an ion-trap mass spectrometer. Our results demonstrated that quantitatively, the technique provided good reproducibility (median coefficient of variation of ratios was 18.6%), and on average identified more than 450 unique proteins per experiment. However, the method was strongly biased to detect acidic proteins (pI < 7), under-represented small proteins (<10 kDa) and failed to show clear superiority over 2-DE methods in monitoring hydrophobic proteins from cell lysates.

Anti-Infective Agents, Local↗
PubMed2006

Examination of 2-DE in the Human Proteome Organisation Brain Proteome Project pilot studies with the new RAIN gel matching technique.

The Human Proteome Organisation (HUPO) Brain Proteome Project (BPP) pilot studies have generated over 200 2-D gels from eight participating laboratories. This data includes 67 single-channel and 60 DIGE gels comparing 30 whole frozen C57/BL6 female mouse brains, ten each at embryonic day 16, postnatal day 7 (juvenile) and postnatal day 54-56 (adult); and ten single-channel and three DIGE gels comparing human epilepsy surgery of the temporal front lobe with a corresponding post-mortem specimen. The samples were generated centrally and distributed to the participating laboratories, but otherwise no restrictions were placed on sample preparation, running and staining protocols, nor on the 2-D gel analysis packages used. Spots were characterised by MS and the annotated gel images published on a ProteinScape web server. In order to examine the resultant differential expression and protein identifications, we have reprocessed a large subset of the gels using the newly developed RAIN (Robust Automated Image Normalisation) 2-D gel matching algorithm. Traditional approaches use symbolic representation of spots at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in spot modelling and matching. With RAIN, image intensity distributions, rather than selected features, are used, where smooth geometric deformation and expression bias are modelled using multi-resolution image registration and bias-field correction. The method includes a new approach of volume-invariant warping which ensures the volume of protein expression under transformation is preserved. An image-based statistical expression analysis phase is then proposed, where small insignificant expression changes over one gel pair can be revealed when reinforced by the same consistent changes in others. Results of the proposed method as applied to the HUPO BPP data show significant intra-laboratory improvements in matching accuracy over a previous state-of-the-art technique, Multi-resolution Image Registration (MIR), and the commercial Progenesis PG240 package.

Algorithms↗
PubMed2006

Bridging Proteomics and Medical Science - the 5th HUPO Brain Proteome Workshop in Dublin, Ireland.

More than 70 interested colleagues attended the 5th Workshop of the HUPO Brain Proteome Project (HUPO BPP) at the UCD Conway Institute, Dublin, Ireland. An overview of the outcome of the pilot study was presented and the new subprojects "Clinical Neuroproteomics of Human Body Fluids" as well as "Cerebellum 2D-mapping" were announced. In addition the election of the HUPO BPP committees and the future directions of this project were discussed and decided. The meeting was enhanced by several talks highlighting the application of proteomics in biomedical research.

Animals↗
PubMed2006

Characterisation of organellar proteomes: a guide to subcellular proteomic fractionation and analysis.

Subcellular fractionation is being widely used to increase our understanding of the proteome. Fractionation is often coupled with 2-DE, thus allowing the visualisation of proteins and their subsequent identification and characterisation by MS. Whilst this strategy should be effective, to date, there has been little or no consideration given to differences in the mass, pI, hydropathy or abundance of proteins in the organelles and how analytical strategies can be tailored to match the idiosyncrasies of proteins in each particular compartment. To address this, we analysed 3962 Saccharomyces cerevisiae proteins, previously localised to one or more of 22 subcellular compartments. Different compartments showed significantly different distributions of protein pI and hydropathy. Mitochondrial and ER proteins showed the most dramatic differences to other organelles, in their protein pIs and hydropathy, respectively. We show that organelles can be clustered by similarities in these physicochemical protein characteristics. Interestingly, the distribution of protein abundance was also significantly different between many organelles. Our results show that to fully explore subcellular fractions of the proteome, specific analytical strategies should be employed. We outline strategies for all 22 subcellular compartments.

