Sample pooling in 2-D gel electrophoresis: a new approach to reduce nonspecific expression background

Protein expression alterations unrelated to an investigated phenotype are accumulated in most cell line models during establishment. Performing a whole proteome screening of lymphoma cell lines, we established a method to reduce the influence of protein expression unrelated to the distinct investigated phenotype. In 2-D PAGE, the comprehensive analysis of a large number of protein spots would be simplified by pooling cell line samples of the investigated phenotype. Applying this pooling approach, unrelated alterations of single samples are 'muted' by dilution. Analysing two different lymphoma subtypes (follicular and mantle cell lymphoma) by this method, spots originating in only single cell lines were reduced by 72% (650/900), whereas even modestly altered expression of protein spots detected in all lines were reliably detected in the pooled protein gels. We conclude that our pooling approach is a preferable approach to reliably detect a common protein expression pattern and may even allow proteomic analysis of clinical samples with limited amounts of sample material, even with minimal cell numbers as low as 1 x 10(6).     

Two-dimensional molecular profiling of mantle cell lymphoma

The present research establishes standard two-dimensional (2-D) maps for control, reactive lymph node and non-Hodgkin's lymphoma (mantle cell lymphoma, MCL). Medium sensitivity, mass spectrometry compatible colloidal Coomassie has revealed a total of ca. 750 spots in each of the maps. Comparison of 2-D maps by statistical packages, such as the PDQuest, established up- and downregulation of a total of ca. 145 spots, with positive variations of up to 10-folds and negative variations of up to 13-folds in both MCL biopsies' protein extracts. Qualitative and quantitative variations in the two lymphoma samples are consistent. More than 20 proteins have been so far identified by matrix assisted laser desorption/ionisation-time of flight (MALDI-TOF)-mass spectrometry, with an additional five spots, which gave very good spectra but could not be matched to any of the presently available databases. Some of the spots, such as the 78 kDa glucose-regulated protein precursor and the glutathione S-transferase P, appear to be in common with other tumors, such as lung adenocarcinoma. Others may simply reflect overall changes in cellular metabolism and growth rate that occur during malignancy and thus might turn out to be in common with any cell population receiving any kind of stress. Some (notably T-cell leukemia/lymphoma protein 1A, TCL1, found to be 10-fold overexpressed) appear to be specific of the non-Hodgkin's lymphoma here studied. Western blot and immunohistochemical analyses were applied to obtain further information about stathmin (Op18) and TCL1, respectively.     

Proteomic and redox‐proteomic study on the role of glutathione reductase in human lung cancer cells

Glutathione reductase (GR), a cytosolic protein, plays a vital role in maintaining a correct redox status in cells. However, comprehensive investigations of GR‐modulated cellular responses, including protein level alteration and redox regulation, have yet to be performed. In this study, we cultured a human lung adenocarcinoma line transfected with empty pLKO.1 vector as a control, CL1‐0shControl, and its GR‐knockdown derivative, CL1‐0shΔGR, to evaluate differential protein level alteration and redox regulation of these two cell lines. We identified 34 spots that exhibited marked changes in intensities, and 13 proteins showing significant changes in thiol reactivity, in response to GR depletion. Several proteins involved in redox regulation, calcium signaling, cytoskeleton regulation, and protein folding showed significant changes in expression, whereas proteins involved in redox regulation, protein folding, and glycolysis displayed changes in thiol reactivity. Interestingly, GR knockdown induces peroxiredoxin‐1 overexpression in the air‐exposed tissue and high oxygen consuming tissue such as cornea and liver, but not in the low oxygen consuming tissues such as breast and uterine. In summary, we used a comprehensive lung adenocarcinoma based proteomic approach for identifying GR‐modulated protein expression alteration and redox modification. Based on our research, this is the first comprehensive proteomic and redox‐proteomic analysis used to investigate the role of GR in a mammalian cell model.     

Identification of the regulatory proteins in human pancreatic cancers treated with Trichostatin A by 2D-PAGE maps and multivariate statistical analysis

In this paper, principal component analysis (PCA) is applied to a spot quantity dataset comprising 435 spots detected in 18 samples belonging to two different cell lines (Paca44 and T3M4) of control (untreated) and drug-treated pancreatic ductal carcinoma cells. The aim of the study was the identification of the differences occurring between the proteomic patterns of the two investigated cell lines and the evaluation of the effect of the drug Trichostatin A on the protein content of the cells. PCA turned out to be a successful tool for the identification of the classes of samples present in the dataset. Moreover, the loadings analysis allowed the identification of the differentially expressed spots, which characterise each group of samples. The treatment of both the cell lines with Trichostatin A therefore showed an appreciable effect on the proteomic pattern of the treated samples. Identification of some of the most relevant spots was also performed by mass spectrometry.     

