FXR overexpression alters adipose tissue architecture in mice and limits its storage capacity leading to metabolic derangements.

The bile acid-activated nuclear receptor, FXR (NR1H4), has been implicated in the control of lipid and energy metabolism, but its role in fat tissue, where it is moderately expressed, is not understood. In view of the recent development of FXR-targeting therapeutics for treatment of human metabolic diseases, understanding the tissue-specific actions of FXR is essential. Transgenic mice expressing human FXR in adipose tissue (aP2-hFXR mice) at three to five times higher levels than endogenous Fxr, i.e., much lower than its expression in liver and intestine, have markedly enlarged adipocytes and show extensive extracellular matrix remodeling. Ageing and exposure to obesogenic conditions revealed a strongly limited capacity for adipose expansion and development of fibrosis in adipose tissues of aP2-hFXR transgenic mice. This was associated with impaired lipid storage capacity, leading to elevated plasma free fatty acids and ectopic fat deposition in liver and muscle as well as whole-body insulin resistance. These studies establish that adipose FXR is a determinant of adipose tissue architecture and contributes to whole-body lipid homeostasis.

The use of metabolic profiling to identify insulin resistance in veal calves.

Heavy veal calves (4-6 months old) are at risk of developing insulin resistance and disturbed glucose homeostasis. Prolonged insulin resistance could lead to metabolic disorders and impaired growth performance. Recently, we discovered that heavy Holstein-Friesian calves raised on a high-lactose or high-fat diet did not differ in insulin sensitivity, that insulin sensitivity was low and 50% of the calves could be considered insulin resistant. Understanding the patho-physiological mechanisms underlying insulin resistance and discovering biomarkers for early diagnosis would be useful for developing prevention strategies. Therefore, we explored plasma metabolic profiling techniques to build models and discover potential biomarkers and pathways that can distinguish between insulin resistant and moderately insulin sensitive veal calves. The calves (n = 14) were classified as insulin resistant (IR) or moderately insulin sensitive (MIS) based on results from a euglycemic-hyperinsulinemic clamp, using a cut-off value (M/I-value <4.4) to identify insulin resistance. Metabolic profiles of fasting plasma samples were analyzed using reversed phase (RP) and hydrophilic interaction (HILIC) liquid chromatography-mass spectrometry (LC-MS). Orthogonal partial least square discriminant analysis was performed to compare metabolic profiles. Insulin sensitivity was on average 2.3x higher (P <0.001) in MIS than IR group. For both RP-LC-MS and HILIC-LC-MS satisfactory models were build (R2Y >90% and Q2Y >66%), which allowed discrimination between MIS and IR calves. A total of 7 and 20 metabolic features (for RP-LC-MS and HILIC-LC-MS respectively) were most responsible for group separation. Of these, 7 metabolites could putatively be identified that differed (P <0.05) between groups (potential biomarkers). Pathway analysis indicated disturbances in glycerophospholipid and sphingolipid metabolism, the glycine, serine and threonine metabolism, and primary bile acid biosynthesis. These results demonstrate that plasma metabolic profiling can be used to identify insulin resistance in veal calves and can lead to underlying mechanisms.

Quantitative proteomics analyses of activation states of human THP-1 macrophages.

Macrophages display large functional and phenotypical plasticity. They can adopt a broad range of activation states depending on their microenvironment. Various surface markers are used to characterize these differentially polarized macrophages. However, this is not informative for the functions of the macrophage. In order to have a better understanding of the functional changes of macrophages upon differential polarization, we studied differences in LPS- and IL4-stimulated macrophages. The THP-1 human monocytic cell line, was used as a model system. Cells were labeled, differentiated and stimulated with either LPS or IL-4 in a quantitative SILAC proteomics set-up. The resulting sets of proteins were functionally clustered. LPS-stimulated macrophages show increased secretion of proinflammatory peptides, leading to increased pressure on protein biosynthesis and processing. IL4-stimulated macrophages show upregulation of cell adhesion and extracellular matrix remodeling. Our approach provides an integrated view of polarization-induced functional changes and proves useful for studying functional differences between subsets of macrophages. Moreover, the identified polarization specific proteins may contribute to a better characterization of different activation states in situ and their role in various inflammatory processes.