Cell Compartmentation↗
PubMed2005

Dual-purpose sample trap for on-line strong cation-exchange chromatography/reversed-phase liquid chromatography/tandem mass spectrometry for shotgun proteomics. Application to the human Jurkat T-cell proteome.

A dual-purpose sample-trapping column is introduced for the capacity enhancement of proteome analysis in on-line two-dimensional nanoflow liquid chromatography (strong cation-exchange chromatography followed by reversed-phase liquid chromatography) and tandem mass spectrometry. A home-made dual trap is prepared by sequentially packing C18 reversed-phase (RP) particles and SCX resin in a silica capillary tubing (1.5 cm x 200 microm I.D. for SCX, 0.7 cm x 200 microm for RP) ended with a home-made frit and is connected to a nanoflow column having a pulled tip treated with an end frit. Without having a separate fraction collection and concentration process, digested peptide mixtures were loaded directly in the SCX part of the dual trap, and the SCX separation of peptides was performed with a salt step elution initiated by injecting only 8 microL of NH4HCO3 solution from the autosampler to the dual trap. The fractionated peptides at each salt step were directly transferred to the RP trap packed right next to the SCX part for desalting, and a nanoflow LC-MS-MS run was followed. During the sample loading-SCX fractionation-desalting, flow direction was set to bypass the analytical column to prevent contamination. The entire 2D-LC separation and MS-MS analysis were automated. Evaluation of the technique was made with an injection of 15 microg peptide mixtures from human Jurkat T-cell proteome, and the total seven salt step cycles followed by each RPLC run resulted in an identification of 681 proteins.

Cation Exchange Resins↗
PubMed2005

Application of proteomics for comparison of proteome of Neospora caninum and Toxoplasma gondii tachyzoites.

Protein profiles of two isolates of Neospora caninum (KBA-2 and JPA1) and Toxoplasma gondii RH strain were investigated by proteomic approach. Approximately, 78% of protein spots on two-dimensional gel electrophoresis (2-DE) profiles and 80% of antigen spots on 2-DE immunoblotting profiles were exhibited to share the same pI and M(r) between KBA-2 and JPA1 of N. caninum. On the other hand, a total of 30 antigen spots of T. gondii were recognized on 2-DE immunoblotting profile using rabbit antiserum against N. caninum KBA-2. A number of homologue proteins, such as heat shock protein 70, tubulin alpha- and beta-chain, putative protein disulfide isomerase, actin, enolase and 14-3-3 protein homologue are believed as the conserved proteins in both N. caninum and T. gondii. On the contrary, NcSUB1, NcGRA2 and NCDG1 (NcGRA7) might be the species-specific proteins for N. caninum tachyzoites. The present study showed that the high degree of similarity between N. caninum isolates (KBA-2 and JPA1), whereas large differences between N. caninum and T. gondii were noticed by proteome comparisons.

Animals↗
PubMedDate not supplied

Proteomic analysis for the assessment of different lots of fetal bovine serum as a raw material for cell culture. Part IV. Application of proteomics to the manufacture of biological drugs.

Fetal bovine serum (FBS) is the most widely used growth supplement for cell cultures, primarily because of its high levels of growth stimulatory factors and low levels of growth inhibitory factors. Maintaining successful and consistent cell fermentations can be difficult, as FBS is a complex natural product and may vary from lot to lot even from a single manufacturer. The quality and concentration of both bulk and specific proteins can affect cell growth. Quality control tools for FBS are relatively primitive and expensive given the complexity of the sample and the large amounts of FBS used. We undertook this study to examine whether proteomics could be used as a tool to analyze the variability of different fermentation processes. We hypothesized that inconsistent cell growth in fermentations could be due to the quality of FBS and that different lots of FBS had varying concentrations of proteins such as growth stimulatory factors, growth inhibitory factors, and/or other proteins that may correlate with cellular growth rate. To investigate whether this was the case, we grew three batches of adult retinal pigment epithelial cells (ARPE-19) using three different lots of fetal bovine serum (FBS-Ia, FBS-Ib, and FBS-II). We found that the growth rate of the culture was significantly and consistently higher in the FBS-II lot. To determine why the other lots promoted different growth properties, we used proteomic techniques to analyze the protein composition of the three lots. We then performed a time course study to monitor specific changes in individual proteins in the fermentation medium. The amount of several extracellular matrix and structural proteins, which are indicators of cell growth, increased over time. Alternatively, components supplied by the FBS addition, such as nutritional-related and cell-spreading-related proteins, decreased over time.

