Won-Ki Huh

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.

Rewiring of Genetic Networks in Response to DNA Damage

DNA Damage Pathways Revealed Despite the dynamic nature of cellular responses, the genetic networks that govern these responses have been mapped primarily as static snapshots. Bandyopadhyay et al. (p. 1385; see the Perspective by Friedman and Schuldiner) report a comparison of large genetic interactomes measured among all yeast kinases, phosphatases, and transcription factors, as the cell responded to DNA damage. The interactomes revealed were highly dynamic structures that changed dramatically with changing conditions. These dynamic interactions reveal genetic relationships that can be more effective than classical “static” interactions (for example, synthetic lethals and epistasis maps) in identifying pathways of interest. A network comparison of genetic interactions mapped at two conditions reveals genetic responses to DNA damage in yeast. Although cellular behaviors are dynamic, the networks that govern these behaviors have been mapped primarily as static snapshots. Using an approach called differential epistasis mapping, we have discovered widespread changes in genetic interaction among yeast kinases, phosphatases, and transcription factors as the cell responds to DNA damage. Differential interactions uncover many gene functions that go undetected in static conditions. They are very effective at identifying DNA repair pathways, highlighting new damage-dependent roles for the Slt2 kinase, Pph3 phosphatase, and histone variant Htz1. The data also reveal that protein complexes are generally stable in response to perturbation, but the functional relations between these complexes are substantially reorganized. Differential networks chart a new type of genetic landscape that is invaluable for mapping cellular responses to stimuli.

Copper- and zinc-containing superoxide dismutase (Cu/ZnSOD) is required for the protection of Candida albicans against oxidative stresses and the expression of its full virulence

Copper- and zinc-containing superoxide dismutase (Cu/ZnSOD) is suspected to be one of the anti-oxidant enzymes and virulence determinants active in some pathogenic micro-organisms. To elucidate the role of Cu/ZnSOD in the major human fungal pathogen Candida albicans, its gene, designated SOD1, was disrupted by the URA-blaster technique. The resulting sod1/sod1 mutant showed delayed hyphal growth on Spider medium but could still form hyphae on other solid media or in liquid media, particularly in response to serum. Moreover, the sod1/sod1 mutant was more sensitive to menadione, a redox-cycling agent, than the isogenic wild-type strain, although it still showed an adaptive oxidative stress response. Furthermore, the sod1/sod1 mutant cells exhibited slow growth in minimal medium when compared to the wild-type cells, but their growth was restored by the addition of lysine to the medium. Interestingly, C. albicans cells lacking Cu/ZnSOD showed increased susceptibility to macrophage attack and had attenuated virulence in mice. Thus, these results suggest that Cu/ZnSOD is required for the protection of C. albicans against oxidative stresses and for the full virulence of the organism to be expressed.

Bimolecular fluorescence complementation analysis system for in vivo detection of protein-protein interaction in Saccharomyces cerevisiae.

The bimolecular fluorescence complementation (BiFC) assay has been widely accepted for studying in vivo detection of protein–protein interactions in several organisms. To facilitate the application of the BiFC assay to yeast research, we have created a series of plasmids that allow single‐step, PCR‐based C‐ or N‐terminal tagging of yeast proteins with yellow fluorescent protein fragments for BiFC assay. By examination of several interacting proteins (Sis1–Sis1, Net1–Sir2, Cet1–Cet1 and Pho2–Pho4), we demonstrate that the BiFC assay can be used to reliably analyse the occurrence and subcellular localization of protein–protein interactions in living yeast cells. The sequences for the described plasmids were submitted to the GenBank under Accession Nos: EF210802, pFA6a‐VN‐His3MX6; EF210803, pFA6a‐VC‐His3MX6; EF210804, pFA6a‐VN‐TRP1; EF210807, pFA6a‐VC‐TRP1; EF210808, pFA6a‐VN‐kanMX6; EF210809, pFA6a‐VC‐kanMX6; EF210810, pFA6a‐His3MX6‐PGAL1‐VN; EF210805, pFA6a‐His3MX6‐PGAL1‐VC; EF210806, pFA6a‐TRP1‐PGAL1‐VN; EF210811, pFA6a‐TRP1‐PGAL1‐VC; EF210812, pFA6a‐kanMX6‐PGAL1‐VN; EF210813, pFA6a‐kanMX6‐PGAL1‐VC; EF521883, pFA6a‐His3MX6‐PCET1‐VN; EF521884, pFA6a‐His3MX6‐PCET1‐VC; EF521885, pFA6a‐TRP1‐PCET1‐VN; EF521886, pFA6a‐TRP1‐PCET1‐VC; EF521887, pFA6a‐kanMX6‐PCET1‐VN; EF521888, pFA6a‐kanMX6‐PCET1‐VC. Copyright