Cell-based screening assay for anti-inflammatory activity of bioactive compounds.

Excess dietary intake may induce metabolic inflammation which is associated with insulin resistance and cardiovascular disease. Recent evidence indicates that dietary bioactive compounds may diminish metabolic inflammation. To identify anti-inflammatory bioactives, we developed a screening assay using the human H293-NF-κB-RE-luc2P reporter cell line. Under optimised conditions we determined the anti-inflammatory activity of vegetables and purified bioactives, by monitoring their potency to inhibit TNF-α-induced NF-κB activity, as assessed by sensitive chemiluminescence detection in a 96-well assay format. Minced broccoli seedlings reduced NF-κB activity by 16%, while sulphoraphane, the dominant bioactive in broccoli seedlings, inhibited NF-κB activity with an IC50 of 5.11 µmol/l. Short-chain fatty acids also reduced NF-κB activity in the order butyrate>propionate≫acetate with IC50 of 51, 223, and 1300 µmol/l, respectively. The H293-NF-κB-RE-luc2P reporter cell line is a sensitive tool for rapid high-throughput screening for bioactives with anti-inflammatory activity.

Clinical outcome, proteome kinetics and angiogenic factors in serum after thermoablation of colorectal liver metastases.

BACKGROUND: Thermoablation is used to treat patients with unresectable colorectal liver metastases (CRLM). We analyze clinical outcome, proteome kinetics and angiogenic markers in patients treated by cryosurgical ablation (CSA) or radiofrequency ablation (RFA). METHODS: 205 patients underwent CSA (n = 20), RFA (n = 22), partial hepatectomy (PH, n = 134) or were found truly unresectable (n = 29). Clinical outcome, proteome transitions and angiogenic response in serum were analyzed at various time points after ablation. RESULT: Median overall survival in CSA patients (17.6 months) was worse (p < 0.0001) when compared to RFA treated patients (51.7 months) and patients after PH (43.4 months). The complication rate was higher in the CSA group (50%) as compared to the RFA group (22%). Proteomics analyses showed consistently more changes in serum protein abundance with CSA compared to RFA. In the first four days after ablation a pro-angiogenic serum response occurred. CONCLUSIONS: RFA of CRLM is superior to CSA with a median survival which equals survival in patients after PH. Proteomics analyses suggests a more aggravated serum response to CSA compared to RFA. Thermoablation is associated with changes in serum levels of angiogenic factors favouring a pro-angiogenic environment, but without differences between RFA and CSA.

Short-chain fatty acids stimulate angiopoietin-like 4 synthesis in human colon adenocarcinoma cells by activating peroxisome proliferator-activated receptor γ.

Angiopoietin-like protein 4 (ANGPTL4/FIAF) has been proposed as a circulating mediator between the gut microbiota and fat storage. Here, we show that transcription and secretion of ANGPTL4 in human T84 and HT29 colon adenocarcinoma cells is highly induced by physiological concentrations of short-chain fatty acids (SCFA). SCFA induce ANGPTL4 by activating the nuclear receptor peroxisome proliferator activated receptor γ (PPARγ), as demonstrated using PPARγ antagonist, PPARγ knockdown, and transactivation assays, which show activation of PPARγ but not PPARα and PPARδ by SCFA. At concentrations required for PPARγ activation and ANGPTL4 induction in colon adenocarcinoma cells, SCFA do not stimulate PPARγ in mouse 3T3-L1 and human SGBS adipocytes, suggesting that SCFA act as selective PPARγ modulators (SPPARM), which is supported by coactivator peptide recruitment assay and structural modeling. Consistent with the notion that fermentation leads to PPAR activation in vivo, feeding mice a diet rich in inulin induced PPAR target genes and pathways in the colon. We conclude that (i) SCFA potently stimulate ANGPTL4 synthesis in human colon adenocarcinoma cells and (ii) SCFA transactivate and bind to PPARγ. Our data point to activation of PPARs as a novel mechanism of gene regulation by SCFA in the colon, in addition to other mechanisms of action of SCFA.