Amino Acid Sequence↗
PubMed2006

Multivariate approach to comparing whole-cell proteomes of Bacillus cereus indicates a biofilm-specific proteome.

Biofilm bacteria are widely held to exhibit a unique phenotype, typified by their increased resistance to antimicrobial agents. Numerous studies have been devoted to the identification of biofilm-specific genes, but surprisingly few have been reported to date. We compared the whole cell proteomes of 24 h old Bacillus cereus biofilms and the associated suspended population to exponential, transient and stationary phase planktonic cultures using the unbiased approach of principal component analysis, comparing the quantity variations of the 823 detected spots. The analyses support the hypothesis that biofilms of Gram positive bacteria have a unique pattern of gene expression. The data provides proteomic evidence for a new biofilm and surface influenced planktonic population which is distinct to both planktonic and biofilm cells.

Bacillus cereus↗
PubMed2000

The yeast proteome database (YPD) and Caenorhabditis elegans proteome database (WormPD): comprehensive resources for the organization and comparison of model organism protein information.

The Yeast Proteome Database (YPDtrade mark) has been for several years a resource for organized and accessible information about the proteins of Saccharomyces cerevisiae. We have now extended the YPD format to create a database containing complete proteome information about the model organism Caenorhabditis elegans (WormPDtrade mark). YPD and WormPD are designed for use not only by their respective research communities but also by the broader scientific community. In both databases, information gleaned from the literature is presented in a consistent, user-friendly Protein Report format: a single Web page presenting all available knowledge about a particular protein. Each Protein Report begins with a Title Line, a concise description of the function of that protein that is continually updated as curators review new literature. Properties and functions of the protein are presented in tabular form in the upper part of the Report, and free-text annotations organized by topic are presented in the lower part. Each Protein Report ends with a comprehensive reference list whose entries are linked to their MEDLINE s. YPD and WormPD are seamlessly integrated, with extensive links between the species. They are freely accessible to academic users on the WWW at http://www. proteome.com/databases/index.html, and are available by subscription to corporate users.

Animals↗
PubMed2006

Proteomics, part II: the emerging role of proteomics over genomics in spontaneous preterm labor/birth.

UNLABELLED: Conventional wisdom holds that complications of immature organ systems such as respiratory distress syndrome, intraventricular hemorrhage, necrotizing enterocolitis, and bronchopulmonary dysplasia are the primary causes of the high neonatal morbidity and mortality attendant preterm delivery. However, recent evidence suggests that a major cause of prematurity-associated neonatal pathology is the fetal and neonatal response to inflammation/infection. Although functional genomics offered the promise of providing answers to many of these questions, the identification of the genes intrinsic to human parturition proved to be a difficult task. Proteomic profiling of the amniotic fluid (AF) provides a precise means for detection of inflammation by revealing the presence of 4 biomarkers (defensins-2 and -1, calgranulin-C, and calgranulin-A) that are highly predictive of intrauterine inflammation (MR score). The MR score is especially useful as it presents a gradient of disease activity progressing from "absent" to "mild" to "severe" inflammation. Thus, it provides the ability to identify patients who may benefit from interventions in utero in a modern diagnostic-therapeutic framework. TARGET AUDIENCE: Obstetricians & Gynecologists, Family Physicians. LEARNING OBJECTIVES: After completion of this article, the reader should be able to explain that the cause or causes of preterm delivery are still unknown, recall that functional genomics has not given the answer to these causes, and state that proteomic profiling of amniotic fluid, through mass-restricted (MR) scoring, may be predictive of intrauterine inflammation and allow for potential diagnosis and potential therapy.

Animals↗
PubMed2002

[Pharmaco-proteomic analysis: application of proteomic analysis to the discovery and development of new drugs].

