Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry II.Limitations of complex mixture analyses

Davis, Michael T.; Spahr, Chris; McGinley, Michael D.; Robinson, John H.; Bures, Edward J.; Beierle, Jill; Mort, Jessica; Yao, Wen; Luethy, Roland; Patterson, Scott D.

doi:10.1002/1615-9861(200101)1:1<108::aid-prot108>3.0.co;2-5

Cited by 126 publications

(72 citation statements)

References 7 publications

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“…Several research teams have worked on profiling the healthy human urine proteome using electrophoresis and/or liquid chromatography followed by mass spectrometry identification (1)(2)(3)(4)(5).…”

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confidence: 99%

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Concanavalin A-captured Glycoproteins in Healthy Human Urine

Wang

Sun

et al. 2006

Molecular & Cellular Proteomics

115

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Both the urinary proteome and its glycoproteome can reflect human health status, and more directly, functions of kidney and urinary tracts. Because the high abundance protein albumin is not N-glycosylated, the urine N-glycoprotein enrichment procedure could deplete it, and urine proteome could thus provide a more detailed protein profile in addition to glycosylation information especially when albuminuria occurs in some kidney diseases. In terms of describing the details of urinary proteins, the urine glycoproteome is even a better choice than the proteome itself. Pooled urine samples from healthy volunteers were collected and acetone-precipitated for proteins. N-Linked glycoproteins enriched with concanavalin A affinity purification were separated and analyzed by SDS-PAGE-reverse phase LC/MS/MS or two-dimensional LC/MS/MS. A total of 225 urinary proteins were identified based on two-hit criteria with reliability over 97% for each peptide. Among these proteins, 94 were identified in previous urine proteome works, 150 were annotated as glycoproteins in Swiss-Prot, and 43 were predicted as glycoproteins by NetNGlyc 1.0. A number of known biomarkers and disease-related glycoproteins were identified. Because changes in protein quantity or the glycosylation status can lead to changes in the concanavalin A-captured glycoprotein profile, specific urine glycoproteome patterns might be observed for specific pathological conditions as multiplex urinary biomarkers. Knowledge of the urine glycoproteome is important in understanding kidney and body function. Molecular & Cellular Proteomics 5:560 -562, 2006.The urinary proteome has received more and more attention in the proteomic field for its simplicity compared with serum as well as its potential in biomarker discovery. Several research teams have worked on profiling the healthy human urine proteome using electrophoresis and/or liquid chromatography followed by mass spectrometry identification (1-5).The fact that some proteins were observed at higher molecular weight than their theoretical ones on SDS-PAGE (5) confirmed that the post-translational modifications including glycosylation exist extensively in urinary proteins. Glycosylation, a common and important protein post-translational modification, is involved in many biological processes such as cell adhesion, signal transduction, immune response, and inflammatory reaction (6). More than half of all proteins are thought to be glycoproteins, and they will undergo changes in quality and quantity along with the changes in different physiological and pathological states. Both the urine proteome and its glycoproteome can reflect human health status, especially functions of kidney and urinary tracts. In some kidney diseases, albuminuria usually occurs. Because high abundance albumin is not N-glycosylated, urine N-glycoprotein enrichment procedure could deplete it, and the urine glycoproteome could provide a more detailed protein profile in addition to the glycosylation information. In terms of describing details of urinary pr...

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confidence: 99%

“…Even for the other 83 proteins identified by single peptide with multiple hits, the reliability was still more than 97%. 94 proteins were identified in previous urine proteome studies (1)(2)(3)(4)(5). 43 proteins were also identified in serum Nglycoproteome (11)(12)(13).…”

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confidence: 99%

Concanavalin A-captured Glycoproteins in Healthy Human Urine

Wang

Sun

et al. 2006

Molecular & Cellular Proteomics

115

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“…It is likely that many more spectra could be assigned to each of these classes of chemical modifications with more extended searching, and there are undoubtedly additional classes of chemical modifications yet to be discovered. We conclude from these studies that in most cases these additional identifications do not add to the number of distinct peptides or proteins that can be identified, and may even eliminate borderline identifications by providing alternative explanations (21). We found that relatively few unmodified CICAT peptides were eliminated by this means.…”

Section: Discussionmentioning

confidence: 99%

“…In this report, the ChemScore of the b(n-1)ϩ18 ion is counted the same as an ordinary b ion (Table I, rule 21).…”