Propionic acid affects immune status and metabolism in adipose tissue from overweight subjects.

BACKGROUND: Adipose tissue is a primary site of obesity-induced inflammation, which is emerging as an important contributor to obesity-related diseases such as type 2 diabetes. Dietary fibre consumption appears to be protective. Short-chain fatty acids, e.g. propionic acid, are the principal products of the colonic fermentation of dietary fibre and may have beneficial effects on adipose tissue inflammation. MATERIALS AND METHODS: Human omental adipose tissue explants were obtained from overweight (mean BMI 28·8) gynaecological patients who underwent surgery. Explants were incubated for 24 h with propionic acid. Human THP-1 monocytic cells were differentiated to macrophages and incubated with LPS in the presence and absence of propionic acid. Cytokine and chemokine production were determined by multiplex-ELISA, and mRNA expression of metabolic and macrophages genes was determined by RT-PCR. RESULTS: Treatment of adipose tissue explants with propionic acid results in a significant down-regulation of several inflammatory cytokines and chemokines such as TNF-α and CCL5. In addition, expression of lipoprotein lipase and GLUT4, associated with lipogenesis and glucose uptake, respectively, increased. Similar effects on cytokine and chemokine production by macrophages were observed. CONCLUSION: We show that propionic acid, normally produced in the colon, may have a direct beneficial effect on visceral adipose tissue, reducing obesity-associated inflammation and increasing lipogenesis and glucose uptake. Effects on adipose tissue as a whole are at least partially explained by effects on macrophages but likely also adipocytes are involved. This suggests that, in vivo, propionic acid and dietary fibres may have potential in preventing obesity-related inflammation and associated diseases.

Comparative analysis of the human hepatic and adipose tissue transcriptomes during LPS-induced inflammation leads to the identification of differential biological pathways and candidate biomarkers.

BACKGROUND: Insulin resistance (IR) is accompanied by chronic low grade systemic inflammation, obesity, and deregulation of total body energy homeostasis. We induced inflammation in adipose and liver tissues in vitro in order to mimic inflammation in vivo with the aim to identify tissue-specific processes implicated in IR and to find biomarkers indicative for tissue-specific IR. METHODS: Human adipose and liver tissues were cultured in the absence or presence of LPS and DNA Microarray Technology was applied for their transcriptome analysis. Gene Ontology (GO), gene functional analysis, and prediction of genes encoding for secretome were performed using publicly available bioinformatics tools (DAVID, STRING, SecretomeP). The transcriptome data were validated by proteomics analysis of the inflamed adipose tissue secretome. RESULTS: LPS treatment significantly affected 667 and 483 genes in adipose and liver tissues respectively. The GO analysis revealed that during inflammation adipose tissue, compared to liver tissue, had more significantly upregulated genes, GO terms, and functional clusters related to inflammation and angiogenesis. The secretome prediction led to identification of 399 and 236 genes in adipose and liver tissue respectively. The secretomes of both tissues shared 66 genes and the remaining genes were the differential candidate biomarkers indicative for inflamed adipose or liver tissue. The transcriptome data of the inflamed adipose tissue secretome showed excellent correlation with the proteomics data. CONCLUSIONS: The higher number of altered proinflammatory genes, GO processes, and genes encoding for secretome during inflammation in adipose tissue compared to liver tissue, suggests that adipose tissue is the major organ contributing to the development of systemic inflammation observed in IR. The identified tissue-specific functional clusters and biomarkers might be used in a strategy for the development of tissue-targeted treatment of insulin resistance in patients.

Biological effects of propionic acid in humans; metabolism, potential applications and underlying mechanisms.

