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Mukherjee V, Steensels J, Lievens B, Van de Voorde I, Verplaetse A, Aerts G, Willems KA, Thevelein JM, Verstrepen KJ, Ruyters S Appl Microbiol Biotechnol. Springer Berlin Heidelberg; 2014 Sep 30;98(22):9483–98 Yeast/Beer&Wine Saccharomyces cerevisiae is the organism of choice for many food and beverage fermentations because it thrives in high-sugar and high-ethanol conditions. However, the conditions encountered in bioethanol fermentation pose specific challenges, including extremely high sugar and ethanol concentrations, high temperature, and the presence of specific toxic compounds. It is generally considered that exploring the natural biodiversity ofSaccharomyces strains may be an interesting route to find superior bioethanol strains and may also improve our understanding of the challenges faced by yeast cells during bioethanol fermentation. In this study, we phenotypically evaluated a large collection of diverse Saccharomyces strains on six selective traits relevant for bioethanol production with increasing stress intensity. Our results demonstrate a remarkably large phenotypicdiversity among different Saccharomyces species and among S. cerevisiae strains from different origins. Currently applied bioethanol strains showed a high tolerance to many of these relevant traits, but several other natural and industrial S. cerevisiae strains outcompeted the bioethanol strains for specific traits. These multitolerant strains performed well in fermentation experiments mimicking industrial bioethanol production. Together, our results illustrate the potential of phenotyping the natural biodiversity of yeasts to find superior industrial strains that may be used in bioethanolproduction or can be used as a basis for further strain improvement through genetic engineering, experimental evolution, or breeding. Additionally, our study provides a basis for new insights into the relationships between tolerance to different stressors.

Ruyters S, Mukherjee V, Verstrepen KJ, Thevelein JM, Willems KA, Lievens B.   J Ind Microbiol Biotechnol. Springer Berlin Heidelberg; 2015 Jan;42(1):39–48.   Yeast/Beer & Wine.   Bioethanol fermentations expose yeasts to a new, complex and challenging fermentation medium with specific inhibitors and sugar mixtures depending on the type of carbon source. It is, therefore, suggested that the natural diversity of yeasts should be further exploited in order to findyeasts with good ethanol yield in stressed fermentation media. In this study, we screened more than 50 yeast isolates of which we selected five isolates with promising features. The species Candida bombi, Wickerhamomyces anomalus and Torulaspora delbrueckii showed better osmo- and hydroxymethylfurfural tolerance than Saccharomyces cerevisiae. However, S. cerevisiae isolates had the highest ethanol yield in fermentation experiments mimicking high gravity fermentations (25 % glucose) and artificial lignocellulose hydrolysates (with a myriad of inhibitors). Interestingly, among two tested S. cerevisiae strains, a wild strain isolated from an oak tree performed better than Ethanol Red, a S. cerevisiae strain which is currently commonly used in industrial bioethanol fermentations. Additionally, a W. anomalus strain isolated from sugar beet thick juice was found to have a comparable ethanol yield, but needed longer fermentation time. Other non-Saccharomyces yeasts yielded lower ethanol amounts.

Lalonde S, Sero A, Pratelli R, Pilot G, Chen J, Sardi MI, Parsa SA, Kim DY, Acharya BR, Stein EV, Hu HC, Villiers F, Takeda K, Yang Y, Han YS, Schwacke R, Chiang W, Kato N, Loqué D, Assmann SM, Kwak JM, Schroeder JI, Rhee SY, Frommer WB Front Physiol. 2010 Sep 22;1:24 Yeast/2-Hybrid Interactions between membrane proteins and the soluble fraction are essential for signal transduction and for regulating nutrient transport. To gain insights into the membrane-based interactome, 3,852 open reading frames (ORFs) out of a target list of 8,383 representing membrane and signalingproteins from Arabidopsis thaliana were cloned into a Gateway-compatible vector. The mating-based split ubiquitin system was used to screen for potential protein-protein interactions (pPPIs) among 490 Arabidopsis ORFs. A binary robotic screen between 142 receptor-like kinases (RLKs), 72 transporters, 57 soluble protein kinases and phosphatases, 40 glycosyltransferases, 95 proteins of various functions, and 89 proteins with unknown function detected 387 out of 90,370 possible PPIs. A secondary screen confirmed 343 (of 386) pPPIs between 179 proteins, yielding a scale-freenetwork (r(2) = 0.863). Eighty of 142 transmembrane RLKs tested positive, identifying 3 homomers, 63 heteromers, and 80 pPPIs with other proteins. Thirty-one out of 142 RLK interactors (including RLKs) had previously been found to be phosphorylated; thus interactors may be substrates for respective RLKs. None of the pPPIs described here had been reported in the major interactome databases, including potential interactors of G-protein-coupled receptors, phospholipase C, and AMT ammonium transporters. Two RLKs found as putative interactors of AMT1;1 were independently confirmed using a split luciferase assay in Arabidopsis protoplasts. These RLKs may be involved in ammonium-dependent phosphorylation of the C-terminus and regulation of ammonium uptake activity. The robotic screening method established here will enable a systematic analysis of membrane protein interactions in fungi, plants and metazoa.