人卵巢癌耐药细胞株的比较蛋白质组分析

本文采用高分辨二维凝胶电泳分离技术对人卵巢癌细胞株COC1及其耐药细胞株COC1/DDP中的蛋白质进行分离和差异表达分析, 应用基质辅助激光解吸电离-飞行时间质谱对酶解多肽进行测定[即测定蛋白质的肽质量指纹图(Peptide mass fingerprinting, PMF)], 并通过相应的数据库搜索来鉴定蛋白质. 为获得更准确的检索结果, 采用串联质谱技术对各肽段进行氨基酸测序, 并应用IPI-HUMAN数据库对上述检索结果进一步加以确认.      

2-DE and MALDI-TOF-MS for a comparative analysis of proteins expressed in different cellular models of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal, neurodegenerative disorder characterized by the selective loss of motor neurons from the spinal cord and brain. About 10% of ALS cases are familial (FALS), and in 20% of these cases the disease has been linked to mutations in the Cu,Zn-SOD1 gene. Although the molecular mechanisms causing these forms of ALS are still unclear, evidence has been provided that motor neurons injuries associated with mutant superoxide dismutase (SOD1)-related FALS result from a toxic gain-in-fuction of the mutated enzyme. To understand better the role of these mutations in the pathophysiology of FALS we have compared the pattern of proteins expressed in human neuroblastoma SH-SY5Y cell line with those of cell lines transfected with plasmids expressing the wild-type human SOD1 and the H46R and G93A mutants. 2-DE coupled to MALDI-TOF-MS were the proteomic tools used for identification of differentially expressed proteins. These included cytoskeletal proteins, proteins that regulate energetic metabolism and intracellular redox conditions, and the ubiquitin proteasome system. The proteomic approach allowed to expand the knowledge on the pattern of proteins, with altered expression, which we should focus on, for a better understanding of the possible mechanism involved in mutated-SOD1 toxicity. The cellular models considered in this work have also evidenced biochemical characteristics common to other SOD1-mutated cellular lines connected to the pathogenesis of ALS.     

Use of principal components analysis for mutation detection with two-dimensional electrophoresis protein separations.

The application of two-dimensional electrophoresis (2-DE) to mutation detection requires the capability to monitor each protein in a 2-DE pattern for significant changes in abundance indicative of a mutation event. Previously, mutation searches were done using a univariate outlier detection method in which each protein spot was considered independently in a classical outlier search. An alternative approach to analysis of 2-DE patterns for quantitative changes is a multivariate procedure which takes advantage of the observation that protein spots in a 2-DE pattern often represent correlated rather than independent measurements. We have compared the efficiency of univariate and multivariate procedures for mutation detection using data from the Argonne National Laboratory 2-DE database of mouse liver proteins. Analyses involving a total of over 1500 gels were performed to compare the performance of a multivariate method based on principal components analysis (PCA) with the univariate method. Up to 279 spots from each pattern were used for PCA. First, a simulation was performed to assess the detection efficiency of PCA for single protein spots decreased in abundance by 50%. Then, the ability to detect actual mutations was tested using eight confirmed mutations. Results show that, compared to a univariate approach to analysis of data from the mouse model system, the multivariate method increases the number of protein spots on each 2-DE pattern that can be monitored for quantitative changes indicative of mutations by compensating for variables that contribute to the background quantitative variability of protein spots.     

Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry

The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance, but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation.     

缺氧预处理诱导心肌细胞蛋白质组变化的初步研究

缺氧预处理(hypoxia preconditioning, HPC)可模拟缺血预处理(ischemic preconditioning, IPC)对缺血/再灌注心肌的保护作用, 涉及细胞内众多分子事件. 本工作旨在采用双向电泳和质谱分析等蛋白质组分析技术, 发现缺氧预处理后心肌细胞蛋白质整体表达上的变化, 初步分析其与缺氧预处理心肌保护作用的关系. 将原代培养的SD乳鼠心肌细胞分为2组(n＝6): (1)缺氧预处理组(HPC): 将细胞置缺氧仓内短暂缺氧20 min进行缺氧预处理(HPC), 制备心肌细胞蛋白提取物; (2)对照组(control): 细胞置于培养箱内持续常氧孵育至实验结束, 提取蛋白. 采用双向凝胶电泳和图像扫描, 经蛋白样本分离和考马斯亮蓝染色后比较分析, 选取3个差异表达蛋白点进行胶内酶切、肽质量指纹图谱分析和数据库检索. 双向电泳可分离约529±45个蛋白质, 点匹配率约为78%±7.5%. 18种蛋白质在HPC后发生明显表达差异, 其中12种蛋白质表达降低, 6种表达增高. 经质谱分析鉴定出的3种蛋白质分别为myosin light polypeptide 3, nucleoside diphosphate kinase (NDPK)和calreticulin (CRT). 缺氧预处理引起心肌细胞蛋白质组变化, 初步发现其中myosin light polypeptide 3表达下调、nucleoside diphosphate kinase和calreticulin表达增加, 可能通过调节心肌细胞的收缩性、激活G蛋白、调节细胞内Ca^2＋浓度而保护心肌. 本工作通过研究缺氧预处理延迟保护过程中心肌内源性蛋白表达水平的变化, 有助于从细胞水平探讨预处理延迟保护机制.     