Pharmacoproteomics may be defined as proteomics applied to the discovery of new therapeutic targets and to the study of drug effects. Proteomics is a powerful technique for analyzing the protein expression profiles in a biological system and its modifications in response to a stimulus or according to the physiological or pathophysiological states. Thus it is a technique of choice for the discovery of new drug targets. It is also an interesting approach for the study of the mode of action of treatments and preclinical drug development. This pharmacoproteomic approach may be particularly useful for the research of new molecular alterations implicated in type 2 diabetes and/or obesity and for the further characterization of existing or new drugs.

Animals↗
PubMed2005

[Study on differential proteomic expression in human liver cells stimulated by trichloroethylene with proteomics].

OBJECTIVE: To explore the differential proteomic expression in human liver cells L-02 induced by different dosages of trichloroethylene (TCE). METHODS: Human liver cells L-02 were treated with different concentrations of TCE and the solvent control (dimethylsulfoxide). The total cellular proteins were separated using 2DE and visualized with silver staining after TCE treatment. The images were analyzed with Image Master 2D Platinum 5.0 analysis software. The differentially expressed protein spots were identified by matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-TOF-MS). RESULTS: Fifteen protein spots with significant difference were found, and went upward or downward or disappeared after the stimulation of TCE with different dosages, which indicated that TCE induced the change of the proteomic expression in the liver cells. The mass spectrum identification and the IPI human database retrieval were used for identifying 9 proteins related to the L-02 Liver cells induced by TCE. CONCLUSION: The result provides an insight to TCE-related molecular mechanism and which might be useful for further study of the TCE-associated proteins and molecular markers.

Cell Line↗
PubMed1999

A molecular scanner to automate proteomic research and to display proteome images.

Identification and characterization of all proteins expressed by a genome in biological samples represent major challenges in proteomics. Today's commonly used high-throughput approaches combine two-dimensional electrophoresis (2-DE) with peptide mass fingerprinting (PMF) analysis. Although automation is often possible, a number of limitations still adversely affect the rate of protein identification and annotation in 2-DE databases: the sequential excision process of pieces of gel containing protein; the enzymatic digestion step; the interpretation of mass spectra (reliability of identifications); and the manual updating of 2-DE databases. We present a highly automated method that generates a fully annoated 2-DE map. Using a parallel process, all proteins of a 2-DE are first simultaneously digested proteolytically and electro-transferred onto a poly(vinylidene difluoride) membrane. The membrane is then directly scanned by MALDI-TOF MS. After automated protein identification from the obtained peptide mass fingerprints using PeptIdent software (http://www.expasy.ch/tools/peptident.html + ++), a fully annotated 2-D map is created on-line. It is a multidimensional representation of a proteome that contains interpreted PMF data in addition to protein identification results. This "MS-imaging" method represents a major step toward the development of a clinical molecular scanner.

Automation↗
PubMed2002

Strategies for proteomics with incompletely characterized genomes: the proteome of Bos taurus serum.

A reference map for Bos taurus serum was obtained using proteomic tools: 21 proteins, plus several serum albumin fragments, have been identified in 47 spots. One of the major acute-phase reactants, haptoglobin, was also detected in a pathological serum. A number of technical problems had to be solved. (i) Spot resolution in two-dimensional electrophoresis (2-DE) is not easily optimized, as several proteins have similar molecular mass; different polyacrylamide concentration gradients were used for the analysis of various size ranges. (ii) Identification of proteins through mass spectrometry (MS) procedures is also difficult as the genome of Bos taurus is incompletely characterized. The program FASTS proved particularly useful, since it allows simultaneous searching of several unordered sequence fragments, which may be individually too short to provide a statistically valid match using BLAST.

Amine Oxidase (Copper-Containing)↗
PubMed2005

Comparison of alternative analytical techniques for the characterisation of the human serum proteome in HUPO Plasma Proteome Project.

