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Francisella tularensis, the causative agent of tularaemia, is a potential agent of bioterrorism. The phenotypic discrimination of the closely related F. tularensis subspecies and individual strains with traditional methods is difficult and time consuming, often producing ambiguous results. Surface-enhanced laser desorption/ionization time-of-flight MS (SELDI-TOF MS) was used in this study to discriminate the different species and subspecies of the genus Francisella. We tested 18 Francisella strains including at least one representative of each species/subspecies on four different types of chromatographic chip surfaces. Multivariate analysis (hierarchical clustering and principal component analysis) allowed grouping of the strains according to their designated subspecies. Furthermore, single strains within F. tularensis subspecies could be discriminated.

A feasibility study to couple high throughput screening of packed bed chromatography with mass spectrometric detection by SELDI-TOF MS is presented. As model system monoclonal antibodies (mAb) versus host cell protein (HCP) from an industrial cultivation was chosen. Packed bed chromatography was screened on a TECAN Evo Freedom 200 station using miniaturized chromatographic columns placed on a specially designed array carrier linked to a commercially available T-Stack module. Gradient elution of the bound proteins was performed by applying a multiple step strategy. When analyzing selected HCP peaks as well as the detected antibody peaks throughout the chromatographic runs a direct correlation between applied and detected components was established. The sensitivity of conventional protein A chromatography was found to be lower than SELDI-TOF MS analysis. During initial screening a shift in the elution pattern for one of the monoclonal antibodies detected with all four resins was identified to be a heterogeneity in the mAb glycosylation pattern. In addition, a detailed differentiation between various HCP fractions through out the chromatographic process using SELDI-TOF analysis let to the detection of HCP components possibly adhering to the mAbs during chromatographic separations. Biotechnol. Bioeng. 2007;98; 440–450. © 2007 Wiley Periodicals, Inc.

The accurate diagnosis of the different forms of chronic mature B-cell lymphocytic malignancies is of primary importance to determine an appropriate and efficient treatment. Usually, the diagnosis is achieved by morphology and immunophenotyping. Nevertheless, the diagnostic tools available are not able to discriminate pathologies with variable evolution, or to classify some of them. To discover new biomarkers, we used peptide and protein profiling SELDI-TOF-MS, to analyze 39 chronic B-cell malignancies and 20 control serum samples. Markers of interest were subsequently identified and characterized. In the obtained SELDI-MS profiles, most of the differences were observed in three mass ranges (m/z = 13 000; m/z = 9000; m/z2000). Identification of these biomarkers was achieved either by direct enrichment on the ProteinChip arrays followed by on-chip-MS/MS or by chromatographic fractionation, 1D-gel followed by nanoLC-MS/MS analysis. An increase of a sulfite form of transthyretin (13,841 Da) was observed in the patient group. A second set of markers at 8.6 and 8.9 kDa was identified as complement related fragment proteins, the C3a and C4a anaphylatoxins. In the low mass range, several peptides originating from N-terminal and C-terminal processing of the C3 alpha and C4 alpha chains were specifically observed in 38% of the patient sera, but in none of the control sera. This study emphasizes the usefulness of mass spectrometry studies in such malignancies.

Although colorectal cancer is one of the best-characterized tumors with regard to the multistep progression, it remains one of the most frequent and deadly neoplasms. For a better understanding of the molecular mechanisms behind the process of tumorigenesis and tumor progression, changes in protein expression between microdissected normal and tumorous colonic epithelium were analyzed. Cryostat sections from colorectal tumors, adenoma tissue, and adjacent normal mucosa were laser-microdissected and analyzed using ProteinChip Arrays. The derived MS profiles exhibited numerous statistical differences. One peak showing significantly high expression in the tumor was purified by reverse-phase chromatography and SDS-PAGE. The protein band of interest was passively eluted from the gel and identified as heat shock protein 10 (HSP 10) by tryptic digestion, peptide mapping, and MS/MS analysis. This tumor marker was further characterized by immunohistochemistry. Analysis of HSP 10-positive tissue by ProteinChip technology confirmed the identity of this protein. This work demonstrates that biomarker in colorectal cancer can be detected, identified, and assessed by a proteomic approach comprising tissue microdissection, protein profiling, and immunological techniques. In our experience, histological defined microdissected tissue areas should be used to identify proteins that might be responsible for tumorigenesis.

