Expression profiling of proteins inL-threonine biosynthetic pathway ofEscherichia coli by using antibody microarray

We demonstrate the use of an antibody (Ab) microarray for a comparative expression profiling of proteins in an L-threonine biosynthetic pathway of Escherichia coli between a parental strain (W3110) and L-threonine overproducing mutant (TF5015). On the basis of a global comparative transcriptome analysis between the two strains, 28 analytical target proteins were selected and subjected to a production of polyclonal Abs against them. An Ab microarray was constructed by spotting a set of produced antibodies on a glass slide, and was employed for a comparative expression profiling of the proteins between the two strains by a two-color fluorescence assay method. The performance of the Ab microarray was evaluated with respect to cross-reactivity of the antibodies, dye-labeling efficiency, and the nature of antigenic proteins. Of these, the cross-reactivity of the used antibodies was found to mainly cause the deviation of the observed expression ratios from the expected ones. To offset the deviations, correction factors were derived from a statistical analysis and introduced. As a result, ten proteins were categorized to be up-regulated, while one was down-regulated in TF5015. Expression profiling of proteins using the Ab microarray was further verified by comparison with Western blotting and 2-DE.

Protein array staining methods for undefined protein content, manufacturing quality control, and performance validation

Methods to assess the quality and performance of protein microarrays fabricated from undefined protein content are required to elucidate slide-to-slide variability and interpolate resulting signal intensity values after an interaction assay. We therefore developed several simple total- and posttranslational modification-specific, on-chip staining methods to quantitatively assess the quality of gel element protein arrays manufactured with whole-cell lysate in vitro protein fractions derived from two-dimensional liquid-phase fractionation (PF2D) technology. A linear dynamic range of at least 3 logs was observed for protein stains and immobilized protein content, with a lower limit of detection at 8 pg of protein per gel element with Deep Purple protein stain and a field-portable microarray imager. Data demonstrate the successful isolation, separation, transfer, and immobilization of putative transmembrane proteins from Yersinia pestis KIM D27 with the combined PF2D and gel element array method. Internal bovine serum albumin standard curves provided a method to assess on-chip PF2D transfer and quantify total protein immobilized per gel element. The basic PF2D array fabrication and quality assurance/quality control methods described here therefore provide a standard operating procedure and basis for developing whole-proteome arrays for interrogating host-pathogen interactions, independent of sequenced genomes, affinity tags, or a priori knowledge of target cell composition.

Mass spectrometric profiling - a diagnostic tool in fish?

The development of rapid and sensitive diagnostic tools to assess the effect of stressors on organisms is a principal objective of environmental proteomics. This study is focused on evaluating the potential of using surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF MS) to assess stress in Atlantic salmon (Salmo salar). Plasma and mucus samples were taken from fish that had previously been maintained in a range of high density conditions, together with control fish maintained under low density conditions. Samples were collected during the post-density stress period for protein profile analysis. The mass spectra were analysed to evaluate reproducibility and to search for condition specific changes in protein expression. Multivariate analysis of the peak relative intensity data indicated a segregation of the data into three entities in accordance with the density level fish had been subjected to during the density stress period. This segregation was seen in both plasma and mucus data.

Measures of bioavailable serum sex hormone levels in aging Chinese by protein chip

The purpose of this study was to develop a protein chip technique based on receptor binding assays to measure bioavailable serum sex hormone levels (BSSHL). 224 aging healthy Chinese were investigated to get the referenced values of BSSHL for the first time. In the assays recombined sex hormone receptor proteins were jointed to polysaccharide coated slides to make protein chip, and the dose-dependence curves of sex hormone on chip were prepared. The data showed that this method had good precision (CV < 16%) and accuracy (Bias < 10%), and the sensitivity could reach 1 pmol/L. From the results, BSSHL of men and women declined with aging, but no significant differences were observed. The BSSHL of aging men were higher than those of women. The bioavailable serum androgen level of men was 52-112 pmol/L, women's was 3-70 pmol/L and the whole group was 41.9-81.4 pmol/L. The bioavailable serum estrogen level of men was 0.8-3.0 pmol/L, women's was 1.2-2.5 pmol/L and the whole group was 0.6-2.64 pmol/L. Based on the assays, BSSHL measurement by protein chip can meet the needs of epidemiological studies in terms of speed, accuracy and sample volume required, and was helpful in quantitative assessment of aging people's health.

