A Proteomic Survey of Host and Virus Reveals Differential Dynamics

We studied the dynamics of the proteome of influenza virus A/PR/8/34 (H1N1) infected Madin-Darby canine kidney cells up to 12 hours post infection by mass spectrometry based quantitative proteomics using the approach of stable isotope labeling by amino acids in cell culture (SILAC). We identified 1311 cell proteins and, apart from the proton channel M2, all major virus proteins. Based on their abundance two groups of virus proteins could be distinguished being in line with the function of the proteins in genesis and formation of new virions. Further, the data indicate a correlation between the amount of proteins synthesized and their previously determined copy number inside the viral particle. We employed bioinformatic approaches such as functional clustering, gene ontology, and pathway (KEGG) enrichment tests to uncover co- regulated cellular protein sets, assigned the individual subsets to their biological function, and determined their interrelation within the progression of viral infection. For the first time we are able to describe dynamic changes of the cellular and, of note, the viral proteome in a time dependent manner simultaneously. Through cluster analysis, time dependent patterns of protein abundances revealed highly dynamic up- and/or down-regulation processes. Taken together our study provides strong evidence that virus infection has a major impact on the cell status at the protein level

Global quantification of mammalian gene expression control

Gene expression is a multistep process that involves the transcription, translation and turnover of messenger RNAs and proteins. Although it is one of the most fundamental processes of life, the entire cascade has never been quantified on a genome-wide scale. Here we simultaneously measured absolute mRNA and protein abundance and turnover by parallel metabolic pulse labelling for more than 5,000 genes in mammalian cells. Whereas mRNA and protein levels correlated better than previously thought, corresponding half-lives showed no correlation. Using a quantitative model we have obtained the first genome-scale prediction of synthesis rates of mRNAs and proteins. We find that the cellular abundance of proteins is predominantly controlled at the level of translation. Genes with similar combinations of mRNA and protein stability shared functional properties, indicating that half-lives evolved under energetic and dynamic constraints. Quantitative information about all stages of gene expression provides a rich resource and helps to provide a greater understanding of the underlying design principles

Alteration of Protein Levels during Influenza Virus H1N1 Infection in Host Cells: A Proteomic Survey of Host and Virus Reveals Differential Dynamics

<div><p>We studied the dynamics of the proteome of influenza virus A/PR/8/34 (H1N1) infected Madin-Darby canine kidney cells up to 12 hours post infection by mass spectrometry based quantitative proteomics using the approach of stable isotope labeling by amino acids in cell culture (SILAC). We identified 1311 cell proteins and, apart from the proton channel M2, all major virus proteins. Based on their abundance two groups of virus proteins could be distinguished being in line with the function of the proteins in genesis and formation of new virions. Further, the data indicate a correlation between the amount of proteins synthesized and their previously determined copy number inside the viral particle. We employed bioinformatic approaches such as functional clustering, gene ontology, and pathway (KEGG) enrichment tests to uncover co-regulated cellular protein sets, assigned the individual subsets to their biological function, and determined their interrelation within the progression of viral infection. For the first time we are able to describe dynamic changes of the cellular and, of note, the viral proteome in a time dependent manner simultaneously. Through cluster analysis, time dependent patterns of protein abundances revealed highly dynamic up- and/or down-regulation processes. Taken together our study provides strong evidence that virus infection has a major impact on the cell status at the protein level.</p></div

Scheme of samples subjected to mass spectrometry.

<p>Scheme of samples subjected to mass spectrometry.</p

Functional clustering of all estimated cellular proteins.

<p>All normalized time profiles were clustered by a fuzzy clustering algorithm to find modules of co-regulated proteins. Enrichment tests for gene ontology terms on each cluster were performed for all proteins with a membership value >0.5 (n =  number in brackets). The most significant terms are represented on the right panel (see also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094257#pone.0094257.s007" target="_blank">Table S3</a>).</p

a, Outline of the experimental setup (For details see Material and Methods.). b, Proteomic phenotyping of the influenza A/PR/8 infected MDCK cell proteome using GO annotations.

<p>Quantiles of the quantification histogram are indicated at the top of the heatmap. Each quantile was separately analyzed for gene ontology pathways and clustered for the z transformed p values. The most prominent representatives of (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094257#pone.0094257.s006" target="_blank">Table S2</a>) -represented biological processes of each quantile were selected and annotated in the right panel.</p

Time profile of viral proteins.

<p>Logarithmic presentation of the protein abundance fold change. For details see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094257#s3" target="_blank">Material and Methods</a>.</p

Schematic depiction of the steps of the viral life cycle and the associated host. proteins.

<p>Proteins were selected from the overlap between proteins identified by our approach and genes classified as essential for viral reproduction or interacting with viral proteins by Watanabe et al. 2010 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094257#pone.0094257-Karlas2" target="_blank">[68]</a>. These proteins were grouped according 453 to their function and put into context by the schematic graphics of the infection cycle.</p

Proteomic phenotyping of the influenza A/PR/8 infected MDCK cell proteome at 10 hrs p.i. using KEGG annotations.

<p>Quantiles of the quantification histogram are indicated at the top of the heatmap. Each quantile was separately analyzed for KEGG pathways and clustered for the z transformed p values. The most prominent representatives of all over-represented biological processes of each quantile were selected and annotated in the right panel.</p