The correlation between cellular size and protein expression levels - Normalization for global protein profiling

ArticleinJournal of Proteomics 71(4):448-60 · October 2008with6 Reads
DOI: 10.1016/j.jprot.2008.06.014 · Source: PubMed
An automated image analysis system was used for protein quantification of 1862 human proteins in 47 cancer cell lines and 12 clinical cell samples using cell microarrays and immunohistochemistry. The analysis suggests that most proteins are expressed in a cell size dependent manner, and that normalization is required for comparative protein quantification in order to correct for the inherent bias of cell size and systematic ambiguities associated with immunohistochemistry. Two reference standards were evaluated, and normalized protein expression values were found to allow for protein profiling across a panel of morphologically diverse cells, revealing putative patterns of over- and underexpression. Using this approach, proteins with stable expression as well as cell-line specific expression were identified. The results demonstrate the value of large-scale, automated proteome analysis using immunohistochemistry, in revealing functional correlations and establishing methods to interpret and mine proteomic data.
    • "When fluorescence levels of the hml::YFP reporter were plotted against cell volume it was found that there was a simple linear relationship between the two, irrespective of whether volume had been changed by ploidy or by heterozygous deletion of dosage dependent cell size genes in the diploid cell. This suggests that there may be a general increase in protein levels relating to cell volume; a study of human cells has indicated that protein level is generally dependent on cell size over a wide size range [25]. The increase in protein expression in diploids versus haploid yeast may be required to maintain protein concentration balances in a larger cell. "
    [Show abstract] [Hide abstract] ABSTRACT: The repression of genes in regions of heterochromatin is known as transcriptional silencing. It occurs in a wide range of organisms and can have importance in adaptation to the environment, developmental changes and disease. The model organism Saccharomyces cerevisiae has been used for many years to study transcriptional silencing, but until recently no study has been made in relation to ploidy. The aim of this work was to compare transcriptional silencing in haploids and diploids at both telomeres and the hidden mating-type (HM) loci. Transcriptional silencing was assayed, by growth on 5-fluoroorotic acid (5-FOA) media or by flow cytometry, on strains where a telomere or HM locus was marked. RNA levels were measured by quantitative RT-PCR to confirm that effects were transcriptional. 5-FOA assays and flow cytometry were consistent with transcriptional silencing at telomeres and at HML being reduced as ploidy increases which agreed with conclusions in previous publications. However, QRT-PCR revealed that transcriptional silencing was unaffected by ploidy and thus protein levels were increasing independently of RNA levels. At telomere XI left (XI-L), changes in protein level were strongly influenced by mating-type, whereas at HML mating-type had much less influence. The post-transcriptional effects seen in this study, illustrate the often ignored need to measure RNA levels when assaying transcriptional silencing in Saccharomyces cerevisiae.
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    • "It should be noted that IHC as well as MS are limited by a lower level of sensitivity and resolution. This is exemplified by a previous study, in which mRNA levels were compared with protein levels, as detected using SILAC-based MS and antibody-based confocal microscopy, showing that lowabundant transcripts, as exemplified by the functional group of G protein-coupled receptors (GPCRs), were often not detected on a protein level [21] . Within the Human Protein Atlas project, the three cell lines routinely analyzed using IHC as well as IF have also been analyzed using next-generation RNA sequencing using the Illumina system (Illumina Inc. "
    [Show abstract] [Hide abstract] ABSTRACT: In this review, we present an update on the progress of the Human Protein Atlas, with an emphasis on strategies for validating immunohistochemistry-based protein expression patterns and on the possibilities to extend the map of protein expression patterns for cancer research projects. The objectives underlying the Human Protein Atlas include (i) the generation of validated antibodies toward a major isoform of all proteins encoded by the human genome, (ii) creating an information database of protein expression patterns in normal human tissues, in cells, and in cancer, and (iii) utilizing generated antibodies and protein expression data as tools to identify clinically useful biomarkers. The success of such an effort is dependent on the validity of antibodies as specific binders of intended targets in applications used to map protein expression patterns. The development of strategies to support specific target binding is crucial and remains a challenge as a large fraction of proteins encoded by the human genome is poorly characterized, including the approximately one-third of all proteins lacking evidence of existence. Conceivable methods for validation include the use of paired antibodies, i.e. two independent antibodies targeting different and nonoverlapping epitopes on the same protein as well as comparative analysis of mRNA expression patterns with corresponding proteins.
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    • "As all the immunohistochemical images from the TMAs were manually annotated by pathologists involving subjective scoring, we decided to carry out the same analysis on 45 human cell lines in which an automated image analysis algorithm have been used (Stromberg et al, 2007; Lundberg et al, 2008). The data from 5349 antibodies corresponding to 4349 genes were analyzed, involving more than 450 000 additional images, and the results are shown inFigure 3. A pattern of protein expression similar to that for tissues and organs was recorded for the in vitro cultured cells, with most proteins expressed in the majority of the 45 cell lines (Figure 3A) and nearly 80% of the proteins expressed across all the analyzed human cell lines (Figure 3B and Supplemen- taryTable S3). "
    [Show abstract] [Hide abstract] ABSTRACT: Defining the protein profiles of tissues and organs is critical to understanding the unique characteristics of the various cell types in the human body. In this study, we report on an anatomically comprehensive analysis of 4842 protein profiles in 48 human tissues and 45 human cell lines. A detailed analysis of over 2 million manually annotated, high-resolution, immunohistochemistry-based images showed a high fraction (>65%) of expressed proteins in most cells and tissues, with very few proteins (<2%) detected in any single cell type. Similarly, confocal microscopy in three human cell lines detected expression of more than 70% of the analyzed proteins. Despite this ubiquitous expression, hierarchical clustering analysis, based on global protein expression patterns, shows that the analyzed cells can be still subdivided into groups according to the current concepts of histology and cellular differentiation. This study suggests that tissue specificity is achieved by precise regulation of protein levels in space and time, and that different tissues in the body acquire their unique characteristics by controlling not which proteins are expressed but how much of each is produced.
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