Conserved substitution patterns around nucleosome footprints in eukaryotes and Archaea derive from frequent nucleosome repositioning through evolution.

Nucleosomes, the basic repeat units of eukaryotic chromatin, have been suggested to influence the evolution of eukaryotic genomes, both by altering the propensity of DNA to mutate and by selection acting to maintain or exclude nucleosomes in particular locations. Contrary to the popular idea that nucleosomes are unique to eukaryotes, histone proteins have also been discovered in some archaeal genomes. Archaeal nucleosomes, however, are quite unlike their eukaryotic counterparts in many respects, including their assembly into tetramers (rather than octamers) from histone proteins that lack N- and C-terminal tails. Here, we show that despite these fundamental differences the association between nucleosome footprints and sequence evolution is strikingly conserved between humans and the model archaeon Haloferax volcanii. In light of this finding we examine whether selection or mutation can explain concordant substitution patterns in the two kingdoms. Unexpectedly, we find that neither the mutation nor the selection model are sufficient to explain the observed association between nucleosomes and sequence divergence. Instead, we demonstrate that nucleosome-associated substitution patterns are more consistent with a third model where sequence divergence results in frequent repositioning of nucleosomes during evolution. Indeed, we show that nucleosome repositioning is both necessary and largely sufficient to explain the association between current nucleosome positions and biased substitution patterns. This finding highlights the importance of considering the direction of causality between genetic and epigenetic change

A comparative analysis of DNA barcode microarray feature size

<p>Abstract</p> <p>Background</p> <p>Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density), but this increase in resolution can compromise sensitivity.</p> <p>Results</p> <p>We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO) collection used for screens of pooled yeast (<it>Saccharomyces cerevisiae</it>) deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be <it>ALG7</it>.</p> <p>Conclusion</p> <p>We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.</p

Systematic analysis of genome-wide fitness data in yeast reveals novel gene function and drug action

The relationship between co-fitness and co-inhibition of genes in chemicogenomic yeast screens provides insights into gene function and drug target prediction

Reverse Chemical Genetics: Comprehensive Fitness Profiling Reveals the Spectrum of Drug Target Interactions

The emergence and prevalence of drug resistance demands streamlined strategies to identify drug resistant variants in a fast, systematic and cost-effective way. Methods commonly used to understand and predict drug resistance rely on limited clinical studies from patients who are refractory to drugs or on laborious evolution experiments with poor coverage of the gene variants. Here, we report an integrative functional variomics methodology combining deep sequencing and a Bayesian statistical model to provide a comprehensive list of drug resistance alleles from complex variant populations. Dihydrofolate reductase, the target of methotrexate chemotherapy drug, was used as a model to identify functional mutant alleles correlated with methotrexate resistance. This systematic approach identified previously reported resistance mutations, as well as novel point mutations that were validated in vivo. Use of this systematic strategy as a routine diagnostics tool widens the scope of successful drug research and development

Discovery of novel small molecule modulators of Clavibacter michiganensis subsp. michiganensis

Clavibacter michiganensis subsp. michiganensis (Cmm) is a Gram-positive seed-transmitted bacterial phytopathogen responsible for substantial economic losses by adversely affecting tomato production worldwide. A high-throughput, cell-based screen was adapted to identify novel small molecule growth inhibitors to serve as leads for future bactericide development. A library of 4,182 compounds known to be bioactive against Saccharomyces cerevisiae was selected for primary screening against Cmm wild-type strain C290 for whole-cell growth inhibition. Four hundred sixty-eight molecules (11.2% hit rate) were identified as bacteriocidal or bacteriostatic against Cmm at 200 M. Seventy-seven candidates were selected based on Golden Triangle analyses for secondary screening. Secondary screens showed that several of these candidates were strain-selective. Several compounds were inhibitory to multiple Cmm strains as well as Bacillus subtilis, but not Pseudomonas fluorescens, Mitsuaria sp., Lysobacter enzymogenes, Lactobacillus rhamnosus, Bifidobacter animalis, or Escherichia coli. Most of the compounds were not phytotoxic and did not show overt host toxicity. Using a novel 96-well bioluminescent Cmm seedling infection assay, we assessed effects of selected compounds on pathogen infection. The 12 most potent novel molecules were identified by compiling the scores from all secondary screens combined with the reduction of pathogen infection in planta. When tested for ability to develop resistance to the top-12 compounds, no resistant Cmm were recovered, suggesting that the discovered compounds are unlikely to induce resistance. In conclusion, here we report top-12 compounds that provide chemical scaffolds for future Cmm-specific bactericide development

