The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.

Recent progress in metabolomics and the development of increasingly sensitive analytical techniques have renewed interest in global profiling, i.e., semiquantitative monitoring of all chemical constituents of biological fluids. In this work, we have performed global profiling of NIST SRM 1950, "Metabolites in Human Plasma", using GC-MS, LC-MS, and NMR. Metabolome coverage, difficulties, and reproducibility of the experiments on each platform are discussed. A total of 353 metabolites have been identified in this material. GC-MS provides 65 unique identifications, and most of the identifications from NMR overlap with the LC-MS identifications, except for some small sugars that are not directly found by LC-MS. Also, repeatability and intermediate precision analyses show that the SRM 1950 profiling is reproducible enough to consider this material as a good choice to distinguish between analytical and biological variability. Clinical laboratory data shows that most results are within the reference ranges for each assay. In-house computational tools have been developed or modified for MS data processing and interactive web display. All data and programs are freely available online at http://peptide.nist.gov/ and http://srmd.nist.gov/ .

Some of the most prominent "neutral losses" in peptide ion fragmentation are the loss of ammonia and water from N-terminal glutamine. These processes are studied by electrospray ionization mass spectrometry in singly-and doubly-protonated peptide ions undergoing collision-induced dissociation in a triple quadrupole and in an ion trap instrument. For this study, four sets of peptides were synthesized: (1) QLLLPLLLK and similar peptides with K replaced by R, H, or L, and Q replaced by a number of amino acids, (2) QL n K (n ϭ 0, 1, 3, 5, 7, 9, 11), (3) QL n R (n ϭ 0, 1, 3, 5, 7, 9), and (4) QL n (n ϭ 1, 2, 3, 4, 8). The results for QLLLPLLLK and QLLLPLLLR show that the singly protonated ions undergo loss of ammonia and to a smaller extent loss of water, whereas the doubly protonated ions undergo predominant loss of water. The fast fragmentation next to P (forming the y 5 ion) occurs to a larger extent than the neutral losses from the singly protonated ions but much less than the water loss from the doubly protonated ions. The results from these and other peptides show that, in general, when N-terminal glutamine peptides have no "mobile protons", that is, the number of charges on the peptide is no greater than the number of basic amino acids (K, R, H), deamination is the predominant neutral loss fragmentation, but when mobile protons are present the predominant process is the loss of water. Both of these processes are faster than backbone fragmentation at the proline. These results are rationalized on the basis of resonance stabilization of the two types of five-membered ring products that would be formed in the neutral loss processes; the singly protonated ion yields the more stable neutral pyrrolidinone ring whereas the doubly protonated ion yields the protonated aminopyrroline ring (see Schemes). The generality of these trends is confirmed by analyzing an MS/MS spectra library of peptides derived from tryptic digests of yeast. In the absence of mobile protons, glutamine deamination is the most rapid neutral loss process. For peptides with mobile protons, dehydration from glutamine is far more rapid than from any other amino acid. Most strikingly, end terminal glutamine is by far the most labile source of neutral loss in excess-proton peptides, but not highly exceptional when mobile protons are not available. In addition, rates of deamination are faster in lysine versus arginine C-terminus peptides and 20 times faster in positively charged than negatively charged peptides, demonstrating that these formal neutral loss reactions are not "neutral reactions" but depend on charge state and stability. (J Am Soc Mass Spectrom 2007, 18, 27-36)

No abstract

N-glycosylation of proteins is well known to occur at asparagine residues that fall within the canonical consensus sequence N-X-S/T, but has also been identified at a small number of asparagine residues within N-X-C motifs, including the N491 residue of human serotransferrin. Here we report novel glycosylation sites within non-canonical consensus motifs, in the conformation N-X-C, based on mass spectrometry analysis of partially-deglycosylated glycopeptide targets. Alpha-1-acid glycoprotein (A1AG) and serotransferrin (Tf) were observed for the first time to be N-glycosylated on asparagine residues within a total of six unique non-canonical motifs. N-glycosylation was initially predicted in silico based on the evolutionary conservation of the N-X-C motif among related mammalian species, and demonstrated experimentally in A1AG from porcine, canine, and feline sources and in human serotransferrin. High-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed to collect fragmentation data of predicted GlcNAcylated peptides, and to assign modification sites within N-X-C motifs. A combination of targeted analytical techniques that includes complementary mass spectrometry platforms, enzymatic digestions, and partial-deglycosylation procedures, was developed to confirm the novel observations. Additionally, we found that A1AG in porcine and canine sources is highly N-glycosylated at a non-canonical motif (N-Q-C) based on semi-quantitative multiple-reaction monitoring (MRM) analysis – the first report of an N-X-C motif exhibiting substantial N-glycosylation. Although reports of N-X-C motif N-glycosylation are relatively uncommon in the literature, this work adds to a growing list of glycoproteins reported with glycosylation at various forms of non-canonical motifs.

