Two-dimensional database of a Burkitt lymphoma cell line (DG 75) proteins: protein pattern changes following treatment with 5'-azycytidine

Proteomic analysis of the soil filamentous fungus Aspergillus nidulans exposed to a Roundup formulation at a dose causing no macroscopic effect: a functional study

Roundup® is a glyphosate-based herbicide (GBH) used worldwide both in agriculture and private gardens. Thus, it constitutes a substantial source of environmental contaminations, especially for water and soil, and may impact a number of non-target organisms essential for ecosystem balance. The soil filamentous fungus Aspergillus nidulans has been shown to be highly affected by a commercial formulation of Roundup® (R450), containing 450 g/L of glyphosate (GLY), at doses far below recommended agricultural application rate. In the present study, we used two-dimensional gel electrophoresis combined to mass spectrometry to analyze proteomic pattern changes in A. nidulans exposed to R450 at a dose corresponding to the no-observed-adverse-effect level (NOAEL) for macroscopic parameters (31.5 mg/L GLY among adjuvants). Comparative analysis revealed a total of 82 differentially expressed proteins between control and R450-treated samples, and 85% of them (70) were unambiguously identified. Their molecular functions were mainly assigned to cell detoxification and stress response (16%), protein synthesis (14%), amino acid metabolism (13%), glycolysis/gluconeogenesis/glycerol metabolism/pentose phosphate pathway (13%) and Krebs TCA cycle/acetyl-CoA synthesis/ATP metabolism (10%). These results bring new insights into the understanding of the toxicity induced by higher doses of this herbicide in the soil model organism A. nidulans. To our knowledge, this study represents the first evidence of protein expression modulation and, thus, possible metabolic disturbance, in response to an herbicide treatment at a dose that does not cause any visible effect. These data are likely to challenge the concept of "substantial equivalence" when applied to herbicide-tolerant plants.

Proteomics in hematologic malignancies

Basic science research in hematology has been determining the functions of gene products using classical approaches that typically involve studying one or a few genes at a time. Proteomics, defined as the study of protein properties on a large scale, provides tools to globally analyze malignant hematologic cells. A major challenge in cancer therapy is the identification of drugs that kill tumor cells while preserving normal cells. Differential display via proteomics enables analysis of direct as well as side-effects of drugs at a molecular level. Proteomics also allows a better understanding of cell signaling pathways involved during apoptosis in hematologic cells. Storing the information in a 2D electrophoresis database enhances the efficiency of proteome research on malignant cells. Finally, the work needed to be carried out on proteomic analysis prior to routine clinical adoption is discussed, and the necessity for multi-institutional collaborations is emphasized.

Analysis of high molecular mass proteins larger than 150 kDa using cyanogen bromide cleavage and conventional 2-DE

Proteomic approaches including high-resolution 2-DE are providing the tools needed to discover disease-associated biomarkers in complex biological samples. Although 2-DE is an extremely powerful approach to analyze the proteome, the separation of proteins with extreme molecular masses still remains an issue requiring improvement. Because high molecular mass (HMM) proteins larger than 150 kDa have already been observed to be differentially expressed in several pathologies such as cancer, we developed an original strategy to analyze this part of the proteome that is not easily separated by 2-DE in polyacrylamide gels. This strategy is based on the 2-DE separation of cyanogen bromide (CNBr) fragments of purified HMM protein fractions, and combines techniques including SEC fractionation, TCA precipitation, CNBr cleavage, 2-DE and MS analysis. The method was first tested on a model protein, the BSA. Preliminary results obtained using colonic tissues led to the identification of six HMM proteins with M(r) comprised between 163 and 533 kDa in their reduced state. These results demonstrated that our CNBr/2-DE approach should provide a powerful tool for identification of new biomarkers larger than 150 kDa.