River Pollution Data Interpreted by Means of Chemometric Methods

Environmental data, including river pollution data, are characterized by high variability. Much information is lost by using only univariate graphical or statistical methods for data evaluation and interpretation. Chemometric methods, in particular methods of multivariate data analysis, help to extract the latent information in such data. The combination of cluster analysis as the first step and multivariate analysis of variance and discriminant analysis as the second step enables identification of similar locations in a river. Pollution sources and dischargers can be detected by means of factor analysis. The deposition–remobilization behavior of metals in a river can be described using partial least squares regression. Summarizing, it can be stated that methods of multivariate data analysis are powerful tools for the evaluation and interpretation of river pollution data.     

Multisignal calibration in spark- and ICP-OES

The advantages of multivariate calibration by using more than one selective emission line for one analyte are described in comparison with univariate calibration. Principle component regression (PCR) and partial least squares regression (PLS) are compared with classical univariate linear regression of single lines. Practical applications in spark- and inductively coupled plasma optical emission spectroscopy (ICP-OES) show that the sensitivity can be increased and thus a lower limit of detection be obtained by means of these multivariate techniques. Results from the investigations concerning the problem of collinearity are also discussed. Disturbed analyte lines are included in multisignal calibration. Their influence on the results of calibration is described.     

Combined RNA-expression and 2D-PAGE-screening identifies comprehensive interaction networks affected after bortezomib or enzastaurin exposure of mantle cell lymphoma

Despite recent advances in treatment, mantle cell lymphoma (MCL) still represents a disease with dismal prognosis due to its progressive clinical course, high rate of therapy refractory cases and frequent relapses. During recent years, the proteasome inhibitor bortezomib and enzastaurin, an inhibitor of protein kinase c have been explored in MCL. In relapsed disease enzastaurin achieved disease stabilization in a subset of patients. Bortezomib in relapsed and refractory MCL achieves response rates of 30-40%. To identify signal pathways and manifold interactions regulating cellular response to molecular targeted approaches several high throughput screening methods were applied. A combined network analysis of the identified target molecules based on both RNA array expression data and a survey of cellular protein levels resulted in a unified interaction network more comprehensive (bortezomib: 394 and enzastaurin: 174 molecules) than the networks of the individual screening techniques (329/44 and 117/36 molecules respectively). Interestingly, although none of the target molecules were matched in both RNA-expression and protein level analysis they were mapped nonetheless to common pathways. Additionally, the ranking of identified pathways allowed an improved characterization of the observed induction of cell apoptosis.     

The inter‐ and intra‐operator variability in manual spot segmentation and its effect on spot quantitation in two‐dimensional electrophoresis analysis

Separation of complex mixtures of proteins by 2‐DE is a fundamental component of current proteomic technology. Quantitative analysis of the images generated by digitization of such gels is critical for identifying alterations in protein expression within a given biological system. Software packages are designed for this purpose. The accurate definition of protein spot boundaries, using a suitable method of image segmentation, is a key requirement for image analysis. It is often necessary for operators to intervene manually to correct mistakes in spot segmentation; therefore operator subjectivity and differences in ability can weaken the analysis. We estimated the error in spot quantification after manual spot segmentation, which was performed by different operators, using two different software packages. Our results clearly show that this operation was associated with significant inter‐ and intra‐variability and an overestimation of subsequent spot intensity, especially when spots were weak. For comparative studies, we suggest separately analysing spots which have been manually segmented by imposing a requirement for at least a threefold difference in spot intensity in addition to use of statistical tests.     

The proteome of lentil (Lens culinaris Medik.) seeds: Discriminating between landraces

Lentil (Lens culinaris Medik.) is one of the most ancient crops of the Mediterranean region used for human nutrition; an extensive differentiation of L. culinaris over millennia has resulted in a number of different landraces. As a consequence of environmental and socio‐economic issues, the disappearance of many of them occurred in more recent times. To investigate the potential of proteomics as a tool in phylogenetic studies, testing the possibility to identify specific markers of different plant landraces, 2‐D gel electrophoretic maps of mature seeds were obtained from seven lentil populations belonging to a local ecotype (Capracotta) and five commercial varieties (Turca Rossa, Canadese, Castelluccio di Norcia, Rascino and Colfiorito). 2‐DE analysis resolved hundreds of protein species in each lentil sample, among which only 122 were further identified by MALDI‐TOF PMF and/or nanoLC‐ESI‐LIT‐MS/MS, probably as a result of the poor information available on L. culinaris genome. A comparison of these maps revealed that 103 protein spots were differentially expressed within and between populations. The multivariate statistical analyses carried out on these variably expressed spots showed that 24 protein species were essential for population discrimination, thus determining their proposition as landrace markers. Besides providing the first reference map of mature lentil seeds, our data confirm previous studies based on morphological/genetic observations and further support the valuable use of proteomic techniques as phylogenetic tool in plant studies.     