In this study, we describe a differential mass spectrometric technique for the immuno-proteomic analysis of the major histocompatibility complex (MHC) peptides of a renal cell carcinoma (RCC) biopsy compared with the healthy kidney tissue of the same patient after nephrectomy. Using a stable isotope labeling approach, we could directly compare and relatively quantify 43 MHC-peptide pairs, most of which were present in similar proportions on both normal kidney and tumor. Significantly, two dominant peptides of monoisotopic masses ([M+H](+)) 973.43 u and 967.59 u, respectively, were found exclusively in the tumor sample. One of these was identified as originating from heme oxygenase-1 (HO-1), a protein involved in induction of apoptosis resistance, immuno-suppression and neoangiogenesis and reported to be up-regulated in various cancer types. Moreover, the corresponding synthetic HO-1-derived peptide was shown to be immunogenic in vitro by generation of CD8+ T cell lines with peptide-specific cytolytic activity. Thus, this peptide is an example of a differentially identified T cell epitope that could be considered as a target for immunotherapy.

The calcium-binding proteins of the S100 and the annexin protein families have been implicated in a variety of important physiological functions including membrane remodeling, calcium-related intracellular signaling, cytoskeleton dynamics, tissue homeostasis, and formation of the cornified envelope in differentiating keratinocytes. Deregulated expression of members of these families has been reported in different types of neoplasia and other diseases, but the results were not consistent. Here we have applied a combination of cDNA microarrays, quantitative reverse transcriptase-PCR (qRT-PCR) and surface enhanced laser desorption ionisation-time of flight mass spectrometry (SELDI-TOF MS) to study differential expression of these genes in head and neck squamous cell carcinoma (HNSCC). The calgranulins A and B and annexins 1 and 2 were found to be down-regulated in HNSCC, compared with normal mucosa, at both the mRNA and protein level. Upon validation of the differential gene expression by tissue microarray immunohistochemistry, we detected novel expression patterns of calgranulins A and B both in normal mucosa as well as in HNSCC. In contrast to squamous cancer of skin and other cancers in which the calgranulins were found to be up-regulated, most HNSCC showed reduced and widely deranged staining patterns including heterogeneous nuclear, cytoplasmic and membranous staining, and even enhanced staining in the tumor stroma. These observations suggest that the normal function of the calgranulins A and B in mucosa might be different from that in skin.

The molecular analysis of serum is an important field for the definition of potential diagnostic markers or disease-related protein alterations. Novel proteomic technologies such as the mass spectrometric-based surface-enhanced laser desorption/ionization (SELDI) ProteinChip technique facilitate a rapid and reproducible analysis of such protein mixtures and affords the researcher a new dimension in the search for biomarkers of disease. Here, we have applied this technology to the study of a cohort of serum samples from well-characterized renal cell carcinoma patients for the identification of such proteins by comparison to healthy controls. We detected and characterized haptoglobin 1 alpha and serum amyloid alpha-1 (SAA-1) as disease related, in addition to an as-yet-unidentified marker of 10.84 kDa. Of particular note is the detection of multiple variants of SAA-1 in multiplex that have not been described in the sera of cancer patients. SAA-1 is detected as full-length protein, des-Arginine and des-Arginine/des-Serine variants at the N terminus by SELDI. In addition, we could also detect a low-abundant variant minus the first five N-terminal amino acids. Such variants may impact the function of the protein. We conclude the technique to be a reproducible, fast and simple mode for the discovery and analysis of marker proteins of disease in serum.

Biomarkers are needed to elucidate the biological background and to improve the detection of cancer. Therefore, we have analyzed laser-microdissected cryostat sections from head and neck tumors and adjacent mucosa on ProteinChip arrays. Two differentially expressed proteins (P = 3.34 × 10−5 and 4.6 × 10−5) were isolated by two-dimensional gel electrophoresis and identified as S100A8 (calgranulin A) and S100A9 (calgranulin B) by in-gel proteolytic digestion, peptide mapping, tandem mass spectrometry analysis, and immunodepletion assay. The relevance of these single marker proteins was evaluated by immunohistochemistry. Positive tissue areas were reanalyzed on ProteinChip arrays to confirm the identity of these proteins. As a control, a peak with low P was identified as calgizzarin (S100A11) and characterized in the same way. This technical triade of tissue microdissection, ProteinChip technology, and immunohistochemistry opens up the possibility to find, identify, and characterize tumor relevant biomarkers, which will allow the movement toward the clonal heterogeneity of malignant tumors. Taking this approach, proteins were identified that might be responsible for invasion and metastasis.