Optical technologies for the read out and quality control of DNA and protein microarrays

Microarray formats have become an important tool for parallel (or multiplexed) monitoring of biomolecular interactions. Surface-immobilized probes like oligonucleotides, cDNA, proteins, or antibodies can be used for the screening of their complementary targets, covering different applications like gene or protein expression profiling, analysis of point mutations, or immunodiagnostics. Numerous reviews have appeared on this topic in recent years, documenting the intriguing progress of these miniaturized assay formats. Most of them highlight all aspects of microarray preparation, surface chemistry, and patterning, and try to give a systematic survey of the different kinds of applications of this new technique. This review places the emphasis on optical technologies for microarray analysis. As the fluorescent read out of microarrays is dominating the field, this topic will be the focus of the review. Basic principles of labeling and signal amplification techniques will be introduced. Recent developments in total internal reflection fluorescence, resonance energy transfer assays, and time-resolved imaging are addressed, as well as non-fluorescent imaging methods. Finally, some label-free detection modes are discussed, such as surface plasmon microscopy or ellipsometry, since these are particularly interesting for microarray development and quality control purposes.

Protein profiling as a diagnostic tool in clinical chemistry: a review

Serum protein profiling by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) appears to be an important diagnostic tool for a whole range of diseases. Sensitivities and specificities obtained with this new technology often seem superior to those obtained with current biomarkers. However, reproducibility and standardization are still problematic. The present review gives an overview of the diagnostic value of protein profiles obtained with SELDI in studies on prostate and ovarian cancer. To identify aspects important for protein profiling, we compare and discuss differences in pre- and post-analytical conditions presented in the literature supplemented with some of our own data. Further progress in protein profiling as a diagnostic tool requires a more comprehensive description of technical details in all future studies.

Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach

OBJECTIVE

To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology.

METHODS

A total of 103 serum samples from patients and healthy controls were analyzed. Thirty-four of the patients had a diagnosis of RA, based on the American College of Rheumatology criteria. The inflammation control group comprised 20 patients with psoriatic arthritis (PsA), 9 with asthma, and 10 with Crohn's disease. The noninflammation control group comprised 14 patients with knee osteoarthritis and 16 healthy control subjects. Serum protein profiles were obtained by SELDI-TOF-MS and compared in order to identify new biomarkers specific for RA. Data were analyzed by a machine learning algorithm called decision tree boosting, according to different preprocessing steps.

RESULTS

The most discriminative mass/charge (m/z) values serving as potential biomarkers for RA were identified on arrays for both patients with RA versus controls and patients with RA versus patients with PsA. From among several candidates, the following peaks were highlighted: m/z values of 2,924 (RA versus controls on H4 arrays), 10,832 and 11,632 (RA versus controls on CM10 arrays), 4,824 (RA versus PsA on H4 arrays), and 4,666 (RA versus PsA on CM10 arrays). Positive results of proteomic analysis were associated with positive results of the anti-cyclic citrullinated peptide test. Our observations suggested that the 10,832 peak could represent myeloid-related protein 8.

CONCLUSION

SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA.

Recent advances of protein microarrays

Technological innovations and novel applications have greatly advanced the field of protein microarrays. Over the past two years, different types of protein microarrays have been used for serum profiling, protein abundance determinations, and identification of proteins that bind DNA or small compounds. However, considerable development is still required to ensure common quality standards and to establish large content repertoires. Here, we summarize applications available to date and discuss recent technological achievements and efforts on standardization.

Development of an Internally Controlled Antibody Microarray

Antibody microarrays are a high throughput technology used to concurrently screen for protein expression. Most antibody arrays currently used are based on the ELISA sandwich approach that uses two antibodies to screen for the expression of a limited number of proteins. Also because antigen-antibody interactions are concentration-dependent, antibody microarrays need to normalize the amount of antibody that is used. In response to the limitations with the currently existing technology we have developed a single antibody-based microarray where the quantity of antibody spotted is used to standardize the antigen concentration. In addition, this new array utilizes an internally controlled system where one color represents the amount of antibody spotted, and the other color represents the amount of the antigen that is used to quantify the level of protein expression. When compared with median fluorescence intensity alone, normalization for antibody spot intensity decreased variability and lowered the limits of detection. This new antibody array was tested using standard cytokine proteins and also cell lysates obtained from mouse macrophages stimulated in vitro and evaluated for the expression of the cytokine proteins interleukin (IL)-1beta, IL-5, IL-6, and macrophage inflammatory proteins 1alpha and 1beta. The levels of protein expression seen with the antibody microarray was compared with that obtained with Western blot analysis, and the magnitude of protein expression observed was similar with both technologies with the antibody array actually showing a greater degree of sensitivity. In summary, we have developed a new type of antibody microarray to screen for protein expression that utilizes a single antibody and controls for the amount of antibody spotted. This type of array appears at least as sensitive as Western blot analysis, and the technology can be scaled up for high throughput screening for hundreds of proteins in complex biofluids such as blood.

