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PubMedDate not supplied

Analysis of several fluorescent detector molecules for protein microarray use.

The utility of several streptavidin-linked fluorescent detector molecules was evaluated on two protein microarray platforms. Tested detector molecules included: Alexa Fluor 546; R-phycoerythrin (RPE), orange fluospheres; Cy3-containing liposomes (Large Unilamellar Vesicles, LUV) labelled with Cy3; and an RPE-antibody complex. The two array architectures tested consisted of an array of murine Fc-biotin and an array of murine IgG (the murine IgG array was probed with a biotinylated rabbit anti-murine IgG). These platforms allowed for the direct comparison of detector utility by detector recognition of array-bound biotin. All of the fluorescent detectors examined demonstrated utility on each of the array platforms. For the Fc-biotin array, detector signal intensity (background adjusted) was as follows: RPE-antibody complex > fluospheres > RPE > liposomes > Alexa 546: for the IgG array: RPE/antibody complex > RPE > fluospheres > Alexa546 > liposomes. The RPE-antibody complex fluoresced 67% and 150% more intensely than the next closest detector molecule for the Fc-biotin and the murine IgG arrays, respectively. A marked increase in background fluorescence (as compared to RPE alone) did not accompany the increase in signal intensity gained through RPE-antibody complex use (a true increase in signal:noise ratio). These results suggest that the RPE-antibody complex is superior to other molecules for fluorescent detection of analytes on protein microarrays.

Animals↗
PubMed2003

Potential for proteomic profiling of Helicobacter pylori and other Helicobacter spp. using a ProteinChip array.

The Helicobacter genus is associated with a wide spectrum of pathologies in the gastrointestinal tract. However, in contrast to Helicobacter pylori, few data are available regarding proteomic characteristics of enterohepatic helicobacters. Proteomic analysis of this genus has predominantly utilised two-dimensional gel electrophoresis methodology. In the present study we applied an innovative technique using ProteinChip arrays coupled with surface-enhanced laser desorption/ionisation time of flight mass spectroscopy to accurately assess the M(r) of proteins for comparative proteomic profiling. We analysed binding of outer membrane fractions to a weak cation exchange array for strains of H. pylori from culture collections and compared these profiles to fresh clinical isolates. In addition, we analysed profiles from Helicobacter pullorum, Helicobacter bilis and 'Helicobacter sp. flexispira'. The system proved rapid, accurate and reproducible. Distinct specific profiles for all the strains studied were identified. However, strains from culture collections that have undergone numerous subcultures had almost identical profiles. In contrast, profiles from fresh clinical isolates were markedly different. Moreover, certain features of the profiles from the enterohepatic species were conserved.

Animals↗
PubMedDate not supplied

Elevated HGF levels in sera from breast cancer patients detected using a protein microarray ELISA.

We developed an ELISA in high-density microarray format to detect hepatocyte growth factor (HGF) in human serum. The microassay can detect HGF at sub-pg/mL concentrations in sample volumes of 100 microL or less. The microassay is also quantitative and was used to detect elevated HGF levels in sera from recurrent breast cancer patients. The microarray format provides the potential for high-throughput quantitation of multiple biomarkers in parallel, as demonstrated with a multiplex analysis of five biomarker proteins.

Biomarkers, Tumor↗
PubMed2002

Combinatorial use of mRNA and two-dimensional electrophoresis expression data to choose relevant features for mass spectrometric identification.

It is only recently that quantitative studies of differential proteome analysis (DPA) have become possible. In this paper the issues involved in quantitative DPA are discussed and novel tools to select features for identification by mass spectrometry (MS) are described. The problem of comparing two sets of gels on a global level is explored as well as how to find specific protein features that differentiate two sets of two-dimensional electrophoresis gels. The concept of a 'virtual' gel, derived from gene expression data, is introduced. The virtual gel enables the co-analysis of data from gene and protein expression. We discuss the value of such an approach, and consider what new information can be gained by using gene and protein expression together. These tools are illustrated by analysis of data from tandem gene and protein expression experiments. Features that are highlighted by the above methods are putative candidates for MS identification. Tools are described that integrate the process of feature selection, cutting, and MS analysis.

Breast↗
PubMed2003

Quantitative detection of protein arrays.

We introduce a quantitative method that utilizes scanning electron microscopy for the analysis of protein chips (SEMPC). SEMPC is based upon counting target-coated gold particles interacting specifically with ligands or proteins arrayed on a derivative microscope glass slide by utilizing backscattering electron detection. As model systems, we quantified the interactions of biotin and streptavidin and of an antibody with its cognate hapten. Our method gives quantitative molecule-counting capabilities with an excellent signal-to-noise ratio and demonstrates a broad dynamic range while retaining easy sample preparation and realistic automation capability. Increased sensitivity and dynamic range are achieved in comparison to currently used array detection methods such as fluorescence, with no signal bleaching, affording high reproducibility and compatibility with miniaturization. Thus, our approach facilitates the determination of the absolute number of molecules bound to the chip rather than their relative amounts, as well as the use of smaller samples.

Antibodies↗
PubMed2002

Improved chip design for integrated solid-phase microextraction in on-line proteomic sample preparation.

A recently introduced silicon microextraction chip (SMEC), used for on-line proteomic sample preparation, has proved to facilitate the process of protein identification by sample clean up and enrichment of peptides. It is demonstrated that a novel grid-SMEC design improves the operating characteristics for solid-phase microextraction, by reducing dispersion effects and thereby improving the sample preparation conditions. The structures investigated in this paper are treated both numerically and experimentally. The numerical approach is based on finite element analysis of the microfluidic flow in the microchip. The analysis is accomplished by use of the computational fluid dynamics-module FLOTRAN in the ANSYS software package. The modeling and analysis of the previously reported weir-SMEC design indicates some severe drawbacks, that can be reduced by changing the microextraction chip geometry to the grid-SMEC design. The overall analytical performance was thereby improved and also verified by experimental work. Matrix-assisted laser desorption/ionization mass spectra of model peptides extracted from both the weir-SMEC and the new grid-SMEC support the numerical analysis results. Further use of numerical modeling and analysis of the SMEC structures is also discussed and suggested in this work.

Miniaturization↗
PubMed2003

Improved net protein balance, lean mass, and gene expression changes with oxandrolone treatment in the severely burned.

OBJECTIVE: To determine the effects of the anabolic agent oxandrolone on muscle protein and gene expression in severely burned children. SUMMARY BACKGROUND DATA: The authors previously showed that oxandrolone increased net muscle protein synthesis in emaciated burned patients receiving delayed treatment for severe burns. They hypothesized that similar effects would be seen in those treated early after burn. METHODS: Thirty-two severely burned children were enrolled in a prospective randomized trial. Subjects underwent studies to assess leg protein net balance 5 days after the first excision and grafting procedure. Immediately after these studies, treatment with placebo (n = 18) or 0.1 mg/kg oxandrolone (n = 14) twice a day was started. One week after this, another net balance study was performed in each subject. Body weights and total body potassium counting were used to determine body compositional changes. Muscle biopsies were taken 1 week after treatment in oxandrolone subjects to examine gene expression changes with gene array (12,600 genes). RESULTS: Protein net balance did not change in the placebo group, while oxandrolone-treated subjects had a significant improvement. Body weights and fat free mass significantly decreased in the placebo group, while no changes were found in the oxandrolone-treated subjects. Expression changes were seen in 14 genes in the oxandrolone group compared to placebo. Some of these included myosin light chain (+2.7-fold change), tubulin (+2.3), calmodulin (-2.3), and protein phosphatase I inhibitor (-2.8). CONCLUSIONS: Oxandrolone improves protein net balance and lean mass in the severely burned. These changes are associated with increased gene expression for functional muscle proteins.

Amino Acids↗
PubMed2000

van't Hoff enthalpies without baselines.

Analysis of thermal melting curves represents one important approach for evaluating protein stability and the consequences of amino acid substitution on protein structure. By use of the van't Hoff relationship, the differential melting curve can be robustly fit to only three parameters, two of which are the underlying physical constants of melting temperature (Tm) and van't Hoff enthalpy (deltaHvH). Calculated Tm and deltaHvH values are insensitive to the choice of pre- and post-transition baselines. Consequently, the method accurately computes Tm and deltaHvH for extremely truncated data sets, in the complete absence of baseline information, and for proteins with low melting temperatures, where the traditional direct approach routinely fails. Moreover, agreement between deltaHvH values obtained using points derived from pre- vs. post-transition data provide an independent method for detecting some classes of non-two-state transitions. Finally, fitting of the differential denaturation curve should prove useful for analysis of abbreviated data sets obtained from high throughput array analysis of protein stability.

Cytochrome c Group↗
PubMed2003

Profiling the progression of cancer: separation of microsomal proteins in MCF10 breast epithelial cell lines using nonporous chromatophoresis.

