Techniques for systematically monitoring protein translation have lagged far behind methods for measuring messenger RNA (mRNA) levels. Here, we present a ribosome-profiling strategy that is based on the deep sequencing of ribosome-protected mRNA fragments and enables genome-wide investigation of translation with subcodon resolution. We used this technique to monitor translation in budding yeast under both rich and starvation conditions. These studies defined the protein sequences being translated and found extensive translational control in both determining absolute protein abundance and responding to environmental stress. We also observed distinct phases during translation that involve a large decrease in ribosome density going from early to late peptide elongation as well as widespread regulated initiation at non-adenine-uracil-guanine (AUG) codons. Ribosome profiling is readily adaptable to other organisms, making high-precision investigation of protein translation experimentally accessible.The ability to monitor the identity and quantity of proteins that a cell produces would inform nearly all aspects of biology. Microarray-based measurements of mRNA abundance have revolutionized the study of gene expression (1). However, for several reasons there is a critical need for techniques that directly monitor protein synthesis. First, mRNA levels are an imperfect proxy for protein production because mRNA translation is subject to extensive regulation (2-4). Second predicting the exact protein product from the transcript sequence is not possible because of effects such as internal ribosome entry sites, initiation at non-AUG codons, and nonsense read-through (5,6). Finally, programmed ribosomal pausing during protein synthesis is thought to aid the cotranslational folding and secretion of some proteins (7-9).Polysome profiling, in which mRNAs are recovered from translating ribosomes for subsequent microarray analysis, can provide a useful estimate of protein synthesis (10). However, this approach suffers from limited resolution and accuracy. Additionally, upstream open reading frames (uORFs)-short translated sequences found in the 5′ untranslated region (5′UTR) of many genes-result in ribosomes that are bound to an mRNA and yet are not translating the encoded gene (11). Advances in quantitative proteomics circumvent some of these problems (2,3), but there currently are substantial limits on their ability to independently determine protein sequences and measure low-abundance proteins.The position of a translating ribosome can be precisely determined by using the fact that a ribosome protects a discrete footprint [∼30 nucleotides (nt)] on its mRNA template from nuclease digestion (12). We reasoned that advances in deep-sequencing technology, which NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript make it possible to read tens of millions of short (∼35 base pairs) DNA sequences in parallel (13), would allow the full analysis of ribosome footprints from cells. Here, we present a ribosome-...

The availability of complete genomic sequences and technologies that allow comprehensive analysis of global expression profiles of messenger RNA have greatly expanded our ability to monitor the internal state of a cell. Yet biological systems ultimately need to be explained in terms of the activity, regulation and modification of proteins--and the ubiquitous occurrence of post-transcriptional regulation makes mRNA an imperfect proxy for such information. To facilitate global protein analyses, we have created a Saccharomyces cerevisiae fusion library where each open reading frame is tagged with a high-affinity epitope and expressed from its natural chromosomal location. Through immunodetection of the common tag, we obtain a census of proteins expressed during log-phase growth and measurements of their absolute levels. We find that about 80% of the proteome is expressed during normal growth conditions, and, using additional sequence information, we systematically identify misannotated genes. The abundance of proteins ranges from fewer than 50 to more than 10(6) molecules per cell. Many of these molecules, including essential proteins and most transcription factors, are present at levels that are not readily detectable by other proteomic techniques nor predictable by mRNA levels or codon bias measurements.

A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Bulk protein abundance measurements of >2,500 proteins in rich and minimal media provide a detailed view of the cellular response to these conditions, and capture many changes not observed by DNA microarray analyses. Our single-cell data argue that noise in protein expression is dominated by the stochastic production/destruction of messenger RNAs. Beyond this global trend, there are dramatic protein-specific differences in noise that are strongly correlated with a protein's mode of transcription and its function. For example, proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet. Thus, these studies reveal a remarkable structure to biological noise and suggest that protein noise levels have been selected to reflect the costs and potential benefits of this variation.

Fig. 2. (A)Interaction web of top-down and bottom-up effects in the eelgrass study system. The top predator is the sea otter (E. lutris), the mesopredators are crabs (Cancer spp. and Pugettia producta), the epiphyte mesograzers are primarily an isopod (I. resecata) and a sea slug (P. taylori), and algal epiphyte competitors of eelgrass primarily consist of chain-forming diatoms, and the red alga Smithora naiadum. Solid arrows indicate direct effects, dashed arrows indicate indirect effects, and the plus and minus symbols indicate positive and/or negative effects on trophic guilds and eelgrass condition. C, competitive interaction; T, trophic interaction. (Original artwork by A. C. Hughes.) (B-E) Survey results testing for the effects of sea otter density on eelgrass bed community properties (Tables S2 and S3). Elkhorn Slough (sea otters present and high nutrients) eelgrass beds (n = 4) are coded in red, and the Tomales Bay reference site (no sea otters, low nutrients) beds (n = 4) are coded in blue. (B) Crab biomass and size structure of two species of Cancer crabs; (C) grazer biomass per shoot and large grazer density; (D) algal epiphyte loading; and (E) aboveground and belowground eelgrass biomass. DW, dry weight; FW, fresh weight.

In proteomic research, it is often necessary to screen a large number of polypeptides for the presence of stable structure. Described here is a technique (referred to as SUPREX, stability of unpurified proteins from rates of H͞D exchange) for measuring the stability of proteins in a rapid, high-throughput fashion. The method uses hydrogen exchange to estimate the stability of microgram quantities of unpurified protein extracts by using matrix-assisted laser desorption͞ionization MS. T he function of a protein is contingent on the stability of its native conformation. Consequently, in the field of protein biochemistry, stability measurements frequently are performed to establish a polypeptide as a stably folded protein and to study the physical forces that lead to its folding (1). Stability measurements also provide important biological information; a decrease in stability can be a sign of misfolding, which in some proteins leads to disease (2), whereas an increase in stability can be indicative of ligand binding (3). Despite their utility, stability measurements currently necessitate time-consuming experiments with pure protein samples. In proteomic experiments (4), where a large number of polypeptides often need to be analyzed, stability measurements are not practical. We have developed the SUPREX (stability of unpurified proteins from rates of H͞D exchange) technique to rapidly screen a large number of protein samples for the presence of stable structure. The method uses hydrogen exchange coupled with matrix-assisted laser desorption͞ionization (MALDI) MS to obtain quantitative measurements of stability from crude extracts of recombinant Escherichia coli cultures grown in 96-well microtiter plates.Within a polypeptide, certain labile hydrogen atoms can exchange freely with the surrounding solvent. Native structure protects a subset of these hydrogens from exchange (5), and some of these protected protons exchange only if the protein globally unfolds (6). The stability of a protein can be analyzed by monitoring the exchange rates of these ''globally protected'' hydrogens (7). Protein hydrogen exchange rates typically are measured by allowing labile protons to exchange with D 2 O. The proton͞deuteron exchange reaction can be monitored by NMR (6) or MS (8). MS is experimentally more convenient than NMR for several reasons: it requires less protein, is faster and simpler to use, does not require complicated spectral assignments, and does not require pure protein samples. These advantages come at the expense of the residue-specific information NMR affords, but that information is not necessary for assessing global stability.Recent studies have demonstrated that hydrogen exchange coupled with electrospray ionization MS can qualitatively distinguish native-like proteins from unfolded polypeptides in partially purified samples (9) and can be used to study the kinetics and thermodynamics of folding (8, 10). In contrast, the experiments described here use MALDI MS to detect hydrogen exchange, an approach previously desc...

In a recent study, in vivo metabolic labeling using 15 N traced the rate of label incorporation among more than 1700 proteins simultaneously and enabled the determination of individual protein turnover rate constants over a dynamic range of three orders of magnitude (Price, J. C., Guan, S., Burlingame, A., Prusiner, S. B., and Ghaemmaghami, S. (2010) Analysis of proteome dynamics in the mouse brain. Proc. Natl. Acad. Sci. U. S. A. 107, 14508 -14513). These studies of protein dynamics provide a deeper understanding of healthy development and wellbeing of complex organisms, as well as the possible causes and progression of disease. In addition to a fully labeled food source and appropriate mass spectrometry platform, an essential and enabling component of such large scale investigations is a robust data processing and analysis pipeline, which is capable of the reduction of large sets of liquid chromatography tandem MS raw data files into the desired protein turnover rate constants. The data processing pipeline described in this contribution is comprised of a suite of software modules required for the workflow that fulfills such requirements. This software platform includes established software tools such as a mass spectrometry database search engine together with several additional, novel data processing modules specifically developed for 15 N metabolic labeling. These fulfill the following functions: (1) cross-extraction of 15 N-containing ion intensities from raw data files at varying biosynthetic incorporation times, (2) computation of peptide 15 N isotopic incorporation distributions, and (3) aggregation of relative isotope abundance curves for multiple peptides into single protein curves. In addition, processing parameter optimization and noise reduction procedures were found to be necessary in the processing modules in order to reduce

Quinacrine is a potent antiprion compound in cell culture models of prion disease but has failed to show efficacy in animal bioassays and human clinical trials. Previous studies demonstrated that quinacrine inefficiently penetrates the blood-brain barrier (BBB), which could contribute to its lack of efficacy in vivo. As quinacrine is known to be a substrate for P-glycoprotein multi-drug resistance (MDR) transporters, we circumvented its poor BBB permeability by utilizing MDR0/0 mice that are deficient in mdr1a and mdr1b genes. Mice treated with 40 mg/kg/day of quinacrine accumulated up to 100 µM of quinacrine in their brains without acute toxicity. PrPSc levels in the brains of prion-inoculated MDR0/0 mice diminished upon the initiation of quinacrine treatment. However, this reduction was transient and PrPSc levels recovered despite the continuous administration of quinacrine. Treatment with quinacrine did not prolong the survival times of prion-inoculated, wild-type or MDR0/0 mice compared to untreated mice. A similar phenomenon was observed in cultured differentiated prion-infected neuroblastoma cells: PrPSc levels initially decreased after quinacrine treatment then rapidly recovered after 3 d of continuous treatment. Biochemical characterization of PrPSc that persisted in the brains of quinacrine-treated mice had a lower conformational stability and different immunoaffinities compared to that found in the brains of untreated controls. These physical properties were not maintained upon passage in MDR0/0 mice. From these data, we propose that quinacrine eliminates a specific subset of PrPSc conformers, resulting in the survival of drug-resistant prion conformations. Transient accumulation of this drug-resistant prion population provides a possible explanation for the lack of in vivo efficacy of quinacrine and other antiprion drugs.

A new method that utilizes matrix-assisted laser desorption/ionization (MALDI) mass spectrometry and exploits the hydrogen/deuterium (H/D) exchange properties of proteins was developed for measuring the thermodynamic properties of protein-ligand complexes in solution. Dissociation constants (Kd values) determined by the method for five model protein-ligand complexes that included those with small molecules, nucleic acids, peptides, and other proteins were generally in good agreement with Kd values measured by conventional methods. Important experimental advantages of the described method over existing methods include: the ability to make measurements in a high-throughput and automated fashion, the ability to make measurements using only picomole quantitities of protein, and the ability to analyze either purified or unpurified protein-ligand complexes.