Protein chip for detection of different HCV antibodies: preparation, quality control, and clinical evaluation

INTRODUCTION

As a contagious disease caused by hepatitis C virus (HCV) hepatitis C is a serious threat to human health. Therefore, the detection and verification of HCV infection is very important in the treatment of hepatitis C. This study investigated the preparation, quality control, and clinical evaluation of a protein chip capable of simultaneously detecting different HCV antibodies. The aim was to establish a convenient method for the detection of HCV.

METHOD

To prepare the protein chip, six antigens including five recombinant HCV antigens (chimeric, core, NS3, NS4, and NS5) and interleukin (IL)-1 were arrayed onto aldehyde-coated slides and blocked using 10% calf serum in phosphate buffered saline. After dilution with sample solution, the serum sample was added to a reaction well on the protein chip. After incubation for 30 minutes at 37 degrees C, fluorescence Cy3-labeled rabbit antihuman IgG was added and incubated again for 30 minutes at 37 degrees C, and then scanned. Positive or negative controls were established from serum samples with or without HCV infection. Clinical evaluation was done by detecting 490 serum samples using the protein chips and ELISA reagents, with 150 of the 490 serum samples confirmed by recombinant immunoblot assay (RIBA).

RESULTS

The protein chip for detection of five HCV antibodies was successfully prepared. Fifteen positive controls and 15 negative controls were established as standard samples for quality control. The quality control-passed protein chip was tested again using the standard of the National Institute for the Control of Pharmaceutical and Biological Products (NICPBP), and met the quality control criteria prescribed by the NICPBP. In the clinical evaluation with 490 samples, the coincidence rates between the protein-chip assay and ELISA were 97.4% for positive and 100% for negative results. Five inconsistent samples that were positive in ELISA, but non-positive (four samples) or negative (one) in the protein-chip assay, were confirmed by RIBA (gold standard) to be four non-positive and one negative. The results of 150 samples showed the coincidence rates between protein chip and RIBA were 98.15% for positive and 96.88% for single-segment positive.

CONCLUSION

The protein-chip assay has higher sensitivity and specificity than ELISA and has a high coincidence rate with RIBA. The protein chip, characterized by its easy operation and low economic cost, will be very useful for in vitro detection of HCV antibodies.

Microarray scanner calibration curves: characteristics and implications

Background

Microarray-based measurement of mRNA abundance assumes a linear relationship between the fluorescence intensity and the dye concentration. In reality, however, the calibration curve can be nonlinear.

Results

By scanning a microarray scanner calibration slide containing known concentrations of fluorescent dyes under 18 PMT gains, we were able to evaluate the differences in calibration characteristics of Cy5 and Cy3. First, the calibration curve for the same dye under the same PMT gain is nonlinear at both the high and low intensity ends. Second, the degree of nonlinearity of the calibration curve depends on the PMT gain. Third, the two PMTs (for Cy5 and Cy3) behave differently even under the same gain. Fourth, the background intensity for the Cy3 channel is higher than that for the Cy5 channel. The impact of such characteristics on the accuracy and reproducibility of measured mRNA abundance and the calculated ratios was demonstrated. Combined with simulation results, we provided explanations to the existence of ratio underestimation, intensity-dependence of ratio bias, and anti-correlation of ratios in dye-swap replicates. We further demonstrated that although Lowess normalization effectively eliminates the intensity-dependence of ratio bias, the systematic deviation from true ratios largely remained. A method of calculating ratios based on concentrations estimated from the calibration curves was proposed for correcting ratio bias.

Conclusion

It is preferable to scan microarray slides at fixed, optimal gain settings under which the linearity between concentration and intensity is maximized. Although normalization methods improve reproducibility of microarray measurements, they appear less effective in improving accuracy.

Reproducible clusters from microarray research: whither?

Motivation

In cluster analysis, the validity of specific solutions, algorithms, and procedures present significant challenges because there is no null hypothesis to test and no 'right answer'. It has been noted that a replicable classification is not necessarily a useful one, but a useful one that characterizes some aspect of the population must be replicable. By replicable we mean reproducible across multiple samplings from the same population. Methodologists have suggested that the validity of clustering methods should be based on classifications that yield reproducible findings beyond chance levels. We used this approach to determine the performance of commonly used clustering algorithms and the degree of replicability achieved using several microarray datasets.

