Jonathan S. Weissman

Global analysis of protein localization in budding yeast

A fundamental goal of cell biology is to define the functions of proteins in the context of compartments that organize them in the cellular environment. Here we describe the construction and analysis of a collection of yeast strains expressing full-length, chromosomally tagged green fluorescent protein fusion proteins. We classify these proteins, representing 75% of the yeast proteome, into 22 distinct subcellular localization categories, and provide localization information for 70% of previously unlocalized proteins. Analysis of this high-resolution, high-coverage localization data set in the context of transcriptional, genetic, and protein–protein interaction data helps reveal the logic of transcriptional co-regulation, and provides a comprehensive view of interactions within and between organelles in eukaryotic cells.

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.

Mammalian microRNAs predominantly act to decrease target mRNA levels

MicroRNAs (miRNAs) are endogenous ∼22-nucleotide RNAs that mediate important gene-regulatory events by pairing to the mRNAs of protein-coding genes to direct their repression. Repression of these regulatory targets leads to decreased translational efficiency and/or decreased mRNA levels, but the relative contributions of these two outcomes have been largely unknown, particularly for endogenous targets expressed at low-to-moderate levels. Here, we use ribosome profiling to measure the overall effects on protein production and compare these to simultaneously measured effects on mRNA levels. For both ectopic and endogenous miRNA regulatory interactions, lowered mRNA levels account for most (≥84%) of the decreased protein production. These results show that changes in mRNA levels closely reflect the impact of miRNAs on gene expression and indicate that destabilization of target mRNAs is the predominant reason for reduced protein output.

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Identification of protein–protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization–time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein–protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein–protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.

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.

Functional and Genomic Analyses Reveal an Essential Coordination between the Unfolded Protein Response and ER-Associated Degradation

The unfolded protein response (UPR) regulates gene expression in response to stress in the endoplasmic reticulum (ER). We determined the transcriptional scope of the UPR using DNA microarrays. Rather than regulating only ER-resident chaperones and phospholipid biosynthesis, as anticipated from earlier work, the UPR affects multiple ER and secretory pathway functions. Studies of UPR targets engaged in ER-associated protein degradation (ERAD) reveal an intimate coordination between these responses: efficient ERAD requires an intact UPR, and UPR induction increases ERAD capacity. Conversely, loss of ERAD leads to constitutive UPR induction. Finally, simultaneous loss of ERAD and the UPR greatly decreases cell viability. Thus, the UPR and ERAD are dynamic responses required for the coordinated disposal of misfolded proteins even in the absence of acute stress.

CRISPR-Mediated Modular RNA-Guided Regulation of Transcription in Eukaryotes

The genetic interrogation and reprogramming of cells requires methods for robust and precise targeting of genes for expression or repression. The CRISPR-associated catalytically inactive dCas9 protein offers a general platform for RNA-guided DNA targeting. Here, we show that fusion of dCas9 to effector domains with distinct regulatory functions enables stable and efficient transcriptional repression or activation in human and yeast cells, with the site of delivery determined solely by a coexpressed short guide (sg)RNA. Coupling of dCas9 to a transcriptional repressor domain can robustly silence expression of multiple endogenous genes. RNA-seq analysis indicates that CRISPR interference (CRISPRi)-mediated transcriptional repression is highly specific. Our results establish that the CRISPR system can be used as a modular and flexible DNA-binding platform for the recruitment of proteins to a target DNA sequence, revealing the potential of CRISPRi as a general tool for the precise regulation of gene expression in eukaryotic cells.

Molecular Chaperones and Protein Quality Control

In living cells, both newly made and preexisting polypeptide chains are at constant risk for misfolding and aggregation. In accordance with the wide diversity of misfolded forms, elaborate quality-control strategies have evolved to counter these inevitable mishaps. Recent reports describe the removal of aggregates from the cytosol; reveal mechanisms for protein quality control in the endoplasmic reticulum; and provide new insight into two classes of molecular chaperones, the Hsp70 system and the AAA+ (Hsp100) unfoldases.

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.

Ribosome Profiling of Mouse Embryonic Stem Cells Reveals the Complexity and Dynamics of Mammalian Proteomes

The ability to sequence genomes has far outstripped approaches for deciphering the information they encode. Here we present a suite of techniques, based on ribosome profiling (the deep sequencing of ribosome-protected mRNA fragments), to provide genome-wide maps of protein synthesis as well as a pulse-chase strategy for determining rates of translation elongation. We exploit the propensity of harringtonine to cause ribosomes to accumulate at sites of translation initiation together with a machine learning algorithm to define protein products systematically. Analysis of translation in mouse embryonic stem cells reveals thousands of strong pause sites and unannotated translation products. These include amino-terminal extensions and truncations and upstream open reading frames with regulatory potential, initiated at both AUG and non-AUG codons, whose translation changes after differentiation. We also define a class of short, polycistronic ribosome-associated coding RNAs (sprcRNAs) that encode small proteins. Our studies reveal an unanticipated complexity to mammalian proteomes.