Interactomic study on interaction between lipid droplets and mitochondria

An increasing body of evidence shows that the lipid droplet, a neutral lipid storage organelle, plays a role in lipid metabolism and energy homeostasis through its interaction with mitochondria. However, the cellular functions and molecular mechanisms of the interaction remain ambiguous. Here we present data from transmission electron microscopy, fluorescence imaging, and reconstitution assays, demonstrating that lipid droplets physically contact mitochondria in vivo and in vitro. Using a bimolecular fluorescence complementation assay in Saccharomyces cerevisiae, we generated an interactomic map of protein-protein contacts of lipid droplets with mitochondria and peroxisomes. The lipid droplet proteins Erg6 and Pet10 were found to be involved in 75% of the interactions detected. Interestingly, interactions between 3 pairs of lipid metabolic enzymes were detected. Collectively, these data demonstrate that lipid droplets make physical contacts with mitochondria and peroxisomes, and reveal specific molecular interactions that suggest active participation of lipid droplets in lipid metabolism in yeast.

Protein networks markedly improve prediction of subcellular localization in multiple eukaryotic species

The function of a protein is intimately tied to its subcellular localization. Although localizations have been measured for many yeast proteins through systematic GFP fusions, similar studies in other branches of life are still forthcoming. In the interim, various machine-learning methods have been proposed to predict localization using physical characteristics of a protein, such as amino acid content, hydrophobicity, side-chain mass and domain composition. However, there has been comparatively little work on predicting localization using protein networks. Here, we predict protein localizations by integrating an extensive set of protein physical characteristics over a proteins extended protein–protein interaction neighborhood, using a classification framework called ‘Divide and Conquer k-Nearest Neighbors’ (DC-kNN). These predictions achieve significantly higher accuracy than two well-known methods for predicting protein localization in yeast. Using new GFP imaging experiments, we show that the network-based approach can extend and revise previous annotations made from high-throughput studies. Finally, we show that our approach remains highly predictive in higher eukaryotes such as fly and human, in which most localizations are unknown and the protein network coverage is less substantial.

Bimolecular fluorescence complementation (BiFC) analysis: advances and recent applications for genome-wide interaction studies

Complex protein networks are involved in nearly all cellular processes. To uncover these vast networks of protein interactions, various high-throughput screening technologies have been developed. Over the last decade, bimolecular fluorescence complementation (BiFC) assay has been widely used to detect protein-protein interactions (PPIs) in living cells. This technique is based on the reconstitution of a fluorescent protein in vivo. Easy quantification of the BiFC signals allows effective cell-based high-throughput screenings for protein binding partners and drugs that modulate PPIs. Recently, with the development of large screening libraries, BiFC has been effectively applied for genome-wide PPI studies and has uncovered novel protein interactions, providing new insight into protein functions. In this review, we describe the development of reagents and methods used for BiFC-based screens in yeast, plants, and mammalian cells. We also discuss the advantages and drawbacks of these methods and highlight the application of BiFC in large-scale studies.

Ssn6, an important factor of morphological conversion and virulence in Candida albicans

Candida albicans , the major fungal pathogen in humans, undergoes morphological conversion from yeasts to filamentous growth forms depending upon various environmental conditions. Here, we have identified a C. albicans gene, namely SSN6 , encoding a putative global transcriptional co‐repressor that is highly homologous to the Saccharomyces cerevisiae Ssn6. The isolated C. albicans SSN6 complemented the pleiotropic phenotypes of S. cerevisiae ssn6 mutation, and its expression levels declined significantly in response to a strong true hyphal inducer, serum. The mutant lacking C. albicans Ssn6 displayed a stubby pseudohyphal growth pattern, derepressed filament‐specific genes in response to elevated temperature 37°C and failed to develop true hyphae, extensive filamentation and virulence. Such morphological defects of ssn6 / ssn6 mutant were not rescued by overexpression of Tup1, Cph1 or Efg1. Moreover, epistatic analysis showed that, as far as cell morphology was concerned, Ssn6 was epistatic to Tup1 at the higher temperature but that, at the lower temperature, the ssn6 / ssn6 tup1 / tup1 double mutant grew in a stubby form of pseudohyphae distinct from the phenotypes of either single mutant. Furthermore, overexpression of SSN6 in C. albicans led to enhanced filamentous growth and attenuated virulence. These findings suggest that Ssn6 may function as an activator as well as a repressor of filamentous growth and be a target for candidacidal drugs, as its excess or deficiency resulted in impaired virulence.

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.