Undigested food is fermented in the colon by the microbiota and gives rise to various microbial metabolites. Short-chain fatty acids (SCFA), including acetic, propionic and butyric acid, are the principal metabolites produced. However, most of the literature focuses on butyrate and to a lesser extent on acetate; consequently, potential effects of propionic acid (PA) on physiology and pathology have long been underestimated. It has been demonstrated that PA lowers fatty acids content in liver and plasma, reduces food intake, exerts immunosuppressive actions and probably improves tissue insulin sensitivity. Thus increased production of PA by the microbiota might be considered beneficial in the context of prevention of obesity and diabetes type 2. The molecular mechanisms by which PA may exert this plethora of physiological effects are slowly being elucidated and include intestinal cyclooxygenase enzyme, the G-protein coupled receptors 41 and 43 and activation of the peroxisome proliferator-activated receptor γ, in turn inhibiting the sentinel transcription factor NF-κB and thus increasing the threshold for inflammatory responses in general. Taken together, PA emerges as a major mediator in the link between nutrition, gut microbiota and physiology.

Regulation of adipokine production in human adipose tissue by propionic acid.

BACKGROUND: Dietary fibre (DF) has been shown to be protective for the development of obesity, insulin resistance and type 2 diabetes. Short-chain fatty acids, produced by colonic fermentation of DF might mediate this beneficial effect. Adipose tissue plays a key role in the regulation of energy homeostasis, therefore, we investigated the influence of the short-chain fatty acid propionic acid (PA) on leptin, adiponectin and resistin production by human omental (OAT) and subcutaneous adipose tissue (SAT). As PA has been shown to be a ligand for G-protein coupled receptor (GPCR) 41 and 43, we investigated the role of GPCR's in PA signalling. MATERIALS AND METHODS: Human OAT and SAT explants were obtained from gynaecological patients who underwent surgery. Explants were incubated for 24 h with PA. Adipokine secretion and mRNA expression were determined using ELISA and RT-PCR respectively. RESULTS: We found that PA significantly stimulated leptin mRNA expression and secretion by OAT and SAT, whereas it had no effect on adiponectin. Furthermore, PA reduced resistin mRNA expression. Leptin induction, but not resistin reduction, was abolished by inhibition of Gi/o-coupled GPCR signalling. Moreover, GPCR41 and GPCR43 mRNA levels were considerably higher in SAT than in OAT. CONCLUSIONS: We demonstrate that PA stimulates expression of the anorexigenic hormone leptin and reduces the pro-inflammatory factor resistin in human adipose tissue depots. This suggests that PA is involved in regulation of human energy metabolism and inflammation and in this way may influence the development of obesity and type 2 diabetes.

Computational modeling of the human serum proteome response to colon resection surgery.

Principal component analysis (PCA) is much used in exploring time-course biological data sets, but does not distinguish variation between time and subjects. This study proposes a new integrated approach by combining analysis of variance (ANOVA) and three component modeling methods. The former was used to separate the between- and within-subject variation, and the latter represent modeling strategies on a scale moving from commonality to individuality. The proposed approach was applied to a surface-enhanced laser desorption and ionization time of flight mass spectrometry (SELDI-TOF-MS) data set of a serum protein expression time course before and after colon resection. Two common biological processes are identified and individual differences among patients were also detected, and the biological relevance of both is discussed.

Comparison of isotope-labeled amino acid incorporation rates (CILAIR) provides a quantitative method to study tissue secretomes.