Recently, a novel antimicrobial peptide DCD-1, derived from the Dermcidin (DCD) gene and secreted by sweat glands, has been described by Schittek et al. [Nat. Immunol. 2 (2001) 1133.]. Here we describe the application of the surface-enhanced laser desorption/ionisation (SELDI) technology for the detection of DCD-1 and other dermcidin-derived peptides directly from microlitre amounts of human sweat. The advantages of the technique are as follows: (a) it can be carried out with ease and rapidity; (b) multiple samples can be processed simultaneously; (c) prior purification is not required; and (d) only a limited sample volume is necessary for both protein profiling and semiquantitation. Profiling of human sweat from various donors revealed that in addition to DCD-1, other DCD-derived peptide species were also present in significant quantities. Four of five identified peptides were DCD-1 related, while the fifth corresponded to a portion of the DCD protein outside the DCD-1 core. This provides clues as to how the novel protein is processed to its active form, though further work remains to elucidate this fully. Thus, we have demonstrated the applicability of such technology to the detection of DCD-1 and for the protein profiling of sweat in general. Such studies could reveal valuable new biomarkers for diagnosis and treatment of skin and sweat gland disorders.

Dimethylargininase (EC 3.5.3.18) is involved in the regulation of the levels of the natural occurring free arginine derivatives L-Nomega,Nomega-dimethylarginine and L-Nomega-methylarginine, which are reversible inhibitors of nitric oxide synthase. A dimethylargininase has been isolated from bovine brain tissue and was characterized by using immunological, kinetic, and spectroscopic techniques. Western blot analysis using polyclonal antibodies revealed that the enzyme is widely distributed in bovine with the highest relative concentrations found in brain and kidney tissue. A similar tissue distribution has also been reported for the other so far isolated dimethylargininase from rat kidney [Ogawa, T., Kimoto, M., and Sasaoka, K. (1989) J. Biol. Chem. 264, 10205-10209]. The bovine enzyme is a monomeric, globular protein (molecular mass approximately 31.2 kDa) containing one tightly bound Zn2+ ion, which can be removed by dialysis against 1,10-phenanthroline. The determination of kinetic constants for both the native (holo-protein) and the zinc-depleted (apo-protein) enzyme at 37 degrees ¿C established that the dimethylargininase is not a zinc hydrolase. The specific activity was 0.66 unit/mg for the holo-protein and 0.19 unit/mg for the apo-protein. The secondary structure determination of the native enzyme by circular dichroism revealed 41% alpha-helix and 32% beta-sheet and beta-turn structure. In the apo-enzyme, a small, but significant decrease in the alpha-helical content (5%) was observed, consistent with a marked decrease in enzymatic activity to 30%. Upon preincubation of both enzyme forms at 50 degrees C, only the holo-enzyme showed a residual enzymatic activity. In thermostability studies, a 7 degrees C lower apparent Tm value was observed for the apo-enzyme compared to the 66 degrees C for the holo-enzyme, suggesting that the zinc ion has a structure-stabilizing role. Besides the tightly bound zinc, additional Zn2+ ions inhibit the enzyme competitively with a Ki value of 2.0 microM. A possible interrelationship between dimethylargininase and nitric oxide synthase is discussed.

Objective Testing of serum for protein patterns to monitor progression of suspected to definite chronic pancreatitis (CP). Methods Serum samples of CP patients and healthy volunteers were fractionated on anion exchange columns and analyzed by surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry to elucidate CP-related protein alterations and to identify biomarkers for this disease. Potential biomarkers were purified and identified by mass spectrometry. Results In total, 258 protein peaks were found that discriminated between the 2 groups. Analysis revealed 28 most prominent peaks on immobilized metal affinity capture coupled with Cu and CM10 protein chips, covering the m/z range between 3.3 and 33.3 kd. Performing multivariate pattern analysis, the best pattern model was obtained using fraction 6 on immobilized metal affinity capture coupled with Cu arrays with a sensitivity of 96% and a specificity of 84%. Using a combination of matrix-assisted laser desorption-ionization-time-of-flight mass spectrometry and immunodepletion, we identified 14-m/z peaks. The proteins were found to be significantly decreased in CP serum and were identified as retinol-binding protein, serum amyloid-alpha, apolipoprotein A-II (Apo A-II), Apo C-I, Apo C-II, Apo C-III, and transthyretin and truncated forms thereof. Conclusions Distinct protein profile differences exist between normal and CP serum and reflect the metabolic and inflammatory condition in CP patients. The identified protein panel may eventually serve as a diagnostic marker set for CP.