Reece-Hoyes JS, Diallo A, Lajoie B, Kent A, Shrestha S, Kadreppa S, Pesyna C, Dekker J, Myers CL, Walhout AJ Nat Methods. 2011 Oct 30;8(12):1059-64 Yeast/2-Hybrid A major challenge in systems biology is to understand the gene regulatory networks that drive development, physiology and pathology. Interactions between transcription factors and regulatory genomic regions provide the first level of gene control. Gateway-compatible yeast one-hybrid (Y1H)assays present a convenient method to identify and characterize the repertoire of transcription factors that can bind a DNA sequence of interest. To delineate genome-scale regulatory networks, however, large sets of DNA fragments need to be processed at high throughput and high coverage. Here we present enhanced Y1H (eY1H) assays that use a robotic mating platform with a set of improved Y1H reagents and automated readout quantification. We demonstrate that eY1H assays provide excellent coverage and identify interacting transcription factors for multiple DNA fragments in a short time. eY1H assays will be an important tool for mapping gene regulatory networks in Caenorhabditis elegans and other model organisms as well as in humans.

Hruby A, Zapatka M, Heucke S, Rieger L, Wu Y, Nussbaumer U, Timmermann S, Dünkler A, Johnsson N J Cell Sci. 2011 Jan 1;124(Pt 1):35–46 Yeast/2-Hybrid We used a generally applicable strategy to collect and structure the protein interactions of the yeast type II protein phosphatase Ptc1p and its binding partner Nbp2p. The procedure transformed primary unstructured protein interaction data into an ensemble of alternative interaction states. Certain combinations of proteins are allowed in different network configurations. Nbp2p serves as the network hub and brings seven kinases in close contact to Ptc1p. As a consequence, the deletion of NBP2 affects several cellular processes including organelle inheritance and the responses to mating hormone, cell wall stress and high osmolarity; it also impairs the proper execution of the morphogenetic program. Our constraint interactionmap provides a basis for understanding a subset of the observed phenotypes and assigns the Ptc1p-Nbp2p module a role in synchronizing the associated kinases during the cell cycle.

Chen J, Lalonde S, Obrdlik P, Noorani Vatani A, Parsa SA, Vilarino C, Revuelta JL, Frommer WB, Rhee SY Front Plant Sci. 2012;3:124 Yeast/2-Hybrid High-throughput data are a double-edged sword; for the benefit of large amount of data, there is an associated cost of noise. To increase reliability and scalability of high-throughput protein interaction data generation, we tested the efficacy of classification to enrich potential protein-proteininteractions. We applied this method to identify interactions among Arabidopsis membrane proteins enriched in transporters. We validated our method with multiple retests. Classification improved the quality of the ensuing interaction network and was effective in reducing the search space and increasing true positive rate. The final network of 541 interactions among 239 proteins (of which 179 are transporters) is the first proteininteraction network enriched in membrane transporters reported for any organism. This network has similar topological attributes to other publishedprotein interaction networks. It also extends and fills gaps in currently available biological networks in plants and allows building a number of hypotheses about processes and mechanisms involving signal-transduction and transport systems.