Selection of orthogonal reversed-phase HPLC systems by univariate and auto-associative multivariate regression trees

In order to select chromatographic starting conditions to be optimized during further method development of the separation of a given mixture, so-called generic orthogonal chromatographic systems could be explored in parallel. In this paper the use of univariate and multivariate regression trees (MRT) was studied to define the most orthogonal subset from a given set of chromatographic systems. Two data sets were considered, which contain the retention data of 68 structurally diversive drugs on sets of 32 and 38 chromatographic systems, respectively. For both the univariate and multivariate approaches no other data but the measured retention factors are needed to build the decision trees. Since multivariate regression trees are used in an unsupervised way, they are called auto-associative multivariate regression trees (AAMRT). For all decision trees used, a variable importance list of the predictor variables can be derived. It was concluded that based on these ranked lists, both for univariate and multivariate regression trees, a selection of the most orthogonal systems from a given set of systems can be obtained in a user-friendly and fast way.     

A simple protocol for protein extraction of recalcitrant fruit tissues suitable for 2-DE and MS analysis

Fruit tissues are considered recalcitrant plant tissue for proteomic analysis. Three phenol-free protein extraction procedures for 2-DE were compared and evaluated on apple fruit proteins. Incorporation of hot SDS buffer, extraction with TCA/acetone precipitation was found to be the most effective protocol. The results from SDS-PAGE and 2-DE analysis showed high quality proteins. More than 500 apple polypeptides were separated on a small scale 2-DE gel. The successful protocol was further tested on banana fruit, in which 504 and 386 proteins were detected in peel and flesh tissues, respectively. To demonstrate the quality of the extracted proteins, several protein spots from apple and banana peels were cut from 2-DE gels, analyzed by MS and have been tentatively identified. The protocol described in this study is a simple procedure which could be routinely used in proteomic studies of many types of recalcitrant fruit tissues.     

Dynamics of Arabidopsis thaliana soluble proteome in response to different nutrient culture conditions

In an effort to determine the best extraction procedure compatible with the high-reproducible 2-DE, different methods of soluble protein extraction from Arabidopsis cell culture suspensions grown in Gamborg B5 medium were tested. A reference 2-DE map was established for this soluble extract revealing 1184 spots. The most abundant protein spots were excised, trypsin-digested, and mass spectra obtained via MALDI-TOF and/or LC coupled to ESI-MS. Three hundred and thirty one proteins were identified and their functions were defined based on sequence comparisons and classified in different protein families. In order to analyze the impact of culture medium on the Arabidopsis proteome, we performed the 2-DE map from Arabidopsis cell suspensions cultured in another growth medium Murashige and Skoog (M-S) and 327 major spots were identified. Using PDQuest imaging analysis, significant increases in the amount of several housekeeping enzymes, stress/defense proteins, and heat shock proteins were found in M-S medium. Modified expression of certain proteins and detection of new isoforms involved in nitrate assimilation, nitrogen, and sulfur metabolism were also observed in the M-S medium. This study provides the first 2-DE maps of the soluble proteome of Arabidopsis cell suspensions. The comparative analysis of the Arabidopsis proteome in respect to different nutrient supplies shows that the culture medium may significantly influence the expression pattern of major soluble proteins in Arabidopsis cells. This work also constitutes an important step for further proteomic analysis concerning cell responses to abiotic or biotic stresses.     

A multivariate insight into the in vitro antitumour screen database of the National Cancer Institute: classification of compounds, similarities among cell lines and the influence of molecular targets

A multivariate insight into the in vitro antitumour screen database of the NCI by means of the SIMCA package allows to propose hypotheses on the mechanism of action of novel anticancer compounds. As an example, the application of multivariate analysis to the NCI standard database provided clues to the classification of drugs whose mechanism is either unknown or controversial. Moreover, the influence of intrinsic biochemical cell line properties (molecular targets) on the sensitivity to drug treatment could be evaluated simultaneously for classes of compounds which act by the same mechanism. Interestingly, the present approach can also provide a correlation between the molecular targets and the therapeutical fingerprint of novel active compounds thus suggesting specific biochemical studies for the investigation of new mechanisms of drug action and resistance. The statistical approach reported here represents a valuable tool for handling theenormous data sets deriving from recent genome-wide investigations of gene expression in the NCI cell lines.