Novel Hybrid Quadrupole-Multireflecting Time-of-Flight Mass Spectrometry System.

A novel mass spectrometry system is described here comprising a quadrupole-multireflecting time-of-flight design. The new multireflecting time-of-flight analyzer has an effective path length of 48 m and employs planar, gridless ion mirrors providing fourth-order energy focusing resulting in resolving power over 200 000 fwhm and sub-ppm mass accuracy. We show how these attributes are maintained with relatively fast acquisition speeds, setting the system apart from other high resolution mass spectrometers. We have integrated this new system into both liquid chromatography-mass spectrometry and mass spectrometry imaging workflows to demonstrate how the instrument characteristics are of benefit to these applications.

BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology.

Mass Spectrometry Imaging (MSI) holds significant promise in augmenting digital histopathologic analysis by generating highly robust big data about the metabolic, lipidomic and proteomic molecular content of the samples. In the process, a vast quantity of unrefined data, that can amount to several hundred gigabytes per tissue section, is produced. Managing, analysing and interpreting this data is a significant challenge and represents a major barrier to the translational application of MSI. Existing data analysis solutions for MSI rely on a set of heterogeneous bioinformatics packages that are not scalable for the reproducible processing of large-scale (hundreds to thousands) biological sample sets. Here, we present a computational platform (pyBASIS) capable of optimized and scalable processing of MSI data for improved information recovery and comparative analysis across tissue specimens using machine learning and related pattern recognition approaches. The proposed solution also provides a means of seamlessly integrating experimental laboratory data with downstream bioinformatics interpretation/analyses, resulting in a truly integrated system for translational MSI.

VHL-dependent regulation of a ß-dystroglycan glycoform and glycogene expression in renal cancer.

Identification of novel biomarkers and targets in renal cell carcinoma (RCC) remains a priority and one cellular compartment that is a rich potential source of such molecules is the plasma membrane. A shotgun proteomic analysis of cell surface proteins enriched by cell surface biotinylation and avidin affinity chromatography was explored using the UMRC2- renal cancer cell line, which lacks von Hippel-Lindau (VHL) tumour suppressor gene function, to determine whether proteins of interest could be detected. Of the 814 proteins identified ~22% were plasma membrane or membrane-associated, including several with known associations with cancer. This included ß-dystroglycan, the transmembrane subunit of the DAG1 gene product. VHL-dependent changes in the form of ß-dystroglycan were detected in UMRC2-/+VHL transfectants. Deglycosylation experiments showed that this was due to differential sialylation. Analysis of normal kidney cortex and conventional RCC tissues showed that a similar change also occurred in vivo. Investigation of the expression of genes involved in glycosylation in UMRC2-/+VHL cells using a focussed microarray highlighted a number of enzymes involved in sialylation; upregulation of bifunctional UDP-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase (GNE) was validated in UMRC2- cells compared with their +VHL counterparts and also found in conventional RCC tissue. These results implicate VHL in the regulation of glycosylation and raise interesting questions regarding the extent and importance of such changes in RCC.

Proteomic identification of differentially expressed plasma membrane proteins in renal cell carcinoma by stable isotope labelling of a von Hippel-Lindau transfectant cell line model.

The von Hippel-Lindau (VHL) tumour suppressor gene plays a central role in development of clear cell renal cell carcinoma (RCC). Using a cell line pair generated from the VHL-defective RCC cell line UMRC2 by transfection with vector control or VHL (-/+VHL) and stable isotope labelling with amino acids in cell culture (SILAC) followed by enrichment of plasma membrane proteins by cell surface biotinylation/avidin-affinity chromatography and analysis by GeLC-MS/MS, VHL-associated changes in plasma membrane proteins were analysed. Comparative analysis of -/+VHL cells identified 19 differentially expressed proteins which were confirmed by reciprocal SILAC labelling. These included several proteins previously reported to be VHL targets, such as transferrin receptor 1 and the alpha 3 and beta1 integrin subunits and novel findings including upregulation of CD166 and CD147 in VHL-defective cells. Western blotting confirmed these changes and also revealed VHL-dependent alterations in protein form for CD147 and CD166, which in the case of CD166 was shown to be due to differential glycosylation. Analysis of patient-matched normal and malignant renal tissues confirmed these differences were also present in vivo in a subset of clear cell RCCs. These results illustrate the potential of this approach for identifying VHL-dependent proteins that may be important in tumorigenesis.

Considerations for powering a clinical proteomics study: Normal variability in the human plasma proteome.