Objective: Early detection is the only promising approach to significantly improve the survival of patients with pancreatic cancer (PCa). Noninvasive tools for the diagnosis, prognosis, and monitoring of this disease are of urgent need. The purpose of this study was to identify and validate new biomarkers in PCa patient serum samples. Methods: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry has been applied to analyze serum protein alterations associated with PCa and to identify sets of potential biomarkers indicative for this disease. A cohort of 96 serum samples from patients undergoing PCa surgery was compared with sera from 96 healthy volunteers as controls. The sera were fractionated by anion exchange chromatography, and 3 of 6 fractions were analyzed onto 2 different chromatographic arrays. Results: Data analysis revealed 24 differentially expressed protein peaks (P < 0.001), of which 21 were downregulated in the PCa samples. The best single marker can predict 92% of the controls and 89% of the cancer samples correctly. In addition, multivariate pattern analysis was performed. The best pattern model using a set of 3 markers was obtained using fraction 6 on immobilized metal affinity capture, loaded with Cu-Cu arrays. With this pattern model, a sensitivity of 100% and a specificity of 98% for the training data set and a sensitivity of 83% and specificity of 77% for the test data set were achieved with the PCa group set as true positive. Several of protein peaks, including the best single marker at 17.27 kd and other proteins from the pattern models, were purified and identified by peptide mapping and postsource decay-matrix-assisted laser desorption ionization-time-of-flight mass spectrometry. Apolipoprotein A-II, transthyretin, and apolipoprotein A-I were identified as markers, and these identified proteins were decreased at least 2-fold in PCa serum when compared with the control group. Conclusions: PCa is associated with a specific decrease of distinct serum proteins, which allows a reliable differentiation between pancreatic cancer and healthy controls.

The resistance of the malarial parasite Plasmodium falciparum to chloroquine represents an emerging problem since neither mode of drug action nor mechanisms of resistance are fully elucidated. We describe a protein expression profiling approach by SELDI-TOF-MS as a useful tool for studying the proteome of malarial parasites. Reproducible and complex protein profiles of the P. falciparum strains K1, Dd2, HB3 and 3D7 were measured on four array types. Hierarchical clustering led to a clear separation of the two major subgroups "resistant" and "sensitive" as well as of the four parasite strains. Our study delivers sets of regulated proteins derived from extensive comparative analyses of 64 P. falciparum protein profiles. A group of 12 peaks reflecting proteome changes under chloroquine treatment and a set of 10 potential chloroquine resistance markers were defined. Three of these regulated peaks were preparatively enriched, purified and identified. They were shown to represent the plasmodial EXP-1 protein, also called circumsporozoite-related antigen, as well as the alpha- and beta- (delta-) chains of human hemoglobin.

Development of head and neck squamous cell carcinoma (HNSCC) is a multistep process and in many cases involves a phenomenon coined 'field cancerization'. In order to identify changes in protein expression occurring at different stages of tumorigenesis and field cancerization, we analysed 113 HNSCCs and 73 healthy, 99 tumor-distant and 18 tumor-adjacent squamous mucosae by SELDI-TOF-MS on IMAC30 ProteinChip Arrays. Forty-eight protein peaks were differentially expressed between healthy mucosa and HNSCC. Calgizarrin (S100A11), the Cystein proteinase inhibitor Cystatin A, Acyl-CoA-binding protein, Stratifin (14-3-3 sigma), Histone H4, alpha- and beta-Hemoglobin, a C-terminal fragment of beta-hemoglobin and the alpha-defensins 1-3 were identified by mass spectrometry. The alpha-defensins showed various alterations in expression as validated by immunohistochemistry (IHC). Supervised prediction analysis revealed excellent classification of healthy mucosa (94.5% correctly classified) and tumor samples (92.9% correctly classified). Application of this classifier to the tumor-adjacent and tumor-distant mucosa samples disclosed dramatic changes: only 59.6% of the tumor-distant biopsies were classified as normal, 27.3% were predicted as aberrant or HNSCC. Strikingly, 72% of the tumor-adjacent mucosae were predicted as aberrant. These data provide evidence for the existence of genetically altered fields with inconspicuous histology. Comparison of the protein profiles in the tumor-distant-samples with clinical outcome of 32 patients revealed a significant association between aberrant profiles with tumor relapse events (P=0.018; Fisher's exact test, two-tailed). We conclude that proteomic profiling in conjunction with protein identification greatly outperforms histopathological diagnosis and may have significant predictive power for clinical outcome and personalized risk assessment.

