Sina Ghaemmaghami

Global analysis of protein expression in yeast

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 106 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.

Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling

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.

Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise

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 proteins 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.

Analysis of proteome dynamics in the mouse brain

Advances in systems biology have allowed for global analyses of mRNA and protein expression, but large-scale studies of protein dynamics and turnover have not been conducted in vivo. Protein turnover is an important metabolic and regulatory mechanism in establishing proteome homeostasis, impacting many physiological and pathological processes. Here, we have used organism-wide isotopic labeling to measure the turnover rates of ~2,500 proteins in multiple mouse tissues, spanning four orders of magnitude. Through comparison of the brain with the liver and blood, we show that within the respective tissues, proteins performing similar functions often have similar turnover rates. Proteins in the brain have significantly slower turnover (average lifetime of 9.0 d) compared with those of the liver (3.0 d) and blood (3.5 d). Within some organelles (such as mitochondria), proteins have a narrow range of lifetimes, suggesting a synchronized turnover mechanism. Protein subunits within complexes of variable composition have a wide range of lifetimes, whereas those within well-defined complexes turn over in a coordinated manner. Together, the data represent the most comprehensive in vivo analysis of mammalian proteome turnover to date. The developed methodology can be adapted to assess in vivo proteome homeostasis in any model organism that will tolerate a labeled diet and may be particularly useful in the analysis of neurodegenerative diseases in vivo.

Quantitative protein stability measurement in vivo

The equilibrium between the native and denatured states of a protein can be key to its function and regulation. Traditionally, the folding equilibrium constant has been measured in vitro using purified protein and simple buffers. However, the biological environment of proteins can differ from these in vitro conditions in ways that could significantly perturb stability. Here, we present the first quantitative comparison between the stability of a protein in vitro and in the cytoplasm of Eschericia coli using amide hydrogen exchange detected by MALDI mass spectrometry (SUPREX). The results indicate that the thermodynamic stability of monomeric λ repressor within the cell is the same as its stability measured in a simple buffer in vitro. However, when the E. coli are placed in a hyperosmotic environment, the in vivo stability is greatly enhanced. The in vivo SUPREX method provides a general and quantitative way to measure protein stabilities in the cell and will be useful for applications where intracellular stability information provides important biological insights.

Continuous Quinacrine Treatment Results in the Formation of Drug-Resistant Prions

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.

Discovery of 2-aminothiazoles as potent antiprion compounds.

ABSTRACT Prion diseases are fatal, untreatable neurodegenerative diseases caused by the accumulation of the misfolded, infectious isoform of the prion protein (PrP), termed PrPSc. In an effort to identify novel inhibitors of prion formation, we utilized a high-throughput enzyme-linked immunosorbent assay (ELISA) to evaluate PrPSc reduction in prion-infected neuroblastoma cell lines (ScN2a). We screened a library of ∼10,000 diverse small molecules in 96-well format and identified 121 compounds that reduced PrPSc levels at a concentration of 5 μM. Four chemical scaffolds were identified as potential candidates for chemical optimization based on the presence of preliminary structure-activity relationships (SAR) derived from the primary screening data. A follow-up analysis of a group of commercially available 2-aminothiazoles showed this class as generally active in ScN2a cells. Our results establish 2-aminothiazoles as promising candidates for efficacy studies of animals and validate our drug discovery platform as a viable strategy for the identification of novel lead compounds with antiprion properties.

Cell division modulates prion accumulation in cultured cells

The phenotypic effect of prions on host cells is influenced by the physical properties of the prion strain and its level of accumulation. In mammalian cell cultures, prion accumulation is determined by the interplay between de novo prion formation, catabolism, cell division, and horizontal cell-to-cell transmission. Understanding this dynamic enables the analytical modeling of protein-based heritability and infectivity. Here, we quantitatively measured these competing effects in a subline of neuroblastoma (N2a) cells and propose a concordant reaction mechanism to explain the kinetics of prion propagation. Our results show that cell division leads to a predictable reduction in steady-state prion levels but not to complete clearance. Scrapie-infected N2a cells were capable of accumulating different steady-state levels of prions, dictated partly by the rate of cell division. We also show that prions in this subline of N2a cells are transmitted primarily from mother to daughter cells, rather than horizontal cell-to-cell transmission. We quantitatively modeled our kinetic results based on a mechanism that assumes a subpopulation of prions is capable of self-catalysis, and the levels of this subpopulation reach saturation in fully infected cells. Our results suggest that the apparent effectiveness of antiprion compounds in culture may be strongly influenced by the growth phase of the target cells.

A Data Processing Pipeline for Mammalian Proteome Dynamics Studies Using Stable Isotope Metabolic Labeling

In a recent study, in vivo metabolic labeling using 15N 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 well-being 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 15N metabolic labeling. These fulfill the following functions: (1) cross-extraction of 15N-containing ion intensities from raw data files at varying biosynthetic incorporation times, (2) computation of peptide 15N 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 propagation of errors in the long chain of the processing steps of the entire workflow.

Construction, verification and experimental use of two epitope-tagged collections of budding yeast strains.

A major challenge in the post-genomic era is the development of experimental approaches to monitor the properties of proteins on a proteome-wide level. It would be particularly useful to systematically assay protein subcellular localization, post-translational modifications and protein–protein interactions, both at steady state and in response to environmental stimuli. Development of new reagents and methods will enhance our ability to do so efficiently and systematically. Here we describe the construction of two collections of budding yeast strains that facilitate proteome-wide measurements of protein properties. These collections consist of strains with an epitope tag integrated at the C-terminus of essentially every open reading frame (ORF), one with the tandem affinity purification (TAP) tag, and one with the green fluorescent protein (GFP) tag. We show that in both of these collections we have accurately tagged a high proportion of all ORFs (approximately 75% of the proteome) by confirming expression of the fusion proteins. Furthermore, we demonstrate the use of the TAP collection in performing high-throughput immunoprecipitation experiments. Building on these collections and the methods described in this paper, we hope that the yeast community will expand both the quantity and type of proteome level data available.