Adipose tissue is an endocrine organ involved in regulation of whole-body energy metabolism via storage of lipids and secretion of various peptide hormones (adipokines). We previously characterized the adipose tissue secretome and showed that [(13)C]lysine incorporation into secreted proteins can be used to determine the origin of identified proteins. In the present study we determined the effect of insulin on the secretome by comparing incorporation rates of (13)C-labeled lysine in the presence and absence of insulin. Human visceral adipose tissue from one patient was divided over six dishes. After subsequent washes to remove serum proteins, [(13)C]lysine-containing medium was added. Three dishes also received 60 nm insulin. The other three were controls. After 72 h of culture, media were collected and processed separately, involving concentration by ultrafiltration and fractionation by SDS-PAGE followed by in-gel digestion of excised bands and LC-MS/MS analyses. The obtained spectra were used for database searching and calculation of heavy/light ratios. The three control data sets shared 342 proteins of which 156 were potentially secreted and contained label. The three insulin-derived data sets shared 361 proteins of which 141 were potentially secreted and contained label. After discarding secreted proteins with very low label incorporation, 121 and 113 proteins remained for control and insulin data sets, respectively. The average coefficient of variation for control triplicates was 10.0% and for insulin triplicates was 18.3%. By comparing heavy/light ratios in the absence and presence of insulin we found 24 up-regulated proteins and four down-regulated proteins, and 58 proteins showed no change. Proteins involved in the endoplasmic reticulum stress response and in extracellular matrix remodeling were up-regulated by insulin. In conclusion, comparison of isotope-labeled amino acid incorporation rates (CILAIR) allows quantitative assessment of changes in protein secretion without the need for 100% label incorporation, which cannot be reached in differentiated tissues or cells.

Proteomics analysis of Hodgkin lymphoma: identification of new players involved in the cross-talk between HRS cells and infiltrating lymphocytes.

Hodgkin and Reed-Sternberg (HRS) cells in Hodgkin lymphoma (HL) secrete factors that interact with inflammatory background cells and may serve as biomarkers for disease activity. To detect new proteins related to pathogenesis, we analyzed the secretome of HRS cells. Proteins in cell culture supernatant of 4 HL cell lines were identified using 1DGE followed by in-gel trypsin digestion and LC-MS/MS. In total, 1290 proteins, including 368 secreted proteins, were identified. Functional grouping of secreted proteins revealed 37 proteins involved in immune response. Sixteen of the 37 proteins (ie, ALCAM, Cathepsin C, Cathepsin S, CD100, CD150, CD26, CD44, CD63, CD71, Fractal-kine, IL1R2, IL25, IP-10, MIF, RANTES, and TARC) were validated in HL cell lines and patient material using immunohistochemistry and/or ELISA. Expression of all 16 proteins was confirmed in HL cell lines, and 15 were also confirmed in HL tissues. Seven proteins (ALCAM, cathepsin S, CD26, CD44, IL1R2, MIF, and TARC) revealed significantly elevated levels in patient plasma compared with healthy controls. Proteomics analyses of HL cell line supernatant allowed detection of new secreted proteins, which may add to our insights in the interaction between HRS cells and infiltrating lymphocytes and in some instances might serve as biomarkers.

Sample Stability and Protein Composition of Saliva: Implications for Its Use as a Diagnostic Fluid.

Saliva is an easy accessible plasma ultra-filtrate. Therefore, saliva can be an attractive alternative to blood for measurement of diagnostic protein markers. Our aim was to determine stability and protein composition of saliva. Protein stability at room temperature was examined by incubating fresh whole saliva with and without inhibitors of proteases and bacterial metabolism followed by Surface Enhanced Laser Desorption/Ionization (SELDI) analyses. Protein composition was determined by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) fractionation of saliva proteins followed by digestion of excised bands and identification by liquid chromatography tandem mass spectrometry (LC-MS/MS). Results show that rapid protein degradation occurs within 30 minutes after sample collection. Degradation starts already during collection. Protease inhibitors partly prevented degradation while inhibition of bacterial metabolism did not affect degradation. Three stable degradation products of 2937 Da, 3370 Da and 4132 Da were discovered which can be used as markers to monitor sample quality. Saliva proteome analyses revealed 218 proteins of which 84 can also be found in blood plasma. Based on a comparison with seven other proteomics studies on whole saliva we identified 83 new saliva proteins. We conclude that saliva is a promising diagnostic fluid when precautions are taken towards protein breakdown.

