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With the rapid assimilation of genomic information and the equally impressive developments in the field of proteomics, there is an unprecedented interest in biomarker discovery. Although human biofluids represent increasingly attractive samples from which new and more accurate disease biomarkers may be found, the intrinsic person-to-person variability in these samples complicates their discovery. One of the most extensively used animal models for studying human disease is mouse because, unlike humans, they represent a highly controllable experimental model system. Unfortunately, very little is known about the proteomic composition of mouse serum. In this study, a multidimensional fractionation approach on both the protein and the peptide level that does not require depletion of highly abundant serum proteins was combined with tandem mass spectrometry to characterize proteins within mouse serum. Over 12 300 unique peptides that originate from 4567 unique proteins&sbd;approximately 16% of all known mouse proteins&sbd;were identified. The results presented here represent the broadest proteome coverage in mouse serum and provide a foundation from which quantitative comparisons can be made in this important animal model. Keywords: mouse • serum proteomics • multidimensional fractionation • tandem mass spectrometry

Metastatic lesions occur in up to 36% of patients with pheochromocytoma. Currently there is no way to reliably detect or predict which patients are at risk for metastatic pheochromocytoma. Thus, the discovery of biomarkers that could distinguish patients with benign disease from those with metastatic disease would be of great clinical value. Using surface-enhanced laser desorption ionization protein chips combined with high-resolution mass spectrometry, we tested the hypothesis that pheochromocytoma pathologic states can be reflected as biomarker information within the low molecular weight (LMW) region of the serum proteome. LMW protein profiles were generated from the serum of 67 pheochromocytoma patients from four institutions and analyzed by two different bioinformatics approaches employing pattern recognition algorithms to determine if the LMW component of the circulatory proteome contains potentially useful discriminatory information. Both approaches were able to identify combinations of LMW molecules which could distinguish all metastatic from all benign pheochromocytomas in a separate blinded validation set.In conclusion, for this study set low molecular mass biomarker information correlated with pheochromocytoma pathologic state using blinded validation. If confirmed in larger validation studies, efforts to identify the underlying diagnostic molecules by sequencing would be warranted. In the future, measurement of these biomarkers could be potentially used to improve the ability to identify patients with metastatic disease.

Enzyme-mediated ¹⁸O/¹⁶O differential labeling of proteome samples often suffers from incomplete exchange of the carboxy-terminus oxygen atoms, resulting in ambiguity in the measurable abundance differences. In this study, an ¹⁸O/¹⁶O labeling strategy was optimized for and applied to the solution-based comparative analysis of the detergent-resistant membrane proteome (DRMP) of untreated and Iota-b (Ib)-induced Vero cells. Solubilization and tryptic digestion of the DRMP was conducted in a buffer containing 60% methanol. Unfortunately, the activity of trypsin is attenuated at this methanol concentration hampering the ability to obtain complete oxygen atom turnover. Therefore, the incorporation of the ¹⁸O atoms was decoupled from the protein digestion step by carrying out the trypsin-mediated heavy atom incorporation in a buffer containing 20% methanol; a concentration at which trypsin activity is enhanced compared to purely aqueous conditions. After isotopic labeling, the samples were combined, fractionated by strong cation exchange and analyzed by microcapillary reversed-phase liquid chromatography coupled on-line with electrospray ionization tandem mass spectrometry. In total, over 1400 unique peptides, corresponding to almost 600 proteins, were identified and quantitated, including all known caveolar and lipid raft marker proteins. The quantitative profiling of Ib-induced DRMP from Vero cells revealed several proteins with altered expression levels suggesting their possible role in Ib binding/uptake. Keywords: membrane proteins • quantitation • ¹⁸O/¹⁶O labeling • lota-b toxin

The endothelium plays a critical role in orchestrating the inflammatory response seen during sepsis. Many of the inflammatory effects of Gram-negative sepsis are elicited by lipopolysaccharide (LPS), a glycolipid component of bacterial cell walls. Lipid-rich microdomains have been shown to concentrate components of the LPS signaling system. However, much remains to be learned about which proteins are constituents of lipid microdomains, and how these are regulated following cell activation. Progress in this area would be accelerated by employing global proteomic analyses, but the hydrophobicity of membrane proteins presents an analytical barrier to the effective application of such approaches. Herein, we describe a method to isolate detergent-resistant membranes from endothelial cells, and prepare these samples for proteomic analysis in a way that is compatible with subsequent separations and mass spectrometric (MS) analysis. In the application of these sample preparation and MS analyses, 358 proteins from the lipid-rich microdomains of LPS-activated endothelial cell membranes have been identified of which half are classified as membrane proteins by Gene Ontology. We also demonstrate that the sample preparation method used for solubilization and trypsin digestion of lipid-rich microdomains renders the membrane spanning sequences of transmembrane proteins accessible for endoproteolytic hydrolysis. This analysis sets the analytical foundation for an in-depth probing of LPS signaling in endothelial cells. Keywords: lipopolysaccharide • endothelium • caveolae • lipid rafts • lipid-rich microdomains • inflammation