Proteomics of viruses

Proteomics is a promising approach for the study of viruses allowing a better understanding of disease processes and the development of new biomarkers for diagnosis and early detection of disease, thus accelerating drug development. Viral proteomics has included the analysis of viral particles to determine all proteins that compose the infectious virus, the examination of cellular proteins associated with a single viral protein in the hopes of determining all the functions of that viral protein, or the determination of cellular proteins induced or altered during a particular disease state. Viral particles of human cytomegalovirus (HCMV) and Kaposi's sarcoma-associated herpesvirus/human herpesvirus 8 (KSHV/HHV-8) have been recently examined. During the herpesviral replicative cycle, different viral particles are formed. For HCMV, this includes mature, infectious virions, noninfectious enveloped particles, and dense bodies. A proteome database of B-lymphoblastoid cell lines (LCLs), before and after transformation, has been developed to identify the cellular mechanisms of virus-induced immortalization. 2DE is used to first separate proteins based on their relative charge (pI) and then based on their molecular weight. Proteomic analysis has provided a unique tool for the identification of diagnostic biomarkers, evaluation of disease progression, and drug development. It is also an important approach for clinical diagnostics.

Proteome analysis of B-cell maturation

Proteins affected by anti-mIgM stimulation during B-cell maturation were identified using 2-DE-based proteomics. We investigated the proteome profiles of stimulated and nonstimulated Ramos B-cells at eight time points during 5 d and compared the obtained proteomic data to the corresponding data from DNA-microarray studies. Anti-mIgM stimulation of the cells resulted in significant differences (> or =twofold) in the protein abundance close to 100 proteins and differences in post-translational protein modifications. Forty-eight up- or down-regulated proteins were identified by mass spectrometric methods and database searches. The identities of a further nine proteins were revealed by comparing their positions to the known proteins in other lymphocyte 2-DE databases. Several of the proteins are directly related to the functional and morphological characteristics of B-cells, such as cytoskeleton rearrangement and intracellular signalling triggered by the crosslinking of B-cell receptors. In addition to proteins known to be involved in human B-cell maturation, we identified several proteins that were not previously linked to lymphocyte differentiation. The results provide deeper insights into the process of B-cell maturation and may lead to novel therapeutic strategies for immunodeficiencies. An interactive 2-DE reference map is available at http://bioinf.uta.fi/BcellProteome.

Toward a comprehensive quantitative proteome database: protein expression map of lymphoid neoplasms by 2-D DIGE and MS

Using 2-D DIGE, we constructed a quantitative 2-D database including 309 proteins corresponding to 389 protein spots across 42 lymphoid neoplasm cell lines. The proteins separated by 2-D PAGE were identified by MS and assigned to the expression data obtained by 2-D DIGE. The cell lines were categorized into four groups: those from Hodgkin's lymphoma (HL) (4 cell lines), B cell malignancies (19 cell lines), T cell malignancies (16 cell lines), and natural killer (NK) cell malignancies (3 cell lines). We characterized the proteins in the database by classifying them according to their expression level. We found 28 proteins with more than a 2-fold difference between the cell line groups. We also noted the proteins that allowed multidimensional separation to be achieved (1) between HL cells and other cells, (2) between the cells derived from B cells, T cells and NK cells, and (3) between HL cells and anaplastic large cell lymphoma cells. Decision tree classification identified five proteins that could be used to classify the 42 cell lines according to differentiation. These results suggest that the quantitative 2-D database using 2-D DIGE will be a useful resource for studying the mechanisms underlying the differentiation phenotypes of lymphoid neoplasms.

A proteomic approach to investigate potential biomarkers directed against membrane-associated breast cancer proteins

The identification of specific protein markers for breast cancer would provide the basis for early diagnosis. Particularly, membrane and membrane-associated proteins are rich in targets for antibodies that may constitute suitable biomarkers of carcinogenesis. However, membrane proteins separation using 2-DE remains difficult. In this work, the breast cancer cell line MCF7 was used as source of proteins for the screening of potential cell membrane-associated antigens recognized by autoantibodies in patients with breast cancer and healthy volunteers. The protein extract obtained using trifluoroethanol (TFE) as cosolvent was compared to a total cell lysate protein extract prepared by a current technique. After 2-DE separation of the two extracts, their protein patterns clearly differed. About 63% of the proteins identified in the TFE-extract were predicted to possess at least one transmembrane domain. 2-D blots probed with sera from cancer patients or from healthy volunteers showed that, as expected, additional antigens were provided in the TFE-extract. Thus, the method described here appeared well suited for proteomic investigation of potential biomarkers undetected by current techniques.

