A high-throughput phenotypic screen based on a Citrobacter freundii AmpC reporter expressed in Escherichia coli was executed to discover novel inhibitors of bacterial cell wall synthesis, an attractive, well-validated target for antibiotic intervention. Here we describe the discovery and characterization of sulfonyl piperazine and pyrazole compounds, each with novel mechanisms of action. E. coli mutants resistant to these compounds display no cross-resistance to antibiotics of other classes. Resistance to the sulfonyl piperazine maps to LpxH, which catalyzes the fourth step in the synthesis of lipid A, the outer membrane anchor of lipopolysaccharide (LPS). To our knowledge, this compound is the first reported inhibitor of LpxH. Resistance to the pyrazole compound mapped to mutations in either LolC or LolE, components of the essential LolCDE transporter complex, which is required for trafficking of lipoproteins to the outer membrane. Biochemical experiments with E. coli spheroplasts showed that the pyrazole compound is capable of inhibiting the release of lipoproteins from the inner membrane. Both of these compounds have significant promise as chemical probes to further interrogate the potential of these novel cell wall components for antimicrobial therapy. IMPORTANCEThe prevalence of antibacterial resistance, particularly among Gram-negative organisms, signals a need for novel antibacterial agents. A phenotypic screen using AmpC as a sensor for compounds that inhibit processes involved in Gram-negative envelope biogenesis led to the identification of two novel inhibitors with unique mechanisms of action targeting Escherichia coli outer membrane biogenesis. One compound inhibits the transport system for lipoprotein transport to the outer membrane, while the other compound inhibits synthesis of lipopolysaccharide. These results indicate that it is still possible to uncover new compounds with intrinsic antibacterial activity that inhibit novel targets related to the cell envelope, suggesting that the Gram-negative cell envelope still has untapped potential for therapeutic intervention.

Uncovering genetic control of variation in ethanol tolerance in natural populations of yeast Saccharomyces cerevisiae is essential for understanding the evolution of fermentation, the dominant lifestyle of the species, and for improving efficiency of selection for strains with high ethanol tolerance, a character of great economic value for the brewing and biofuel industries. To date, as many as 251 genes have been predicted to be involved in influencing this character. Candidacy of these genes was determined from a tested phenotypic effect following gene knockout, from an induced change in gene function under an ethanol stress condition, or by mutagenesis. This article represents the first genomics approach for dissecting genetic variation in ethanol tolerance between two yeast strains with a highly divergent trait phenotype. We developed a simple but reliable experimental protocol for scoring the phenotype and a set of STR/SNP markers evenly covering the whole genome. We created a mapping population comprising 319 segregants from crossing the parental strains. On the basis of the data sets, we find that the tolerance trait has a high heritability and that additive genetic variance dominates genetic variation of the trait. Segregation at five QTL detected has explained $50% of phenotypic variation; in particular, the major QTL mapped on yeast chromosome 9 has accounted for a quarter of the phenotypic variation. We integrated the QTL analysis with the predicted candidacy of ethanol resistance genes and found that only a few of these candidates fall in the QTL regions.

Genome-wide association study (GWAS) has become an obvious general approach for studying traits of agricultural importance in higher plants, especially crops. Here, we present a GWAS of 32 morphologic and 10 agronomic traits in a collection of 615 barley cultivars genotyped by genome-wide polymorphisms from a recently developed barley oligonucleotide pool assay. Strong population structure effect related to mixed sampling based on seasonal growth habit and ear row number is present in this barley collection. Comparison of seven statistical approaches in a genome-wide scan for significant associations with or without correction for confounding by population structure, revealed that in reducing false positive rates while maintaining statistical power, a mixed linear model solution outperforms genomic control, structured association, stepwise regression control and principal components adjustment. The present study reports significant associations for sixteen morphologic and nine agronomic traits and demonstrates the power and feasibility of applying GWAS to explore complex traits in highly structured plant samples.

MicroRNAs (miRNAs) are increasingly implicated in regulating tumor malignance through their capacity to coordinately repress expression of tumor-related genes. Here, we show that overexpression of miR-194 in lung cancer cell lines, results in suppressing metastasis of lung cancer cells, while inhibiting its expression through 'miRNA sponge' promotes the cancer cells to metastasize. miR-194 expression is also found to be in strongly negative association with metastasis in clinical specimens of non-small cell lung cancer. We demonstrate that miR-194 directly targets both BMP1 and p27(kip1). The resulting downregulation of BMP1 leads to suppression of TGFβ activity and, thus, to downregulation of the expression of key oncogenic genes (matrix metalloproteinases MMP2 and MMP9). This leads, in turn, to decreased tumor invasion. In addition, the miRNA-194-induced suppression of p27(kip1) activates the RhoA pathway, producing enhanced development of actin stress fibers and impaired migration of cancer cells. These findings reveal two structurally independent but functionally linked branches of the regulatory and signaling pathway that together provide a bridge between the metastasis-depressing miRNA and the key genes that govern the malignancy of lung cancers.

BackgroundBread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution ‘nullisomic-tetrasomic’ lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression.ResultsWe discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss.ConclusionsWe conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution.