SummaryGene expression is a multistep process that involves transcription, translation and turnover of mRNAs 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 mRNA and protein abundance and turnover by parallel metabolic pulse labeling for more than 5,000 genes in mammalian cells. While mRNA and protein levels correlated better than previously thought, corresponding half-lives showed no correlation. Employing a quantitative model we obtain 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 stabilities shared functional properties, suggesting that half-lives evolved under energetic and dynamic constraints. Quantitative information about all stages of gene expression obtained in this study provides a rich resource and helps understanding the underlying design principles.

Animal microRNAs (miRNAs) regulate gene expression by inhibiting translation and/or by inducing degradation of target messenger RNAs. It is unknown how much translational control is exerted by miRNAs on a genome-wide scale. We used a new proteomic approach to measure changes in synthesis of several thousand proteins in response to miRNA transfection or endogenous miRNA knockdown. In parallel, we quantified mRNA levels using microarrays. Here we show that a single miRNA can repress the production of hundreds of proteins, but that this repression is typically relatively mild. A number of known features of the miRNA-binding site such as the seed sequence also govern repression of human protein synthesis, and we report additional target sequence characteristics. We demonstrate that, in addition to downregulating mRNA levels, miRNAs also directly repress translation of hundreds of genes. Finally, our data suggest that a miRNA can, by direct or indirect effects, tune protein synthesis from thousands of genes.

Protein-RNA interactions are fundamental to core biological processes, such as mRNA splicing, localization, degradation, and translation. We developed a photoreactive nucleotide-enhanced UV crosslinking and oligo(dT) purification approach to identify the mRNA-bound proteome using quantitative proteomics and to display the protein occupancy on mRNA transcripts by next-generation sequencing. Application to a human embryonic kidney cell line identified close to 800 proteins. To our knowledge, nearly one-third were not previously annotated as RNA binding, and about 15% were not predictable by computational methods to interact with RNA. Protein occupancy profiling provides a transcriptome-wide catalog of potential cis-regulatory regions on mammalian mRNAs and showed that large stretches in 3' UTRs can be contacted by the mRNA-bound proteome, with numerous putative binding sites in regions harboring disease-associated nucleotide polymorphisms. Our observations indicate the presence of a large number of mRNA binders with diverse molecular functions participating in combinatorial posttranscriptional gene-expression networks.

Posttranscriptional gene regulation relies on hundreds of RNA binding proteins (RBPs) but the function of most RBPs is unknown. The human RBP HuR/ELAVL1 is a conserved mRNA stability regulator. We used PAR-CLIP, a recently developed method based on RNA-protein crosslinking, to identify transcriptome-wide ∼26,000 HuR binding sites. These sites were on average highly conserved, enriched for HuR binding motifs and mainly located in 3' untranslated regions. Surprisingly, many sites were intronic, implicating HuR in mRNA processing. Upon HuR knockdown, mRNA levels and protein synthesis of thousands of target genes were downregulated, validating functionality. HuR and miRNA binding sites tended to reside nearby but generally did not overlap. Additionally, HuR knockdown triggered strong and specific upregulation of miR-7. In summary, we identified thousands of direct and functional HuR targets, found a human miRNA controlled by HuR, and propose a role for HuR in splicing.

Current methods for system-wide gene expression analysis detect changes in mRNA abundance, but neglect regulation at the level of translation. Pulse labeling with stable isotopes has been used to measure protein turnover rates, but this does not directly provide information about translation rates. Here, we developed pulsed stable isotope labeling by amino acids in cell culture (pSILAC) with two heavy isotope labels to directly quantify protein translation on a proteome-wide scale. We applied the method to cellular iron homeostasis as a model system and demonstrate that it can confidently identify proteins that are translationally regulated by iron availability.

No abstract

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.

It is of fundamental importance to understand how the individual processes of gene expression, transcription, and translation, as well as mRNA and protein stability, act in concert to produce dynamic cellular proteomes. We use the concept of response times to illustrate the relation between degradation processes and responsiveness of the proteome to system changes and to provide supporting experimental evidence: proteins with short response times tend to be more strongly up-regulated after 1 hour of TNFα stimulation than proteins with longer response times. Furthermore, based on process-dependent response times, we demonstrate that synthesis and degradation act in concert to enable rapid responses. Finally, by building on a previously published data set quantifying the mammalian gene expression cascade, we speculate on how combinations of stable and unstable mRNAs and proteins may be wired to transcriptional or translational regulation to support gene function.