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confidence: 99%

Depth of Proteome Issues

Parker¹,

Patterson²,

Williamson³

et al. 2004

Molecular & Cellular Proteomics

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As a test case for optimizing how to perform proteomics experiments, we chose a yeast model system in which the UPF1 gene, a protein involved in nonsense-mediated mRNA decay, was knocked out by homologous recombination. The results from five complete isotope-coded affinity tag (ICAT) experiments were combined, two using matrix-assisted laser desorption/ionization (MALDI) tandem mass spectrometry (MS/MS) and three using electrospray MS/MS. We sought to assess the reproducibility of peptide identification and to develop an informatics structure that characterizes the identification process as well as possible, especially with regard to tenuous identifications. The cleavable form of the ICAT reagent system (Gygi et al. (1999) Nat. Biotechnol. 17, 994 -999) was used for quantification. Most proteins did not change significantly in expression as a consequence of the upf1 knockout. As expected, the Upf1 protein itself was down-regulated, and there were reproducible increases in expression of proteins involved in arginine biosynthesis. Initially, it seemed that about 10% of the proteins had changed in expression level, but after more thorough examination of the data it turned out that most of these apparent changes could be explained by artifacts of quantification caused by overlapping heavy/light pairs. About 700 proteins altogether were identified with high confidence and quantified. Many peptides with chemical modifications were identified, as well as peptides with noncanonical tryptic termini. Nearly all of these modified peptides corresponded to the most abundant yeast proteins, and some would otherwise have been attributed to "single hit" proteins at low confidence. To improve our confidence in the identifications, in MALDI experiments, the parent masses for the peptides were calibrated against nearby components. In addition, five novel parameters reflecting different aspects of identification were collected for each spectrum in addition to the Mascot score that was originally used. The interrelationship between these scoring parameters and confidence in protein identification is discussed. Molecular & Cellular Proteomics 3:625-659, 2004.One of the goals of proteomic research is to identify (correctly) and quantify as many proteins as possible in the biological system of choice (see Refs. 1 and 2 for general reviews). We chose a yeast system for this study because it is possible to get large quantities of biological material from yeast cells using fermentation, and the yeast genome encodes Ͻ6600 rather well-characterized proteins whose abundance can be estimated based on the codon adaptation index (3). At the biological level, we chose to study two yeast strains that were related by the knockout of Upf1p (the protein encoded by the UPF1 gene), a protein that is crucial to the process of nonsense-mediated mRNA decay (4, 5).1 We used the isotope-coded affinity tag (ICAT) 2 reagent approach (6) to

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“…The algorithms will therefore fail to find a correct answer if the sample peptide differs from a canonical version in a database due to mutations, posttranslational modifications (PTMs) or database sequence errors, because the calculated mass from the database sequence may no longer match the measured mass. A list of peptide candidates that do not include the correct peptide will provide incorrect answers [3]. To overcome this drawback, an exhaustive search approach was suggested [4] where a virtual database of all modified peptides from a small set of potential modifications is generated and experimental spectra are matched against this enlarged database.…”

Section: Introductionmentioning

confidence: 99%

PepTiger: Search Engine for Error-Tolerant Protein Identification from de Novo Sequences

Fedulova¹,

Ouyang²,

Buck³

et al. 2007

TOSPECJ

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Abstract:In recent years a number of de novo sequencing software products became available providing possible partial or complete amino acid sequence tags for MS/MS spectra of peptides. However, for a variety of reasons including spectral chemical noise and imperfect fragmentation these sequence tags almost always contain errors. Additional difficulties arise from actual protein sequence variation and post-translational modifications. We present a search engine named PepTiger which is capable of correctly matching de novo sequence tags with errors to protein sequences in a protein database. The algorithm is based on approximate string matching followed by a novel scoring procedure which takes into account mass differences and the string distance between de novo sequence and matched peptides and similarities between theoretical and experimental MS/MS spectra. Comparison of PepTiger with other protein identification software shows that PepTiger is better able to assign de novo sequence tags with errors to the correct peptide sequences.

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Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry II.Limitations of complex mixture analyses

Cited by 126 publications

References 7 publications

Concanavalin A-captured Glycoproteins in Healthy Human Urine

Concanavalin A-captured Glycoproteins in Healthy Human Urine

Depth of Proteome Issues

PepTiger: Search Engine for Error-Tolerant Protein Identification from de Novo Sequences

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