Proteomics is increasingly being applied to the human plasma proteome to identify biomarkers of disease for use in non-invasive assays. 2-D DIGE, simultaneously analysing thousands of protein spots quantitatively and maintaining protein isoform information, is one technique adopted. Sufficient numbers of samples must be analysed to achieve statistical power; however, few reported studies have analysed inherent variability in the plasma proteome by 2-D DIGE to allow power calculations. This study analysed plasma from 60 healthy volunteers by 2-D DIGE. Two samples were taken, 7 days apart, allowing estimation of sensitivity of detection of differences in spot intensity between two groups using either a longitudinal (paired) or non-paired design. Parameters for differences were: two-fold normalised volume change, α of 0.05 and power of 0.8. Using groups of 20 samples, alterations in 1742 spots could be detected with longitudinal sampling, and in 1206 between non-paired groups. Interbatch gel variability was small relative to the detection parameters, indicating robustness and reproducibility of 2-D DIGE for analysing large sample sets. In summary, 20 samples can allow detection of a large number of proteomic alterations by 2-D DIGE in human plasma, the sensitivity of detecting differences was greatly improved by longitudinal sampling and the technology was robust across batches.

Proteomic profiling identifies afamin as a potential biomarker for ovarian cancer.

PURPOSE: To discover and validate serum glycoprotein biomarkers in ovarian cancer using proteomic-based approaches. EXPERIMENTAL DESIGN: Serum samples from a "discovery set" of 20 patients with ovarian cancer or benign ovarian cysts or healthy volunteers were compared by fluorescence two-dimensional differential in-gel electrophoresis and parallel lectin-based two-dimensional profiling. Validation of a candidate biomarker was carried out with Western blotting and immunoassay (n = 424). RESULTS: Twenty-six proteins that changed significantly were identified by mass spectrometric sequencing. One of these, confirmed by Western blotting, was afamin, a vitamin E binding protein, with two isoforms decreasing in patients with ovarian cancer. Validation using cross-sectional samples from 303 individuals (healthy controls and patients with benign, borderline, or malignant ovarian conditions and other cancers) assayed by ELISA showed significantly decreased total afamin concentrations in patients with ovarian cancer compared with healthy controls (P = 0.002) and patients with benign disease (P = 0.046). However, the receiver operating characteristic areas for total afamin for the comparison of ovarian cancer with healthy controls or benign controls were only 0.67 and 0.60, respectively, with comparable figures for CA-125 being 0.92 and 0.88 although corresponding figures for a subgroup of samples analyzed by isoelectric focusing for afamin isoform 2 were 0.85 and 0.79. Analysis of a further 121 samples collected prospectively from 9 patients pretreatment through to relapse indicated complementarity of afamin with CA-125, including two cases in whom CA-125 was noninformative. CONCLUSIONS: Afamin shows potential complementarity with CA-125 in longitudinal monitoring of patients with ovarian cancer, justifying prospective larger-scale investigation. Changes in specific isoforms may provide further information.

Statistically integrated metabonomic-proteomic studies on a human prostate cancer xenograft model in mice.

A novel statistically integrated proteometabonomic method has been developed and applied to a human tumor xenograft mouse model of prostate cancer. Parallel 2D-DIGE proteomic and 1H NMR metabolic profile data were collected on blood plasma from mice implanted with a prostate cancer (PC-3) xenograft and from matched control animals. To interpret the xenograft-induced differences in plasma profiles, multivariate statistical algorithms including orthogonal projection to latent structure (OPLS) were applied to generate models characterizing the disease profile. Two approaches to integrating metabonomic data matrices are presented based on OPLS algorithms to provide a framework for generating models relating to the specific and common sources of variation in the metabolite concentrations and protein abundances that can be directly related to the disease model. Multiple correlations between metabolites and proteins were found, including associations between serotransferrin precursor and both tyrosine and 3-D-hydroxybutyrate. Additionally, a correlation between decreased concentration of tyrosine and increased presence of gelsolin was also observed. This approach can provide enhanced recovery of combination candidate biomarkers across multi-omic platforms, thus, enhancing understanding of in vivo model systems studied by multiple omic technologies.

Systems toxicology: integrated genomic, proteomic and metabonomic analysis of methapyrilene induced hepatotoxicity in the rat.

Administration of high doses of the histamine antagonist methapyrilene to rats causes periportal liver necrosis. The mechanism of toxicity is ill-defined and here we have utilized an integrated systems approach to understanding the toxic mechanisms by combining proteomics, metabonomics by 1H NMR spectroscopy and genomics by microarray gene expression profiling. Male rats were dosed with methapyrilene for 3 days at 150 mg/kg/day, which was sufficient to induce liver necrosis, or a subtoxic dose of 50 mg/kg/day. Urine was collected over 24 h each day, while blood and liver tissues were obtained at 2 h after the final dose. The resulting data further define the changes that occur in signal transduction and metabolic pathways during methapyrilene hepatotoxicity, revealing modification of expression levels of genes and proteins associated with oxidative stress and a change in energy usage that is reflected in both gene/protein expression patterns and metabolites. The difficulties of combining and interpreting multiomic data are considered.