To understand the effect of Se supplementation on health, it is critical to accurately assess the Se status in the human body by measuring reliable biomarkers. The preferred biomarkers of the Se status are selenoprotein P (SelP) and glutathione peroxidase 3 (GPx3) along with selenoalbumin (SeAlb), but there is still a real need for reference methods and reference materials to validate their measurements. Therefore, this work presents a systematic approach to provide quality control data in selenoprotein measurements. This approach combines online isotope dilution affinity liquid chromatography (LC) coupled to inductively coupled plasma mass spectrometry (ICPMS), laser ablation ICPMS, and tandem mass spectrometry (MS/MS) to identify and quantify SelP, GPx3, and SeAlb in a human plasma reference material SRM 1950. Quantitative determinations of SelP, GPx3, and SeAlb were 50.2 ± 4.3, 23.6 ± 1.3, and 28.2 ± 2.6 ng g(-1) as Se, respectively. The subsequent identification of the selenoproteins included nine SelP peptides, including two selenopeptides and nine GPx3 peptides, while albumin was identified with a protein coverage factor >95%. The structural elucidation of selenoproteins in the target Se affinity fractions in SRM 1950 provides information needed for method validation and quality control measurements of selenoproteins and therefore the selenium status in human plasma.

This work presents a method for creating a mass spectral library containing tandem spectra of identifiable peptide ions in the tryptic digestion of a single protein. Human serum albumin (HSA 1 ) was selected for this purpose owing to its ubiquity, high level of characterization and availability of digest data. The underlying experimental data consisted of ϳ3000 one-dimensional LC-ESI-MS/MS runs with ion-trap fragmentation. In order to generate a wide range of peptides, studies covered a broad set of instrument and digestion conditions using multiple sources of HSA and trypsin. Computer methods were developed to enable the reliable identification and reference spectrum extraction of all peptide ions identifiable by current sequence search methods. This process made use of both MS2 (tandem) spectra and MS1 (electrospray) data. Identified spectra were generated for 2918 different peptide ions, using a variety of manually-validated filters to ensure spectrum quality and identification reliability. Shotgun proteomics is a widely used and evolving method for determining the protein composition of a biological mixture (1-3). It most often involves the digestion of denatured proteins by trypsin, followed by the identification of product peptides and the use of this information to infer protein identities and possibly targeted post-translational modifications (PTMs)1 . However, because digestion is a highly complex chemical process, a large proportion of identifiable products are not specifically targeted for analysis and therefore invisible to the analysis. These include unexpected and unwanted peptides that interfere with the analysis. Others may contain modifications of biological origin, which, unless specifically targeted, can be lost among the forest of artifacts (4 -6). This paper describes methods for building a tandem mass spectral library capable of characterizing all identifiable peptides in a tryptic digest of a selected protein. Spectral libraries are known to provide an effective way of reusing this information to quickly, reliably, and sensitively determine peptide identities (7-11). These identifications can serve several purposes, including 1) ensuring that all previously identified peptides are identified regardless of search engine settings, 2) tagging artifact peptides that might otherwise lead to false positive identifications, 3) ensuring the identification of known and identifiable biological post-translational modifications without explicitly looking for them, and 4) providing a list of artifact peptides for assessing the quality of the sample preparation process.HSA, human serum albumin, was selected as the target protein for library development partly because of its ubiquity, making up Ͼ50% of the total protein in blood (12-13) and therefore found in many biological samples, and partly because of the considerable background information available