Based on the same HUPO reference specimen (C1-serum) with the six proteins of highest abundance depleted by immunoaffinity chromatography, we have compared five proteomics approaches, which were (1) intact protein fractionation by anion-exchange chromatography followed by 2-DE-MALDI-TOF-MS/MS for protein identification (2-DE strategy); (2) intact protein fractionation by 2-D HPLC followed by tryptic digestion of each fraction and microcapillary RP-HPLC/microESI-MS/MS identification (protein 2-D HPLC fractionation strategy); (3) protein digestion followed by automated online microcapillary 2-D HPLC (strong cation-exchange chromatography (SCX)-RPC) with IT microESI-MS/MS; (online shotgun strategy); (4) same as (3) with the SCX step performed offline (offline shotgun strategy) and (5) same as (4) with the SCX fractions reanalysed by optimised nanoRP-HPLC-nanoESI-MS/MS (offline shotgun-nanospray strategy). All five approaches yielded complementary sets of protein identifications. The total number of unique proteins identified by each of these five approaches was (1) 78, (2) 179, (3) 131, (4) 224 and (5) 330 respectively. In all, 560 unique proteins were identified. One hundred and sixty-five proteins were identified through two or more peptides, which could be considered a high-confidence identification. Only 37 proteins were identified by all five approaches. The 2-DE approach yielded more information on the pI-altered isoforms of some serum proteins and the relative abundance of identified proteins. The protein prefractionation strategy slightly improved the capacity to detect proteins of lower abundance. Optimising the separation at the peptide level and improving the detection sensitivity of ESI-MS/MS were more effective than fractionation of intact proteins in increasing the total number of proteins identified. Overall, electrophoresis and chromatography, coupled respectively with MALDI-TOF/TOF-MS and ESI-MS/MS, identified complementary sets of serum proteins.

Blood Proteins↗
PubMed2006

Biomarker discovery from the plasma proteome using multidimensional fractionation proteomics.

Because biomarkers are typically low in abundance, the crucial step of biomarker discovery is to efficiently separate clinically relevant sets of proteins that might define disease stages and/or predict disease development. It is anticipated that a multi-dimensional fractionation system (MDFS) will provide an efficient means of separating low abundance proteins from plasma proteins, resulting in the extension of the detection limit. However, when using an MDFS to analyze the plasma proteome it is important to consider how sample processing, yield, resolution and throughput potential may influence the detection limit. This review evaluates the recent advances in MDFS research with respect to '4RS criterion' (4R: resolution, reproducibility, recovery, and robustness; 4S: simplicity, speed, selectivity and sensitivity) and discusses perspectives for future plasma-derived biomarker discovery.

Biomarkers↗
PubMed2026

Identification of Immune Response-Related Proteomic Biomarkers in Moyamoya Disease Using Serum Olink Proteomics.

Moyamoya disease, a rare chronic cerebrovascular disorder, requires invasive digital subtraction angiography (DSA) for diagnosis. This study employed high-throughput proteomics to identify plasma biomarkers for Moyamoya disease diagnosis. We conducted immunopanel analysis using the Olink platform to evaluate 92 immune-related proteins in plasma samples from 88 Moyamoya disease patients and 88 healthy controls. Key proteins were identified through differential expression analysis, GO, and KEGG enrichment analysis. A diagnostic model was constructed using LASSO regression, Boruta algorithm, and machine learning models including random forest and XGBoost. Validation of these proteins was performed using GEO external data sets, followed by prediction of potential therapeutic drugs and molecular docking validation through pharmacogenomic databases. A total of 44 differentially expressed proteins were identified through the Olink immunopanel, with 12 downregulated and 32 upregulated. GO and KEGG analyses revealed significant enrichment of these proteins in innate immune responses and signaling pathways such as NF-kB and MAPK. Through LASSO, random forest, and protein under-area analysis, four potential biomarkers for Moyamoya disease (MGMT, SIT1, PRDX1, TRAF2) were identified. A diagnostic model using these proteins showed the highest AUC value with the XGBoost model. Additionally, TRAF2 and PRDX1 exhibited significant expression differences in Moyamoya disease patients within the GEO data set. Our study revealed the immune landscape of Moyamoya disease, identified four biomarkers, and established a variety of diagnostic models.

Humans↗