We have determined the relationship between mRNA and protein expression levels for selected genes expressed in the yeast Saccharomyces cerevisiae growing at mid-log phase. The proteins contained in total yeast cell lysate were separated by high-resolution two-dimensional (2D) gel electrophoresis. Over 150 protein spots were excised and identified by capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS). Protein spots were quantified by metabolic labeling and scintillation counting. Corresponding mRNA levels were calculated from serial analysis of gene expression (SAGE) frequency tables (V. E. Velculescu, L. Zhang, W. Zhou, J. Vogelstein, M. A. Basrai, D. E. Bassett, Jr., P. Hieter, B. Vogelstein, and K. W. Kinzler, Cell 88:243-251, 1997). We found that the correlation between mRNA and protein levels was insufficient to predict protein expression levels from quantitative mRNA data. Indeed, for some genes, while the mRNA levels were of the same value the protein levels varied by more than 20-fold. Conversely, invariant steady-state levels of certain proteins were observed with respective mRNA transcript levels that varied by as much as 30-fold. Another interesting observation is that codon bias is not a predictor of either protein or mRNA levels. Our results clearly delineate the technical boundaries of current approaches for quantitative analysis of protein expression and reveal that simple deduction from mRNA transcript analysis is insufficient.The description of the state of a biological system by the quantitative measurement of the system constituents is an essential but largely unexplored area of biology. With recent technical advances including the development of differential display-PCR (21), of cDNA microarray and DNA chip technology (20,27), and of serial analysis of gene expression (SAGE) (34, 35), it is now feasible to establish global and quantitative mRNA expression profiles of cells and tissues in species for which the sequence of all the genes is known. However, there is emerging evidence which suggests that mRNA expression patterns are necessary but are by themselves insufficient for the quantitative description of biological systems. This evidence includes discoveries of posttranscriptional mechanisms controlling the protein translation rate (15), the half-lives of specific proteins or mRNAs (33), and the intracellular location and molecular association of the protein products of expressed genes (32).Proteome analysis, defined as the analysis of the protein complement expressed by a genome (26), has been suggested as an approach to the quantitative description of the state of a biological system by the quantitative analysis of protein expression profiles (36). Proteome analysis is conceptually attractive because of its potential to determine properties of biological systems that are not apparent by DNA or mRNA sequence analysis alone. Such properties include the quantity of protein expression, the subcellular location, the state of modification, and the association with ligands, as w...
Proteome analysis is most commonly accomplished by a combination of two-dimensional gel electrophoresis (2DE) to separate and visualize proteins and mass spectrometry (MS) for protein identification. Although this technique is powerful, mature, and sensitive, questions remain concerning its ability to characterize all of the elements of a proteome. In the current study, more than 1,500 features were visualized by silver staining a narrow pH range (4.9 -5.7) 2D gel in which 0.5 mg of total soluble yeast protein was separated. Fifty spots migrating to a region of 4 cm 2 were subjected to MS protein identification. Despite the high sample load and extended electrophoretic separation, proteins from genes with codon bias values of <0.1 (lower abundance proteins) were not found, even though fully one-half of all yeast genes fall into that range. Proteins from genes with codon bias values of <0.1 were found, however, if protein amounts exceeding the capacity of 2DE were fractionated and analyzed. We conclude that the large range of protein expression levels limits the ability of the 2DE-MS approach to analyze proteins of medium to low abundance, and thus the potential of this technique for proteome analysis is likewise limited.T he genomics revolution has changed the paradigm for the comprehensive analysis of biological processes and systems. It is now hypothesized that biological processes and systems can be described based on the comparison of global, quantitative gene expression patterns from cells or tissues representing different states. To test this hypothesis, it is essential that methods for the precise measurement of gene expression be developed and applied.Several methods, including serial analysis of gene expression, oligonucleotide and cDNA microarrays, and large-scale sequencing of expressed sequence tags have been developed to globally and quantitatively measure gene expression at the mRNA level (1, 2). The discovery of posttranscriptional mechanisms that control rate of synthesis and half-life of proteins (3) and the ensuing nonpredictive correlation between mRNA and protein levels expressed by a particular gene (4, 5) indicate that direct measurement of protein expression also is essential for the analysis of biological processes and systems.Global analysis of gene expression at the protein level is now also termed proteomics. The standard method for quantitative proteome analysis combines protein separation by highresolution (isoelectric focusing͞SDS-PAGE) two-dimensional gel electrophoresis (2DE) with mass spectrometric (MS) or tandem MS (MS͞MS) identification of selected protein spots. Important technical advances related to 2DE and protein MS have increased sensitivity, reproducibility, and throughput of proteome analysis while creating an integrated technology.By using 2DE with extended pH range and high-sensitivity protein identification by electrospray ionization and MS͞MS, we have evaluated the potential of the 2DE-MS strategy to serve as the technology base for comprehensive and quantitative pr...
Immunized mice after inhalation of specific antigen have the following characteristic features of human asthma: airway eosinophilia, mucus and Th2 cytokine release, and hyperresponsiveness to methacholine. A model of late-phase allergic pulmonary inflammation in ovalbumin-sensitized mice was used to address the role of the alpha4 integrin (CD49d) in mediating the airway inflammation and hyperresponsiveness. Local, intrapulmonary blockade of CD49d by intranasal administration of CD49d mAb inhibited all signs of lung inflammation, IL-4 and IL-5 release, and hyperresponsiveness to methacholine. In contrast, CD49d blockade on circulating leukocytes by intraperitoneal CD49d mAb treatment only prevented the airway eosinophilia. In this asthma model, a CD49d-positive intrapulmonary leukocyte distinct from the eosinophil is the key effector cell of allergen-induced pulmonary inflammation and hyperresponsiveness.
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