The heterogeneity of cellular protein expression has stimulated development of separations targeting smaller groups of related proteins rather than entire proteomes. The following work describes the development of a technique for the characterization of membrane subproteomes from five different breast epithelial cell lines. Intact membrane proteins are separated by hydrophobicity in the first dimension using nonporous reversed-phase high-performance liquid chromatography (RP-HPLC) to generate unique chromatographic profiles. Fractions of eluent are further separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to create distinct banding patterns. This hybrid liquid phase/gel phase method circumvents issues of membrane protein precipitation and provides a simple strategy aimed at isolating and characterizing a traditionally underrepresented protein class. Membrane protein profiles are created that discriminate between microsomal fractions of breast epithelial cells in different stages of neoplastic progression. Proteins are subsequently identified using matrix-assisted laser desorption/ionization - mass spectrometry (MALDI-MS) mass fingerprinting and MALDI-quadrupole time of flight - tandem mass spectrometry (QTOF-MS/MS) peptide sequencing. Furthermore, as this strategy preserves intact protein structure, further characterization can be performed on proteins producing mass fingerprint spectra and fragmentation spectra that did not result in database protein identifications. The coupling of nonporous RP-HPLC with SDS-PAGE provides a useful alternative to two-dimensional PAGE (2-D-PAGE) for membrane protein analysis.

Breast↗
PubMed2003

Protein microarrays: meeting analytical challenges for clinical applications.

Protein microarrays, one emerging class of proteomic technologies, have broad applications for discovery and quantitative analysis. A rapidly expanding use of this technology is the acquisition of information about the posttranslational modifications of proteins reflecting the activity state of signal pathways and networks, and is now employed for the analysis of biopsy samples in clinical trial research.

Animals↗
PubMed2002

Global proteome analysis of a human gastric carcinoma.

An approach that combines analysis of global protein digests (GPDs) of various subcellular fractions with a novel chromatographic-based method to map protein expression profiles is described. The KATO III gastric carcinoma cell line was fractionated into membrane and cytosol fractions. Each subcellular fraction was digested with trypsin to yield complex mixtures of global protein tags (GPTs). These mixtures were fractionated by two dimensions of chromatography, and GPTs were sequenced by microcapillary liquid chromatography-tandem mass spectrometry (LC-MS/MS), using two further complementary dimensions of chromatography. Additionally, a novel method of protein expression profiling was used to map the KATO III human gastric carcinoma cell line. This method uses the cells' natural proteolytic processes to derive in vivo peptide tags that represent proteins of every functional class and from all subcellular compartments. In one example, expressed protein tags (EPTs) are naturally displayed on the surface of cells by multiligand receptors. Isolation and sequence identification of EPTs is an efficient approach for protein profiling that is complementary to GPT analysis. The EPT approach also provides a further unique subcellular fraction of the biological starting material. Isolation of the multiligand receptors was by immunoaffinity chromatography (IAC). In the current study, five individual peptide maps (two EPTs and three GPTs) of the KATO III cell line were fractionated by multimodal chromatography, and sequenced by on-line multimodal microcapillary LC-MS/MS. This analysis led to the identification of 4291 individual peptide sequences, which defined 1966 unique proteins expressed by this human carcinoma cell line.

Chromatography, Affinity↗
PubMed2003

Protein profiling of complete mole and normal placenta using ProteinChip analysis on laser capture microdissected cells.

INTRODUCTION: Surface-enhanced laser desorption/ionization mass spectrometry (SELDI-MS) is a novel method for biomarker discovery that can provide a rapid protein expression profile from a variety of biological samples. Since SELDI-MS requires a small amount of biological material, this technique is ideal for analyzing proteins isolated from microdissected tissue samples. The current study was undertaken to investigate potential differences in protein expression between normal and molar trophoblast procured by laser capture microdissection (LCM) utilizing SELDI ProteinChip array technology. Further knowledge of protein expression in complete mole may advance our understanding of the pathogenesis of gestational trophoblastic diseases. MATERIALS AND METHODS: Laser capture microdissected trophoblast cells from nine fresh complete moles were analyzed and compared to the trophoblast cells from 10 fresh normal placentas of comparable gestational age, using SELDI ProteinChip to identify potential differences in protein expression. RESULTS: Three metal binding polypeptides were identified with the estimated molecular weights of 11.3, 13.8, and 14.0 kDa, which appeared in significantly lower levels in complete mole as compared to normal trophoblast cells (P < 0.001, P < 0.03, and P < 0.01). DISCUSSION: While further characterization of these protein peaks is important and necessary, our current work clearly demonstrates that the combined technology of SELDI and LCM is effective in distinguishing protein expression between normal placenta and complete mole. Further knowledge of protein expression in complete mole may advance our understanding of molecular mechanisms and improve management in gestational trophoblastic diseases.