Prostatic tissue protein alterations due to delayed time to freezing.

Clinical studies often produce fresh tissue samples, which ideally should be immediately snap frozen for storage and subsequent analysis. However, this is often not practically possible, and there is inevitably a time period during which the sample is stored on ice. The delay in freezing may allow endogenous degradation of proteins to occur, affecting 2-D gel protein profiles. This study aims to investigate the type and extent of this degradation by examining how the time-to-freezing delay alters prostatic tissue protein profile. The prostate carcinoma-3 cell line (PC-3), prostate cancer xenografts and canine prostate were used with fluorescence 2-D DIGE to assess protein degradation. It was found that 30-min processing time had minimal effects on the protein profile. Longer delays had little visible effect, but subtle alterations in protein profile began to accumulate as time increased. These data support the practice of completing tissue processing as rapidly as possible, and indicate that short processing times do not notably perturb the 2-D gel spot pattern from prostatic tissue.

Development of a high-throughput method for preparing human urine for two-dimensional electrophoresis.

There is an increasing interest in analysing the human urinary proteome in the search for biomarkers. However, despite the ease of its collection, urine is a difficult fluid to analyse by two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) because of its dilute protein content and high salt levels. Here, we describe a method for high-throughput processing of urine for 2-D PAGE. Urine is filtered and applied to solid phase extraction columns. After washing, the urinary proteins are eluted and freeze dried. The lyophilised powder can then be resuspended in an appropriate buffer for downstream proteomic analysis.

Comparative proteomics of primitive hematopoietic cell populations reveals differences in expression of proteins regulating motility.

Lineage-marker depleted (Lin(-)) murine bone marrow cells expressing stem cell antigen 1 (Sca-1) were sorted on the basis of stem cell factor receptor (c-kit) expression to obtain Lin(-)Sca(+)Kit(+) or Lin(-)Sca(+)Kit(-) cells. Lin(-)Sca(+)Kit(-) cells have a markedly greater chemotactic response to stromal derived factor-1 (SDF-1). Using a novel fluorescent stain, we show that both populations generate similar levels of a key messenger, phosphatidylinositol 3,4,5 trisphosphate (PIP(3)), in response to SDF-1. Differences in motile behavior may therefore lie downstream of phosphatidylinositol 3-kinase (PI3-kinase) activation at the level of cytoskeleton regulation. The 2 cell populations were compared using 2-dimensional difference gel electrophoresis (2D-DIGE), with a maleimide CyDye fluorescent protein labeling technique that has enhanced sensitivity for low abundance samples. Comparative proteomic analysis of Cy3- and Cy5-labeled protein samples allows relative quantification of protein spots present in both cell populations; of these, 73% were common. Key protein differences were adseverin and gelsolin, actin micro-filament splicing proteins, regulated by Rac, downstream of PI3-kinase activation. Adseverin was shown to be acetylated, a novel modification for this protein. Differences in major regulators of cell shape and motility between the 2 populations can explain the differential response to SDF-1.

Evaluation of saturation labelling two-dimensional difference gel electrophoresis fluorescent dyes.

Two-dimensional difference gel electrophoresis (2-D DIGE) enables an increased confidence in detection of protein differences. However, due to the nature of the minimal labelling where only approximately 5% of a given protein is labelled, spots cannot be directly excised for mass spectrometry (MS) analysis and detection sensitivity could be further enhanced. Amersham Biosciences have developed a second set of CyDye DIGE Cy 3 and Cy5 dyes, which aim to overcome these limitations through saturation-labelling of cysteine residues. The dyes were evaluated in relation to their sensitivity and dynamic range, their useability as multiplexing reagents and the possibility of direct spot picking from saturation-labelled gels for MS analysis. The saturation-labelling dyes were superior in sensitivity to their minimal-labelling counterparts, silver stain and Sypro Ruby, however, the resulting 2-D spot pattern was significantly altered from that of unlabelled or minimal-labelled protein. The dyes were found to be useful as multiplexing reagents although preferential labelling of proteins with one dye over another was observed but was controlled for through experimental design. Protein identities were successfully obtained from material directly excised from saturation-labelled gels eliminating the need for post-stained preparative gels.

Using statistical image models for objective evaluation of spot detection in two-dimensional gels.