Analyses of intricate kinetics of the serum proteome during and after colon surgery by protein expression time series.

Monitoring changes in serum protein expression in response to acute events such as trauma, infection or drug intervention may reveal key proteins of great value in predicting recovery or treatment response. Concerted actions of many proteins are expected. Proteins sharing similar expression changes may function in the same physiological process. As a model we analyzed expression changes in serum of colon cancer patients, before, during, and after laparoscopic colon resection. Eight samples were taken from each of four patients before, during, and up to 5 days after surgery. Total serum and a low molecular weight fraction were analyzed by SELDI-TOF-MS. In total 146 masses were detected. A principal components analysis (PCA) illustrates the temporal variation in the postsurgery proteome. Time series for each mass could be clustered into four distinct groups based on similarity in expression pattern. Two masses of 11.4 and 11.6 kDa, part of a slow response cluster, were identified as forms of the acute phase protein serum amyloid A (SAA). Fourteen more proteins belong to this cluster and may also function in acute phase response. We present an approach to analyze temporal variation in the proteome. This approach may be useful to evaluate surgical, nutritional, and pharmacological interventions.

Differential analysis of protein expression of Bifidobacterium grown on different carbohydrates.

We observed recently that colonic fermentation of lactose might be a major factor in the pathophysiology of lactose intolerance. Proteomic techniques could be helpful in interpreting the metabolic pathways of lactose fermentation. The objective of this study was to explore proteomic methodologies for studying bacterial lactose metabolism that can be used to detect and identify proteins associated with the onset of intolerance symptoms. Differential expression of cytoplasmic proteins of Bifidobacterium animalis, Bifidobacterium breve and Bifidobacterium longum grown on different carbohydrates (lactose, glucose, galactose) was analyzed with surface-enhanced laser desorption ionization-time of flight (SELDI-TOF) MS and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). After fractionation by SDS-PAGE, differentially-expressed proteins were identified with LC-MS/MS. The three strains grown on the same carbohydrate or the same strain grown on glucose or lactose showed differences in SELDI-TOF MS protein profiles. Differences in protein expression were observed in B. breve grown on glucose, galactose or lactose as analyzed with SDS-PAGE. With LC-MS/MS, proteins from Bifidobacterium were identified, which included enzymes for metabolism of lactose, glucose and galactose. In conclusion, the applied techniques can discern differences in protein expression of bacteria metabolizing different carbohydrates. These techniques are promising in studying metabolism of lactose and other substrates in a complex bacterial ecosystem such as the colonic microbiota.

Fractional factorial design for optimization of the SELDI protocol for human adipose tissue culture media.

The early factors inducing insulin resistance are not known. Therefore, we are interested in studying the secretome of the human visceral adipose tissue as a potential source of unknown peptides and proteins inducing insulin resistance. Surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry is a high-throughput proteomics technology to generate peptide and protein profiles (MS spectra). To obtain good quality and reproducible data from SELDI-TOF, many factors in the sample pretreatment and SELDI protocol should be optimized. To identify the optimal combination of factors resulting in the best and the most reproducible spectra, we designed an experiment where factors were varied systematically according to a fractional factorial design. In this study, seven protein chip preparation protocol factors were tested in 32 experiments. The main effects of these factors and their interactions contributing to the best quality spectra were identified by ANOVA. To assess the reproducibility, in a subsequent experiment the eight protocols generating the highest quality spectra were applied to samples in quadruplicates on different chips. This approach resulted in the development of an improved chip protocol, yielding higher quality peaks and more reproducible spectra.

Characterization of the human visceral adipose tissue secretome.