Dissection↗
PubMed2003

High affinity capture surface for matrix-assisted laser desorption/ionisation compatible protein microarrays.

A surface for the capture of biotin-tagged proteins on matrix-assisted laser desorption/ionisation (MALDI) targets has been investigated. Binding of a poly-L-lysine poly(ethylene glycol)-biotin polymer to glass and gold surfaces has been demonstrated using dual wavelength interferometry. Biotinylated proteins were captured onto this surface using tetrameric neutravidin as a multivalent bridging molecule. Biotin tagging of proteins was achieved by chemical biotinylation or by expressing a protein with a biotinylation consensus sequence in E. coli. The specificity of the surface for biotin-tagged proteins allowed the purification of biotin-tagged glutathione-S-transferase from a bacterial lysate directly onto a MALDI target. Subsequently, the protein was digested on the MALDI target and a protein fingerprint analysis confirmed its presence directly, but no E. coli proteins were detected. Therefore, we conclude that this surface is highly specific for the capture of biotin-labelled proteins and has low non-specific binding properties for non-biotinylated proteins. Furthermore, protein-protein interactions using biotinylated lectins were investigated, and the selective capture of the glycoprotein fetuin with wheat germ agglutinin was demonstrated. Also, immobilised Arachis hypogea agglutinin recognised a minor asialo component of this glycoprotein on the array. The high affinity immobilisation of proteins onto this surface allowed effective desalting procedures to be used which improved the desorption of high molecular weight proteins. Another aspect of this surface is that a highly ordered coupling of the analyte can be achieved which eliminates the search for the sweet spot and allows the creation of densely packed protein microarrays for use in mass spectrometry.

Arachis↗
PubMedDate not supplied

Bioinformatics and genomic medicine.

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational science. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolution in both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high-throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever, in much the same way that biochemistry did a generation ago. This paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine-learning algorithms are discussed. Use of integrative biochip informatics technologies, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and the integrated management of biomolecular databases, are also discussed.

Computational Biology↗
PubMed2003

Clinical applications of proteomics.

Proteomics, the systematic evaluation of changes in the protein constituency of a cell, is more than just the generation of lists of proteins that increase or decrease in expression as a cause or consequence of disease. The ultimate goal is to characterize the information flow through protein pathways that interconnect the extracellular microenvironment with the control of gene transcription. The nature of this information can be a cause or a consequence of disease processes. Clinical applications of proteomics involve the use of proteomic technologies at the bedside. The analysis of human cancer as a model for how proteomics can have an impact at the bedside is now employing several new proteomic technologies that are being developed for early detection, therapeutic targeting and finally, patient-tailored therapy.

Gene Expression Profiling↗
PubMed2003

Cancer diagnosis using proteomic patterns.

The advent of proteomics has brought with it the hope of discovering novel biomarkers that can be used to diagnose diseases, predict susceptibility and monitor progression. Much of this effort has focused upon the mass spectral identification of the thousands of proteins that populate complex biosystems such as serum and tissues. A revolutionary approach in proteomic pattern analysis has emerged as an effective method for the early diagnosis of diseases such as ovarian cancer. Proteomic pattern analysis relies on the pattern of proteins observed and does not rely on the identification of a traceable biomarker. Hundreds of clinical samples per day can be analyzed utilizing this technology, which has the potential to be a novel, highly sensitive diagnostic tool for the early detection of cancer.

Biomarkers, Tumor↗
PubMed2003

Identification and validation of a potential lung cancer serum biomarker detected by matrix-assisted laser desorption/ionization-time of flight spectra analysis.

Many abnormalities detected in the thorax by routine conventional imaging studies are benign, yet all require further evaluation because of the concern for cancer. To address this deficiency and develop a serum biomarker for lung cancer, we designed a matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) based platform to display the proteins present in the serum of patients with or without lung cancer, and then challenged the scientific community to analyze these data with the aim of determining specific ion signal differences among the resulting spectra. The most statistically significant ion peak identified by the various analysis algorithms that differentiated the serum of patients with lung cancer from the serum of individuals without lung cancer was found at m/z 11,702. We identified the protein responsible for this ion peak as serum amyloid A (SAA; M(r) = 11,682.7) by partial purification followed by in-gel digestion and peptide mapping. By enzyme-linked immunosorbent assay, we showed SAA to be present at 286 ng/mL in the serum of cancer patients vs. 34.1 ng/mL in the serum of individuals without cancer. These data suggest that the combination of MALDI-TOF MS and computer analysis can be a powerful tool in the search for serum biomarkers of lung cancer and other diseases.

Adenocarcinoma↗