Investigation of differentially expressed proteins due to the inhibitory effects of berberine in human liver cancer cell line HepG2

The investigation of differentially expressed proteins was used together with other techniques to study the inhibitory effects of two different doses of berberine in human liver cancer cell line HepG2. For HepG2 cells treated with 24.0 mg l(-1) of berberine, an increase in the sub G(0) phase that was indicative of cell death was observed in cell cycle analysis with flow cytometry. However, no significant increase in sub G(0) was observed in HepG2 cells treated with 4.0 mg l(-1) of berberine. Using flow cytometric analysis, significant activation of caspase 3 was not observed with HepG2 cells treated with 4.0 and 24.0 mg l(-1) of berberine. In this work, labeling of cells with stable isotope was not used in the proposed method developed. The whole cell lysates from the control and treated cells were digested with trypsin and the peptides were separated by two-dimensional (cation exchange and reversed phase) liquid chromatography and tandem mass spectrometry. Our preliminary data showed that the proposed platform provided a rapid approach to study the molecular mechanism due to the inhibitory effects of different doses of the berberine on HepG2 cell lines. This included a network of proteins involved in mitogen-activated protein kinase (MAPK) phosphorelay systems, metabolism, regulation of cell cycle and DNA damage response. The differentially expressed proteins identified using the current approach were consistent with the data obtained from cell cycle analysis with flow cytometry.

Proteomic maps of the cancer-associated infectious agents

The number of infectious agents associated with cancer is increasing. There is a need to develop approaches for the early detection of the infected host which might lead to tumor development. Recent advances in proteomic approaches provide that opportunity, and it is now possible to generate proteomic maps of cancer-associated infectious agents. Protein arrays, interaction maps, data archives, and biological assays are being developed to enable efficient and reliable protein identification and functional analysis. Herein, we discuss the current technologies and challenges in the field, and application of protein signatures in cancer detection and prevention.

Recent advances in blood-related proteomics

Blood is divided in two compartments, namely, plasma and cells. The latter contain red blood cells, leukocytes, and platelets. From a descriptive medical discipline, hematology has evolved towards a pioneering discipline where molecular biology has permitted the development of prognostic and diagnostic indicators for disease. The recent advance in MS and protein separation now allows similar progress in the analysis of proteins. Proteomics offers great promise for the study of proteins in plasma/serum, indeed a number of proteomics databases for plasma/serum have been established. This is a very complex body fluid containing lipids, carbohydrates, amino acids, vitamins, nucleic acids, hormones, and proteins. About 1500 different proteins have recently been identified, and a number of potential new markers of diseases have been characterized. Here, examples of the enormous promise of plasma/serum proteomic analysis for diagnostic/prognostic markers and information on disease mechanism are given. Within the blood are also a large number of different blood cell types that potentially hold similar information. Proteomics of red blood cells, until now, has not improved our knowledge of these cells, in contrast to the major progresses achieved while studying platelets and leukocytes. In the future, proteomics will change several aspects of hematology.

Proteome analysis in the study of lymphoma cells

This review provides an overview on recent studies in the field of proteome analysis of lymphoma cells, and highlights the potentials of such studies for a better knowledge of drug effects at the molecular level. After giving general information on the field of proteome analysis of lymphoma cells, some characteristics of the strategies used during this analysis are pointed out, such as cell extraction strategies and affinity captures. Therefore, the issue of proteome analysis of lymphoma cells content will be covered with respect to those protein extracts that can be prepared in saline solutions, such as cytoplasm proteins, or that are associated with the cell membranes. The question of which kinds of information have been retrieved from lymphoma-cell proteomics is discussed on the basis of several examples-lymphoma cell-mapping studies and constitution of protein databases, and comparative proteome analysis studies of the modifications that result from a drug treatment.

Study of proteomic changes associated with healthy and tumoral murine samples in neuroblastoma by principal component analysis and classification methods

BACKGROUND

The adrenal gland is the election organ forming primary neuroblastoma (NB) tumours, the most common extracranial solid tumours of infancy and childhood.