Protein spot detection is central to the analysis of two-dimensional electrophoresis gel images. There are many commercially available packages, each implementing a protein spot detection algorithm. Despite this, there have been relatively few studies comparing the performance characteristics of the different packages. This is in part due to the fact that different packages employ different sets of user-adjustable parameters. It is also partly due to the fact that the images are complex. To carry out an evaluation, "ground truth" data specifying spot position, shape and intensities needs to be defined subjectively on selected test images. We address this problem by proposing a method of evaluation using synthetic images with unambiguous interpretation. The characteristics of the spots in the synthetic images are determined from statistical models of the shape, intensity, size, spread and location of real spot data. The distribution of parameters is described using a Gaussian mixture model obtained from training images. The synthetic images allow us to investigate the effects of individual image properties, such as signal-to-noise ratios and degree of spot overlap, by measuring quantifiable outcomes, e.g. accuracy of spot position, false positive and false negative detection. We illustrate the approach by carrying out quantitative evaluations of spot detection on a number of widely used analysis packages.

Statistical models of shape for the analysis of protein spots in two-dimensional electrophoresis gel images.

In image analysis of two-dimensional electrophoresis gels, individual spots need to be identified and quantified. Two classes of algorithms are commonly applied to this task. Parametric methods rely on a model, making strong assumptions about spot appearance, but are often insufficiently flexible to adequately represent all spots that may be present in a gel. Nonparametric methods make no assumptions about spot appearance and consequently impose few constraints on spot detection, allowing more flexibility but reducing robustness when image data is complex. We describe a parametric representation of spot shape that is both general enough to represent unusual spots, and specific enough to introduce constraints on the interpretation of complex images. Our method uses a model of shape based on the statistics of an annotated training set. The model allows new spot shapes, belonging to the same statistical distribution as the training set, to be generated. To represent spot appearance we use the statistically derived shape convolved with a Gaussian kernel, simulating the diffusion process in spot formation. We show that the statistical model of spot appearance and shape is able to fit to image data more closely than the commonly used spot parameterizations based solely on Gaussian and diffusion models. We show that improvements in model fitting are gained without degrading the specificity of the representation.

Cell culture model for acetaminophen-induced hepatocyte death in vivo.

Overdose of the popular, and relatively safe, analgesic acetaminophen (N-acetyl-p-aminophenol, APAP, paracetamol) can produce a fatal centrilobular liver injury. APAP-induced cell death was investigated in a differentiated, transforming growth factor alpha (TGFalpha)-overexpressing, hepatocyte cell line and found to occur at concentrations, and over time frames, relevant to clinical overdose situations. Coordinated multiorganellar collapse was evident during APAP-induced cytotoxicity with widespread, yet selective, protein degradation events in vitro. Cellular proteasomal activity was inhibited with APAP treatment but not with the comparatively nonhepatotoxic APAP regioisomer, N-acetyl-m-aminophenol (AMAP). Low concentrations of the proteasome-directed inhibitor MG132 (N-carbobenzoxyl-Leu-Leu-Leucinal) increased chromatin condensation and cellular stress responses preferentially in AMAP-treated cultures, suggesting a contribution of the proteasome in APAP- but not AMAP-mediated cell death. APAP-specific alterations to mitochondria were observed morphologically with evidence of mitochondrial proliferation in vitro. Biochemical alterations to cellular proteolytic events were also found in vivo, including APAP- or AMAP-mediated inhibition of caspase-3 processing. These results indicate that, although retaining some attributes of apoptosis, both APAP- and AMAP-mediated cell death have additional distinctive features consistent with longer term necrosis.

Genomics and proteomics analysis of acetaminophen toxicity in mouse liver.

Overdose of acetaminophen (APAP) causes severe centrilobular hepatic necrosis in humans and experimental animals. Here, to explore its mechanism, we administered APAP at subtoxic (150 mg/kg ip) and toxic (500 mg/kg ip) doses to overnight fasted mice. Animals were sacrificed at different time points from 15 min to 4 h postinjection. We assessed liver toxicity by plasma ALT activity and by electron microscopy. Using nylon filter arrays and RTQPCR, we performed genomics analysis in liver. We ran proteomics on liver mitochondrial subfractions using the newly developed quantitative fluorescent 2D-DIGE method (Amersham Pharmacia Biotech UK Limited). As soon as 15 min postinjection, centrilobular hepatocyte mitochondria were already slightly enlarged and GSH total content dropped by a third at top dose. GM-CSF mRNA, which is a granulocyte specific gene likely coming from resident Kupffer cells, was also induced to its maximum of 3-fold at both doses. Chaperone proteins Hsp10 and Hsp60 were readily decreased by half in mitochondria at both doses, most likely by leaking into cytoplasm. Although APAP is known as an apoptotic trigger, no apoptosis was observed at any time point. Most of the protein changes in mitochondria were present at 15 min postinjection, thus preceding most of the gene regulations. The decrease of ATP synthase subunits and beta-oxidation pathway proteins indicated a loss of energy production. As the morphology of mitochondria was also affected very early at top dose, we concluded that APAP toxicity was a direct action of its known reactive metabolite NAPQI, rather than a consequence of gene regulation. However, the latter will either worsen the toxicity or lead toward cell recovery depending on the cellular damage level.