Methods

We considered four commonly used iterative partitioning algorithms (Self Organizing Maps (SOM), K-means, Clutsering LARge Applications (CLARA), and Fuzzy C-means) and evaluated their performances on 37 microarray datasets, with sample sizes ranging from 12 to 172. We assessed reproducibility of the clustering algorithm by measuring the strength of relationship between clustering outputs of subsamples of 37 datasets. Cluster stability was quantified using Cramer's v² from a kXk table. Cramer's v² is equivalent to the squared canonical correlation coefficient between two sets of nominal variables. Potential scores range from 0 to 1, with 1 denoting perfect reproducibility.

Results

All four clustering routines show increased stability with larger sample sizes. K-means and SOM showed a gradual increase in stability with increasing sample size. CLARA and Fuzzy C-means, however, yielded low stability scores until sample sizes approached 30 and then gradually increased thereafter. Average stability never exceeded 0.55 for the four clustering routines, even at a sample size of 50. These findings suggest several plausible scenarios: (1) microarray datasets lack natural clustering structure thereby producing low stability scores on all four methods; (2) the algorithms studied do not produce reliable results and/or (3) sample sizes typically used in microarray research may be too small to support derivation of reliable clustering results. Further research should be directed towards evaluating stability performances of more clustering algorithms on more datasets specially having larger sample sizes with larger numbers of clusters considered.

Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS)

Background

Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis.

Results

The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra.

Conclusion

This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.

Cross-platform comparability of microarray technology: intra-platform consistency and appropriate data analysis procedures are essential

Background

The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630–631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676–5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology.

Results

We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall.

Conclusion

Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control.

Development of a sensitive, colorometric microarray assay for allergen-responsive human IgE

With the existence of several thousand unique human allergens, a multiplex format, such as protein microarrays, is an attractive option for allergy screening. To determine the feasibility and sensitivity of using an enzyme-based, colorimetric protein microarray assay, three common allergens (mold, dust-mite, grass) were arrayed and added sera assayed for responsive human IgE. Normal, low positive, and negative control samples were assayed to determine optimal reaction parameters. Sensitivity of the assay (in international units, IU) was determined by constructing a standard curve using World Health Organization (WHO) standards. The system described here can reliably detect allergen-specific IgE below 0.35 IU, the current WHO standard cutoff. By taking advantage of the sensitivity of enzyme-linked immunosorbent assays (ELISAs) and the multiplex format of microarrays, we have achieved a high throughput system, capable of screening patients for allergen-susceptibility with optimal sensitivity.

[Optimization of the conditions for protein chip preparation]

OBJECTIVE

To define the optimal conditions for preparing protein chips on aldehyde-coated slides.

METHODS

The proteins were diluted in PBS containing 40% glycerol and spotted on aldehyde-coated slides. After the spots were dried for 1 hour at room temperature, the slides were stored at 4 degrees Celsius;. Following block and rinse, the slides were used for immunoassay and the results detected with a scanner. Several key factors that might influence the results were tested, including the number of spots, concentration of protein in the spotting solution, time of immobilization and the blocking reagent.

RESULTS

Pre-spotting of 10 to 15 spots achieved good homogeneity of the subsequent spots on aldehyde-coated slides. The protein immobilized at 4 degrees Celsius; for 24 to 48 h showed higher fluorescence intensity and clearer images, and the slides blocked with 3% BSA produced the lowest background signal. The concentration of protein in the spotting solution significantly affected the fluorescence intensity.

CONCLUSION

To ensure good results in preparing protein chips on aldehyde slides, pre-spotting of 10-15 spots can be necessary followed by immobilization at 4 degrees Celsius; for 24-48 h and 3% BSA blocking.

Urine protein profiling with surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry

BACKGROUND

In the last few years there has been an increasing interest in exploring the human proteome. In particular, efforts have focused on developing strategies to generate reproducible protein maps of normal cells, tissues, and biologic fluids, from which studies can then compare protein expression between different groups (e.g., healthy individuals vs. those with a specific pathologic state).

METHODS

Various extrinsic factors (instrument settings, matrix composition, urine storage post void, freeze-thaw cycles) and intrinsic factors (blood in urine, urine dilution, first-void vs. midstream urine) were analyzed with respect to their impact on urine protein profiling using surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS).