METHODS

Samples of adrenal gland belonging to healthy and diseased nude mouse were analysed by 2D gel-electrophoresis. The resulting 2D-PAGE maps were digitized by PDQuest and investigated by principal component analysis (PCA).

RESULTS

The analysis of the loadings of the first principal component (PC) permitted the evaluation of the spots characterising each class of samples. Moreover, the soft-independent model of class analogy (SIMCA) method confirmed the separation of the samples in the two classes and allowed the identification of the modelling and discriminating spots. Very good correlation was found between the data obtained by analysis of 2D maps via the commercial software PDQuest and the present PCA analysis. In both cases, the comparison between such maps showed up- and down-regulation of 84 polypeptide chains, out of a total of 700 spots detected by a fluorescent stain, Sypro Ruby. Spots that were differentially expressed between the two groups were analysed by matrix-assisted laser desorption time-of-flight (MALDI-TOF) mass spectrometry and 14 of these spots were identified so far.

Differential protein expression of the inhibitory effects of a standardized extract from Scutellariae radix in liver cancer cell lines using liquid chromatography and tandem mass spectrometry

The purpose of this study is to verify the inhibitory effect of a chemically standardized extract from Scutellariae radix in liver cancer cell lines (HepG2). The botanical extract was prepared using pressurized liquid extraction (PLE). A method using proteolytic digest with single dimensional and two-dimensional liquid chromatography with tandem mass spectrometry was used to characterize differential protein expression in mammalian cells in response to the botanical extract. The whole cell lysates were digested with trypsin, and the peptides were separated by one-dimensional (reversed phase) or by two-dimensional (cation exchange and reversed phase) solid-phase extraction (SPE) cleanup and separated by liquid chromatography with UV detection and mass spectrometry. In the presence of the botanical extracts, drug-induced apoptosis was not observed, and a number of proteins that played an important role in the metabolic pathways in HepG2 cell line had been affected. The data, as presented, suggest that the inhibitory effects of the standardized extracts from Scutellariae radix resulted from expression of heat shock protein and other proteins related to energy metabolism. The proposed platform had the potential to provide significant information about the particular proteome such as human hepatoma HepG2. At the molecular level, it was possible to study the proteins and how their levels and modifications change in response to the effects of the botanical extract.

Proteomics and the haematologist

Understanding haematological malignancies at the protein level is important as the development of targeted treatments must be based on knowledge regarding the molecular pathogenesis of the tumour, inherited genetic variation and the mode of action of drugs. 'Proteomics' describes the analysis of the entire proteome of a cell or tissue and incorporates multiple technologies including Western blotting, two-dimensional gel electrophoresis, mass spectrometry, and ProteinChip-based technology. Although there are a limited number of studies to date in haematology those performed highlight the potential future impact of these technologies in the discovery of novel markers, proteins associated with drug resistance and the identification of tumour biomarkers which may facilitate the development of a rapid diagnostic test easily applicable in the clinical setting. Rapid large-scale analysis of the proteome in normal pathways and disease offers the opportunity of identification of potential diagnostic/prognostic markers and proteins associated with the malignant phenotype. This review discusses the current situation regarding the use of these technologies and the potential opportunities their future use may offer in the field of haematology.

A Simple Solid Phase Mass Tagging Approach for Quantitative Proteomics

New mass-tagging reagents for quantitative proteomics measurements have been designed using solid phase peptide synthesis technology. The solid phase mass tags have been used to accurately measure the relative amounts of cysteine-containing peptides in model peptide mixtures as well as in mixtures of tryptic digests in the femtomol range. Measurements were made using both matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) and online reversed-phase capillary liquid chromatography coupled through a nanoelectrospray interface to an ion trap mass spectrometer (capillary LC/ESI-MS). Results of mass-tagging experiments obtained from these two mass spectrometry techniques and their relative advantages and disadvantages for identification and quantitation of mass tagged peptides are compared. These reagents provide a simple, rapid and cost-effective alternative to currently available mass tagging technologies.