Xin X, Boone C, Thierry-Mieg N Methods Mol Biol. Totowa, NJ: Humana Press; 2012;812(Chapter 8):147–59 Yeast/2-Hybrid "Smart-pooling" is a strategy to achieve high efficiency, sensitivity, and specificity in large-scale yeast two-hybrid screening. In smart-pooling, reagents are multiplexed in a highly redundant manner and the positives can be read out on the final selection plates without the requirement of any extra experimental steps. We have shown that the Shifted Transversal Design (STD), a powerful theoretical construction for smart-pooling, can be used in yeast two-hybrid interactome mapping. STD pooling can achieve similar levels of sensitivity and specificity as one-on-one array-based yeast two-hybrid, while the costs and workloads are much lower. This chapter focuses on the construction and usage of STD arrays for large-scale yeast two-hybrid interactome mapping.

Jansen G, Määttänen P, Denisov AY, Scarffe L, Schade B, Balghi H, Dejgaard K, Chen LY, Muller WJ, Gehring K, Thomas DY Mol Cell Proteomics. 2012 Sep;11(9):710–23 Yeast/2-Hybrid Chaperones and foldases in the endoplasmic reticulum (ER) ensure correct protein folding. Extensive protein-protein interaction maps have defined the organization and function of many cellular complexes, but ER complexes are under-represented. Consequently, chaperone and foldase networks in the ER are largely uncharacterized. Using complementary ER-specific methods, we have mapped interactions between ER-lumenal chaperonesand foldases and describe their organization in multiprotein complexes. We identify new functional chaperone modules, including interactions between protein-disulfide isomerases and peptidyl-prolyl cis-trans-isomerases. We have examined in detail a novel ERp72-cyclophilin B complex that enhances the rate of folding of immunoglobulin G. Deletion analysis and NMR reveal a conserved surface of cyclophilin B that interacts with polyacidic stretches of ERp72 and GRp94. Mutagenesis within this highly charged surface region abrogates interactions with its chaperone partners and reveals a new mechanism of ER protein-protein interaction. This ability of cyclophilin B to interact with different partners using the same molecular surface suggests that ER-chaperone/foldase partnerships may switch depending on the needs of different substrates, illustrating the flexibility of multichaperone complexes of the ER folding machinery.

Gubelmann C, Waszak SM, Isakova A, Holcombe W, Hens K, Iagovitina A, Feuz JD, Raghav SK, Simicevic J, Deplancke B Mol Syst Biol. 2013;9:682 Yeast/2-Hybrid The comprehensive mapping of gene promoters and enhancers has significantly improved our understanding of how the mammalian regulatorygenome is organized. An important challenge is to elucidate how these regulatory elements contribute to gene expression by identifying their trans-regulatory inputs. Here, we present the generation of a mouse-specific transcription factor (TF) open-reading frame clone library and its implementation in yeast one-hybrid assays to enable large-scale protein-DNA interaction detection with mouse regulatory elements. Once specific interactions are identified, we then use a microfluidics-based method to validate and precisely map them within the respective DNA sequences. Using well-described regulatory elements as well as orphan enhancers, we show that this cross-platform pipeline characterizes known and uncovers many novel TF-DNA interactions. In addition, we provide evidence that several of these novel interactions are relevant in vivo and aid in elucidating the regulatory architecture of enhancers.

Nichols RJ, Sen S, Choo YJ, Beltrao P, Zietek M, Chaba R, Lee S, Kazmierczak KM, Lee KJ, Wong A, Shales M, Lovett S, Winkler ME, Krogan NJ, Typas A, Gross CA Cell. Elsevier; 2011 Jul 1;144(1):143–56 Bacteria/SGA The explosion of sequence information in bacteria makes developing high-throughput, cost-effective approaches to matching genes with phenotypes imperative. Using E. coli as proof of principle, we show that combining large-scale chemical genomics with quantitative fitness measurements provides a high-quality data set rich in discovery. Probing growth profiles of a mutant library in hundreds of conditions in parallel yielded > 10,000 phenotypes that allowed us to study gene essentiality, discover leads for gene function and drug action, and understand higher-order organization of the bacterial chromosome. We highlight new information derived from the study, including insights into a gene involved in multiple antibiotic resistance and the synergy between a broadly used combinatory antibiotic therapy, trimethoprim and sulfonamides. This data set, publicly available at http://ecoliwiki.net/tools/chemgen/, is a valuable resource for both the microbiological and bioinformatic communities, as it provides high-confidence associations between hundreds of annotated and uncharacterized genes as well as inferences about the mode of action of several poorly understood drugs.