RESULTS

Extrinsic factors that critically influenced reproducibility and peak detection of urine protein profiling were matrix composition and instrument settings, while freeze-thaw cycles had minimal impact. Midstream urines samples did not undergo changes in their protein profile when stored for three days at 4 degrees C. Intrinsic factors that influenced normal urine protein profiling were blood in the urine and urine dilution. Female first-void urine had a significantly different ratio of proteins present compared to a midstream urine sample. Limitations of the SELDI-TOF-MS technique included ion suppression and quantification of individual proteins when protein composition was complex.

CONCLUSION

SELDI-TOF-MS offers a unique platform for high throughput urine protein profiling; however, standardization of analysis conditions is critical, and both extrinsic and intrinsic factors must be taken into account for accurate data interpretation.

Are heterogenous results of EGFR immunoreactivity in renal cell carcinoma related to non-standardised criteria for staining evaluation?

AIMS

To assess whether heterogeneity of epidermal growth factor receptor (EGFR) immunoreactivity in renal cell carcinoma (RCC) is related to non-standardised criteria for staining evaluation.

METHODS

EGFR expression was investigated in 132 primary and 55 metastatic conventional RCCs using a tissue microarray technique.

RESULTS

Overall, membranous and/or cytoplasmic EGFR immunostaining was present in 123 of 132 (93%) primary and 49 of 53 (92%) metastatic RCCs, with extensive immunoreactivity (> 50% of tumour cells) in 110 of 132 (83%) primary tumours and 39 of 53 (73%) metastases. Cytoplasmic staining was associated with high tumour stage and high tumour grade. In addition, strong membranous staining (score 3+) prevailed in high grade RCCs. Cytoplasmic immunostaining was associated with an unfavourable prognosis, whereas overall (cytoplasmic and membranous) immunoreactivity and intensity of membranous staining were not.

CONCLUSIONS

Different methods of immunohistochemical evaluation led to different results, strengthening the need for standardisation, especially against a background of rapidly evolving EGFR targeted cancer treatment strategies.

Direct comparison of traditional ELISAs and membrane protein arrays for detection and quantification of human cytokines

Many labs wish to measure cytokines in an accurate, reproducible, and rapid manner. An antibody-based membrane array for measuring cytokines has been developed based on the same technology as the traditional ELISA. The aim of this study was to compare results obtained with the traditional ELISA method with those from the membrane array technology, a form of low-cost proteomics. Diluted human whole blood was stimulated with live bacteria (Escherichia coli, or Staphylococous aureus), or LPS and cytokines were measured both by ELISA and the membrane protein array. Of the 16 cytokines measured via ELISA, only IFN-gamma was below detection level. The other 15 cytokines were present in concentrations up to several thousand picograms/ml. Of the 20 cytokines measured via membrane protein array, only 3 could be detected (IL-6, IL-8 and MIP-1beta). Additionally, the membrane protein array did not detect TNF-alpha from the LPS-stimulated blood. These results indicate that the low-cost membrane protein array may lack sufficient sensitivity to adequately detect cytokines levels in complex biological fluids such as human plasma.

[Micro-array based technologies to study the proteome: technological progress and applications]

Since these twenty last years, there is an increasing interest for large-scale analysis of biological function. In the field of transcriptome, the emergence of microarray-based technologies and the design of DNA biochips allow high-throughput studies of RNA expression in cell and tissue at a given moment. In the field of proteome, methods of reference are still the 2D electrophoresis followed by analysis with mass spectrometry. Technological progress makes it possible to apply microarray methods to proteomics study : they are protein biochips or protein arrays. Expression analysis of proteins in a cell or a tissue in simultaneous and highly parallel way give further information for large-scale studies of signaling pathway. Numerous applications of protein microarray-based assays are described in basic biological research and in medical research to identify diagnostic biomarkers of inflammatory and cancerous pathologies and to find out news drugs and new therapeutic targets. This review summarizes concrete applications of microarray-based technology in the field of proteome, describes fundamental technical stages in protein array development and highlights critical points which will be useful to improve this emerging proteomic method.