Automating proteome analysis: improvements in throughput, quality and accuracy of protein identification by peptide mass fingerprinting

The use of robots has major effects on maximizing the proteomic workflow required in an increasing number of high-throughput projects and on increasing the quality of the data. In peptide mass finger printing (PMF), automation of steps downstream of two-dimensional gel electrophoresis is essential. To achieve this goal, the workflow must be fluid. We have developed tools using macros written in Microsoft Excel and Word to complete the automation of our platform. Additionally, because sample preparation is crucial for identification of proteins by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry, we optimized a sandwich method usable by any robot for spotting digests on a MALDI target. This procedure enables further efficient automated washing steps directly on the MALDI target. The success rate of PMF identification was evaluated for the automated sandwich method, and for the dried-droplet method implemented on the robot as recommended by the manufacturer. Of the two methods, the sandwich method achieved the highest identification success rate and sequence coverage of proteins.

Proteomics in biomarker discovery and drug development

Proteomics is a research field aiming to characterize molecular and cellular dynamics in protein expression and function on a global level. The introduction of proteomics has been greatly broadening our view and accelerating our path in various medical researches. The most significant advantage of proteomics is its ability to examine a whole proteome or sub-proteome in a single experiment so that the protein alterations corresponding to a pathological or biochemical condition at a given time can be considered in an integrated way. Proteomic technology has been extensively used to tackle a wide variety of medical subjects including biomarker discovery and drug development. By complement with other new technique advances in genomics and bioinformatics, proteomics has a great potential to make considerable contribution to biomarker identification and to revolutionize drug development process. This article provides a brief overview of the proteomic technologies and their application in biomarker discovery and drug development.

Assessment of protein expression by means of 2-D gel electrophoresis with and without mass spectrometry

Careful examination of current literature, particularly over the last 5 years, reveals a wide range of approaches for the relative quantification of protein expression in cells, tissues, and body fluids. In view of such an observation, it is reasonable to ask whether researchers need new methods, or whether it is more productive to optimize and tune already existing ones. It is generally agreed that none of the existing methodologies on its own can give a full account of protein expression in a complex medium; this limitation, however, has not prevented the use of existing methods to provide valuable information on a wide range of proteins, where their expression has been correlated to certain pathologies and/or to pharmacological, genetic, or environmental factors. In the present work, an attempt is made to review the application of one of these methodologies, namely two-dimensional polyacrylamide gel electrophoresis on its own or in conjunction with mass spectrometry, to assess protein expression, particularly when such expression can be correlated to certain pathologies.

Proteome analysis of Epstein-Barr virus-transformed B-lymphoblasts and the proteome database

The proteome is the entire protein complement of the genome expressed in a particular cell, tissue, or organism at a given time under a specific set of environmental conditions. Proteomics is a combinatorial methodology to comprehensively analyze the proteome. The general protocol of the expression proteomics consists of advanced methods of high-resolution protein separation, high-quality image analysis and high-throughput protein identification. Although Epstein-Barr virus-transformed B-lymphoblastoid cell lines (LCLs) have long been believed to be immortalized, recent studies have provided ample evidence that a large proportion of LCLs have limited life spans due to shortening of telomeres, and that part of them are truly immortalized by developing strong telomerase activity to maintain telomeres. Differential proteome analysis of pre- and post-immortal LCLs would provide a powerful tool to analyze proteins participating in the process of immortalization. We focus in this review on cumulative data of proteomic information on pre- and post-immortal LCLs.

Current perspectives in cancer proteomics

Proteome technology has been used widely in cancer research and is a useful tool for the identification of new cancer markers and treatment-related changes in cancer. This article details the use of proteome technology in cancer research, and laboratory-based and clinical cancer research studies are described. New developments in proteome technology that enable higher sample-throughput are evaluated and methods for enhancing conventional proteome analysis (based on two-dimensional electrophoresis) discussed. The need to couple laboratory-based proteomics research with clinically relevant models of the disease is also considered, as this remains the next main challenge of cancer-related proteome research.