Adipose tissue is an endocrine organ involved in storage and release of energy but also in regulation of energy metabolism in other organs via secretion of peptide and protein hormones (adipokines). Especially visceral adipose tissue has been implicated in the development of metabolic syndrome and type 2 diabetes. Factors secreted by the stromal-vascular fraction contribute to the secretome and modulate adipokine secretion by adipocytes. Therefore, we aimed at the characterization of the adipose tissue secretome rather than the adipocyte cell secretome. The presence of serum proteins and intracellular proteins from damaged cells, released during culture, may dramatically influence the dynamic range of the sample and thereby identification of secreted proteins. Part of the study was therefore dedicated to the influence of the culture setup on the quality of the final sample. Visceral adipose tissue was cultured in five experimental setups, and the quality of resulting samples was evaluated in terms of protein concentration and protein composition. The best setup involved one wash after the 1st h in culture followed by two or three additional washes within an 8-h period, starting after overnight culture. Thereafter tissue was maintained in culture for an additional 48-114 h to obtain the final sample. For the secretome experiment, explants were cultured in media containing L-[(13)C(6),(15)N(2)]lysine to validate the origin of the identified proteins (adipose tissue- or serum-derived). In total, 259 proteins were identified with > or =99% confidence. 108 proteins contained a secretion signal peptide of which 70 incorporated the label and were considered secreted by adipose tissue. These proteins were classified into five categories according to function. This is the first study on the (human) adipose tissue secretome. The results of this study contribute to a better understanding of the role of adipose tissue in whole body energy metabolism and related diseases.

Proteomics profiling of urine with surface enhanced laser desorption/ionization time of flight mass spectrometry.

BACKGROUND: Urine consists of a complex mixture of peptides and proteins and therefore is an interesting source of biomarkers. Because of its high throughput capacity SELDI-TOF-MS is a proteomics technology frequently used in biomarker studies. We compared the performance of seven SELDI protein chip types for profiling of urine using standard chip protocols. RESULTS: Performance was assessed by determining the number of detectable peaks and spot to spot variation for the seven array types and two different matrices: SPA and CHCA. A urine sample taken from one healthy volunteer was applied in eight-fold for each chip type/matrix combination. Data were analyzed for total number of detected peaks (S/N > 5). Spot to spot variation was determined by calculating the average CV of peak intensities. In addition, an inventory was made of detectable peaks with each chip and matrix type. Also the redundancy in peaks detected with the different chip/matrix combinations was determined. A total of 425 peaks (136 non-redundant peaks) could be detected when combining the data from the seven chip types and the two matrices. Most peaks were detected with the CM10 chip with CHCA (57 peaks). The Q10 with CHCA (51 peaks), SEND (48 peaks) and CM10 with SPA (48 peaks) also performed well. The CM10 chip with CHCA also has the best reproducibility with an average CV for peak intensity of 13%. CONCLUSION: The combination of SEND, CM10 with CHCA, CM10 with SPA, IMAC-Cu with SPA and H50 with CHCA provides the optimal information from the urine sample with good reproducibility. With this combination a total of 217 peaks (71 non-redundant peaks) can be detected with CV's ranging from 13 to 26%, depending on the chip and matrix type. Overall, CM10 with CHCA is the best performing chip type.

Peak quantification in surface-enhanced laser desorption/ionization by using mixture models.

Surface-enhanced laser desorption/ionization (SELDI) time of flight (TOF) is a mass spectrometry technology for measuring the composition of a sampled protein mixture. A mass spectrum contains peaks corresponding to proteins in the sample. The peak areas are proportional to the measured concentrations of the corresponding proteins. Quantifying peak areas is difficult for existing methods because peak shapes are not constant across a spectrum and because peaks often overlap. We present a new method for quantifying peak areas. Our method decomposes a spectrum into peaks and a baseline using so-called statistical finite mixture models. We illustrate our method in detail on 8 samples from culture media of adipose tissue and globally on 64 samples from serum to compare our method to the standard Ciphergen method. Both methods give similar estimates for singleton peaks, but not for overlapping peaks. The Ciphergen method overestimates the heights of such peaks while our method still gives appropriate estimates. Peak quantification is an important step in pre-processing SELDI-TOF data and improvements therein will pay off in the later biomarker discovery phase.