Novel prognostic biomarkers are imperatively needed to help direct treatment decisions by typing subgroups of node-negative breast cancer patients. The current study has used a proteomic approach of SELDI-TOF-MS screening to identify differentially cytosolic expressed proteins with a prognostic impact in 30 node-negative breast cancer patients with no relapse versus 30 patients with metastatic relapse. The data analysis took into account 73 peaks, among which 2 proved, by means of univariate Cox regression, to have a good cumulative prognostic-informative power. Repeated random sampling (n = 500) was performed to ensure the reliability of the peaks. Optimized thresholds were then computed to use both peaks as risk factors and, adding them to the St. Gallen ones, improve the prognostic classification of node-negative breast cancer patients. Identification of ubiquitin and ferritin light chain (FLC), corresponding to the two peaks of interest, was obtained using ProteinChip LDI-Qq-TOF-MS. Differential expression of the two proteins was further confirmed by Western blotting analyses and immunohistochemistry. SELDI-TOF-MS protein profiling clearly showed that a high level of cytosolic ubiquitin and/or a low level of FLC were associated with a good prognosis in breast cancer.

The diagnosis of brucellosis is mainly based on the detection of anti-LPS antibodies. Due to substantial similarity of the O-polysaccharide of Brucella LPS to that of various other Gram-negative bacteria, serological tests of samples containing high amounts of LPS lack specificity. Hence, the development of assays based on more specific protein antigens is an essential subject in brucellosis research. The aim of this study was proteomic characterization of various antigen preparations of the diagnostic reference strain Brucella abortus 1119-3 and the identification of immunogenic proteins suitable for serological assays. Seventeen out of 383 protein spots of B. abortus 1119-3 were identified to be immunogenic by 2-D immunoblotting. These immunogenic spots were assigned to 6 proteins by MALDI-MS and nLC-ESI-MS/MS: Cu-Zn SOD, BCSP31, L7/L12, GroEL, GroES, and DnaK. All immunogenic proteins were present in three different antigen preparations investigated, i.e. native antigen, standard agglutination and commercially available agglutination antigen. 2-D immunoblotting of bacteria cross-reacting with Brucellae in agglutination tests proved that cross-reactivity of proteins is negligible. Surface enhanced laser desorption/ionization mass spectrometry (SELDI-MS) spectra also differentiated B. abortus clearly from cross-reacting bacteria. The combination of SELDI-MS analysis with the specificity of antibody binding will improve the identification of Brucella specific immunogenic proteins.

Head and neck cancer is a frequent malignancy with a complex, and up to now not clear etiology. Therefore, despite of improvements in diagnosis and therapy, the survival rate with head and neck squamous-cell carcinomas is poor. For a better understanding of the molecular mechanisms behind the process of tumorigenesis and tumor progression, we have analyzed changes of protein expression between microdissected normal pharyngeal epithelium and tumor tissue by ProteinChip® technology. For this, cryostat sections from head and neck tumors (n = 57) and adjacent mucosa (n = 44) were laser-microdissected and analyzed on ProteinChip arrays. The derived mass spectrometry profiles exhibited numerous statistical differences. One peak significantly higher expressed in the tumor (p = 0.000029) was isolated by two-dimensional gel electrophoresis and identified as annexin V by in-gel proteolytic digestion, peptide mapping, tandem mass spectrometry analysis, and immuno-deplete assay. The relevance of this single marker protein was further evaluated by immunohistochemistry. Annexin-positive tissue areas were re-analyzed on ProteinChip arrays to confirm the identity of this protein. In this study, we could show that biomarker in head and neck cancer can be found, identified, and assessed by combination of ProteinChip technology, two-dimensional gel electrophoresis, and immunohistochemistry. In our experience, however, such studies only make sense if a relatively pure microdissected tumor tissue is used. Only then minute changes in protein expression between normal pharyngeal epithelium and tumor tissue can be detected, and it will become possible to educe a tumor-associated protein pattern that might be used as a marker for tumorigenesis and progression.

Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca. © 2013 Bouatra et al.