Pharmacogenetics of anticancer drug sensitivity in non-small cell lung cancer

In mammalian cells, the process of malignant transformation is characterized by the loss or down-regulation of tumor-suppressor genes and/or the mutation or overexpression of proto-oncogenes, whose products promote dysregulated proliferation of cells and extend their life span. Deregulation in intracellular transduction pathways generates mitogenic signals that promote abnormal cell growth and the acquisition of an undifferentiated phenotype. Genetic abnormalities in cancer have been widely studied to identify those factors predictive of tumor progression, survival, and response to chemotherapeutic agents. Pharmacogenetics has been founded as a science to examine the genetic basis of interindividual variation in drug metabolism, drug targets, and transporters, which result in differences in the efficacy and safety of many therapeutic agents. The traditional pharmacogenetic approach relies on studying sequence variations in candidate genes suspected of affecting drug response. However, these studies have yielded contradictory results because of the small number of molecular determinants of drug response examined, and in several cases this approach was revealed to be reductionistic. This limitation is now being overcome by the use of novel techniques, i.e., high-density DNA and protein arrays, which allow genome- and proteome-wide tumor profiling. Pharmacogenomics represents the natural evolution of pharmacogenetics since it addresses, on a genome-wide basis, the effect of the sum of genetic variants on drug responses of individuals. Development of pharmacogenomics as a new field has accelerated the progress in drug discovery by the identification of novel therapeutic targets by expression profiling at the genomic or proteomic levels. In addition to this, pharmacogenetics and pharmacogenomics provide an important opportunity to select patients who may benefit from the administration of specific agents that best match the genetic profile of the disease, thus allowing maximum activity.

Proteomic map and database of lymphoblastoid proteins

Advances in genomics have led to the accumulation of an unprecedented amount of data, giving rise to a new field in biochemistry, proteomics. We used a combination of two dimensional gel electrophoresis, analysis and annotation using third-generation software, and mass spectrometry to establish the proteome maps of lymphoblastoid B-cells, a prerequisite for analysis of drug effects and lymphocyte cell diseases. About 1200 protein spots were detected and characterised in terms of their isoelectric point, molecular mass and expression. The present status of proteomic technologies, as well as a description of the usefulness of human hematopoietic cells proteomic database are discussed.

Effect of 5-azacytidine and galectin-1 on growth and differentiation of the human b lymphoma cell line bl36

BACKGROUND: 5-AzaCytidine (AzaC) is a DNA demethylating drugs that has been shown to inhibit cell growth and to induce apoptosis in certain cancer cells. Induced expression of the galectin1 (Gal1) protein, a galactoside-binding protein distributed widely in immune cells, has been described in cultured hepatoma-derived cells treated with AzaC and this event may have a role in the effect of the drug. According to this hypothesis, we investigated the effect of AzaC and Gal1 on human lymphoid B cells phenotype. METHODS: The effect of AzaC and Gal1 on cell growth and phenotype was determined on the Burkitt lymphoma cell line BL36. An immunocytochemical analysis for detection of Gal1 protein expression was performed in AzaC-treated cells. To investigate the direct effects of Gal1, recombinant Gal1 was added to cells. RESULTS: Treatment of lymphoid B cells with AzaC results in: i) a decrease in cell growth with an arrest of the cell cycle at G0/G1 phase, ii) phenotypic changes consistent with a differentiated phenotype, and iii) the expression of p16, a tumor-suppressor gene whose expression was dependent of its promoter demethylation, and of Gal1. A targeting of Gal 1 to the plasma membrane follows its cytosolic expression. To determine which of the effects of AzaC might be secondary to the induction of Gal1, recombinant Gal1 was added to BL36 cells. Treated cells displayed growth inhibition and phenotypic changes consistent with a commitment toward differentiation. CONCLUSIONS: Altered cell growth and expression of the cell surface plasma cell antigen, CD138 are detectable in BL36 cells treated by AzaC as well as by Gal1. It seems that AzaC-induced Gal1 expression and consequent binding of Gal1 on its cell membrane receptor may be, in part, involved in AzaC-induced plasmacytic differentiation.

Cancer proteomics: from signaling networks to tumor markers

Along with the great strides that have been made towards understanding cancer, has come a realization of the complexity of molecular events that lead to malignancy. Proteomics-based approaches, which enable the quantitative investigation of both cellular protein expression levels and protein-protein interactions involved in signaling networks, promise to define the molecules controlling the processes involved in cancer.