Novel insights into iron metabolism by integrating deletome and transcriptome analysis in an iron deficiency model of the yeast Saccharomyces cerevisiae

<p>Abstract</p> <p>Background</p> <p>Iron-deficiency anemia is the most prevalent form of anemia world-wide. The yeast <it>Saccharomyces cerevisiae </it>has been used as a model of cellular iron deficiency, in part because many of its cellular pathways are conserved. To better understand how cells respond to changes in iron availability, we profiled the yeast genome with a parallel analysis of homozygous deletion mutants to identify essential components and cellular processes required for optimal growth under iron-limited conditions. To complement this analysis, we compared those genes identified as important for fitness to those that were differentially-expressed in the same conditions. The resulting analysis provides a global perspective on the cellular processes involved in iron metabolism.</p> <p>Results</p> <p>Using functional profiling, we identified several genes known to be involved in high affinity iron uptake, in addition to novel genes that may play a role in iron metabolism. Our results provide support for the primary involvement in iron homeostasis of vacuolar and endosomal compartments, as well as vesicular transport to and from these compartments. We also observed an unexpected importance of the peroxisome for growth in iron-limited media. Although these components were essential for growth in low-iron conditions, most of them were not differentially-expressed. Genes with altered expression in iron deficiency were mainly associated with iron uptake and transport mechanisms, with little overlap with those that were functionally required. To better understand this relationship, we used expression-profiling of selected mutants that exhibited slow growth in iron-deficient conditions, and as a result, obtained additional insight into the roles of <it>CTI6</it>, <it>DAP1</it>, <it>MRS4 </it>and <it>YHR045W </it>in iron metabolism.</p> <p>Conclusion</p> <p>Comparison between functional and gene expression data in iron deficiency highlighted the complementary utility of these two approaches to identify important functional components. This should be taken into consideration when designing and analyzing data from these type of studies. We used this and other published data to develop a molecular interaction network of iron metabolism in yeast.</p

Genome-Wide Requirements for Resistance to Functionally Distinct DNA-Damaging Agents

The mechanistic and therapeutic differences in the cellular response to DNA-damaging compounds are not completely understood, despite intense study. To expand our knowledge of DNA damage, we assayed the effects of 12 closely related DNA-damaging agents on the complete pool of ~4,700 barcoded homozygous deletion strains of Saccharomyces cerevisiae. In our protocol, deletion strains are pooled together and grown competitively in the presence of compound. Relative strain sensitivity is determined by hybridization of PCR-amplified barcodes to an oligonucleotide array carrying the barcode complements. These screens identified genes in well-characterized DNA-damage-response pathways as well as genes whose role in the DNA-damage response had not been previously established. High-throughput individual growth analysis was used to independently confirm microarray results. Each compound produced a unique genome-wide profile. Analysis of these data allowed us to determine the relative importance of DNA-repair modules for resistance to each of the 12 profiled compounds. Clustering the data for 12 distinct compounds uncovered both known and novel functional interactions that comprise the DNA-damage response and allowed us to define the genetic determinants required for repair of interstrand cross-links. Further genetic analysis allowed determination of epistasis for one of these functional groups

Design, Synthesis, and Characterization of a Highly Effective Hog1 Inhibitor: A Powerful Tool for Analyzing MAP Kinase Signaling in Yeast

The Saccharomyces cerevisiae High-Osmolarity Glycerol (HOG) pathway is a conserved mitogen-activated protein kinase (MAPK) signal transduction system that often serves as a model to analyze systems level properties of MAPK signaling. Hog1, the MAPK of the HOG-pathway, can be activated by various environmental cues and it controls transcription, translation, transport, and cell cycle adaptations in response to stress conditions. A powerful means to study signaling in living cells is to use kinase inhibitors; however, no inhibitor targeting wild-type Hog1 exists to date. Herein, we describe the design, synthesis, and biological application of small molecule inhibitors that are cell-permeable, fast-acting, and highly efficient against wild-type Hog1. These compounds are potent inhibitors of Hog1 kinase activity both in vitro and in vivo. Next, we use these novel inhibitors to pinpoint the time of Hog1 action during recovery from G1 checkpoint arrest, providing further evidence for a specific role of Hog1 in regulating cell cycle resumption during arsenite stress. Hence, we describe a novel tool for chemical genetic analysis of MAPK signaling and provide novel insights into Hog1 action