This study describes the application of a single tube sample preparation technique coupled with multidimensional fractionation for the analysis of a complex membrane protein sample from murine natural killer (NK) cells. A solution-based method that facilitates the solubilization and tryptic digestion of integral membrane proteins is conjoined with strong cation exchange (SCX) liquid chromatography (LC) fractionation followed by microcapillary reversed-phase (μRP) LC tandem mass spectrometric analysis of each SCXLC fraction in second dimension. Sonication in buffered methanol solution was employed to solubilize, and tryptically digest murine NK cell microsomal proteins, allowing for the large-scale identification of integral membrane proteins, including the mapping of the membrane-spanning peptides. Bioinformatic analysis of the acquired tandem mass spectra versus the murine genome database resulted in 11 967 matching tryptic peptide sequences, corresponding to 5782 unique peptide identifications. These peptides resulted in identification of 2563 proteins of which 876 (34%) are classified as membrane proteins. Keywords: membrane proteins • large-scale membrane proteomics • solution-based multidimensional proteomic analysis

Serum proteomic pattern diagnostics is an emerging paradigm employing low-resolution mass spectrometry (MS) to generate a set of biomarker classifiers. In the present study, we utilized a well-controlled ovarian cancer serum study set to compare the sensitivity and specificity of serum proteomic diagnostic patterns acquired using a high-resolution versus a low-resolution MS platform. In blinded testing sets, the high-resolution mass spectral data contained multiple diagnostic signatures that were superior to the low-resolution spectra in terms of sensitivity and specificity (P<0.00001) throughout the range of modeling conditions. Four mass spectral feature set patterns acquired from data obtained exclusively with the high-resolution mass spectrometer were 100% specific and sensitive in their diagnosis of serum samples as being acquired from either unaffected patients or those suffering from ovarian cancer. Important to the future of proteomic pattern diagnostics is the ability to recognize inferior spectra statistically, so that those resulting from a specific process error are recognized prior to their potentially incorrect (and damaging) diagnosis. To meet this need, we have developed a series of quality-assurance and in-process control procedures to (a) globally evaluate sources of sample variability, (b) identify outlying mass spectra, and (c) develop quality-control release specifications. From these quality-assurance and control (QA/QC) specifications, we identified 32 mass spectra out of the total 248 that showed statistically significant differences from the norm. Hence, 216 of the initial 248 high-resolution mass spectra were determined to be of high quality and were remodeled by pattern-recognition analysis. Again, we obtained four mass spectral feature set patterns that also exhibited 100% sensitivity and specificity in blinded validation tests (68/68 cancer: including 18/18 stage I, and 43/43 healthy). We conclude that (a) the use of high-resolution MS yields superior classification patterns as compared with those obtained with lower resolution instrumentation; (b) although the process error that we discovered did not have a deleterious impact on the present results obtained from proteomic pattern analysis, the major source of spectral variability emanated from mass spectral acquisition, and not bias at the clinical collection site; (c) this variability can be reduced and monitored through the use of QA/QC statistical procedures; (d) multiple and distinct proteomic patterns, comprising low molecular weight biomarkers, detected by high-resolution MS achieve accuracies surpassing individual biomarkers, warranting validation in a large clinical study.

The new generation of isotope-coded affinity tag (ICAT) reagents have been evaluated by labeling an equimolar amount of bovine serum albumin (BSA) with ICAT-¹²C9 and ICAT-¹³C9, combining the mixtures, digesting them with trypsin and analyzing the digestate both by μRPLC-tandem MS and by matrix-assisted laser desorption ionization (MALDI) TOF/TOF MS. The use of ¹³C in place of ²H resulted in both of the labeled peptides having identical elution characteristics in a reversed-phase separation. This similarity in elution allows ICAT-labeled peptides to be effectively analyzed using a μRPLC−MALDI−MS strategy as well. All of the cysteinyl-containing tryptic peptides from BSA were identified with only a 10% variation in the relative abundance measurements between the light and heavy versions of each peptide. A facile method for the removal of contaminants that arise from the cleaved biotin moiety that otherwise interfere with downstream separations and MS analysis has also been developed. The new ICAT reagents were then applied to the analysis of a cortical neuron proteome sample to identify proteins regulated by the antitumor drug, camptothecin. Keywords: isotope-coded affinity tags • quantitative proteomics • mass spectrometry • cortical neurons