[Small but high throughput: how "tissue-microarrays" became a favorite tool for pathologists and scientists]

Progress in the knowledge of molecular genetics and availability of high-throughput technologies offer the opportunity to identify new diagnostic and prognostic markers and new therapeutic targets in human cancer. The recently developed "tIssue microarrays" (TMA) technology allows parallel molecular profiling of clinical samples. Using this technique and immunohistochemistry (IHC), fluorescence in situ hybridisation (FISH), or RNA in situ hybridisation (ISH), the pathologist is now able to perform unprecedented large-scale analyses. The advantages are significant: large number of cases assessed simultaneously for numerous markers, processed in identical conditions, from reduced amount of archival tIssues, with an excellent correlation with standard methods, and a reduction in cost and time. This Article provides a short review of this technology, and points out several aspects of the TMA construction and its applications for clinical research.

Quality control and peak finding for proteomics data collected from nipple aspirate fluid by surface-enhanced laser desorption and ionization

BACKGROUND

Recently, researchers have been using mass spectroscopy to study cancer. For use of proteomics spectra in a clinical setting, stringent quality-control procedures will be needed.

METHODS

We pooled samples of nipple aspirate fluid from healthy breasts and breasts with cancer to prepare a control sample. Aliquots of the control sample were used on two spots on each of three IMAC ProteinChip arrays (Ciphergen Biosystems, Inc.) on 4 successive days to generate 24 SELDI spectra. In 36 subsequent experiments, the control sample was applied to two spots of each ProteinChip array, and the resulting spectra were analyzed to determine how closely they agreed with the original 24 spectra.

RESULTS

We describe novel algorithms that (a) locate peaks in unprocessed proteomics spectra and (b) iteratively combine peak detection with baseline correction. These algorithms detected approximately 200 peaks per spectrum, 68 of which are detected in all 24 original spectra. The peaks were highly correlated across samples. Moreover, we could explain 80% of the variance, using only six principal components. Using a criterion that rejects a chip if the Mahalanobis distance from both control spectra to the center of the six-dimensional principal component space exceeds the 95% confidence limit threshold, we rejected 5 of the 36 chips.

CONCLUSIONS

Mahalanobis distance in principal component space provides a method for assessing the reproducibility of proteomics spectra that is robust, effective, easily computed, and statistically sound.

ArrayTrack--supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research

The mapping of the human genome and the determination of corresponding gene functions, pathways, and biological mechanisms are driving the emergence of the new research fields of toxicogenomics and systems toxicology. Many technological advances such as microarrays are enabling this paradigm shift that indicates an unprecedented advancement in the methods of understanding the expression of toxicity at the molecular level. At the National Center for Toxicological Research (NCTR) of the U.S. Food and Drug Administration, core facilities for genomic, proteomic, and metabonomic technologies have been established that use standardized experimental procedures to support centerwide toxicogenomic research. Collectively, these facilities are continuously producing an unprecedented volume of data. NCTR plans to develop a toxicoinformatics integrated system (TIS) for the purpose of fully integrating genomic, proteomic, and metabonomic data with the data in public repositories as well as conventional (Italic)in vitro(/Italic) and (Italic)in vivo(/Italic) toxicology data. The TIS will enable data curation in accordance with standard ontology and provide or interface a rich collection of tools for data analysis and knowledge mining. In this article the design, practical issues, and functions of the TIS are discussed through presenting its prototype version, ArrayTrack, for the management and analysis of DNA microarray data. ArrayTrack is logically constructed of three linked components: a) a library (LIB) that mirrors critical data in public databases; b) a database (MicroarrayDB) that stores microarray experiment information that is Minimal Information About a Microarray Experiment (MIAME) compliant; and c) tools (TOOL) that operate on experimental and public data for knowledge discovery. Using ArrayTrack, we can select an analysis method from the TOOL and apply the method to selected microarray data stored in the MicroarrayDB; the analysis results can be linked directly to gene information in the LIB.

The UAB Proteomics Database

SUMMARY

The University of Alabama at Birmingham (UAB) Proteomics Database (UPD) (http://www.uab.edu/proteinmenu) was created to provide a repository for the storage and linkage of two-dimensional (2D) gel images and the associated information obtained through mass spectrometry analysis of the proteins excised from the 2D gels in a manner similar to the SWISS-2DPAGE database and the Stanford Microarray Database. This was accomplished through the development of a web interface, a relational database, image maps and hyperlinks stored in the database. In addition to the internally generated data, UPD provides links to the National Center for Biotechnology Information via accession number hyperlinks. UPD currently contains information on 44 individual proteins derived from four experiments conducted by four UAB faculty members. Images of the gels from which each of these proteins was isolated are accessed by hyperlinks embedded in the database.

AVAILABILITY

The UAB Proteomics Database can be accessed at http://www.uab.edu/proteinmenu.