CYSTM, a novel cysteine-rich transmembrane module with a role in stress tolerance across eukaryotes

Using sensitive sequence profile analysis, we identify a hitherto uncharacterized cysteine-rich, transmembrane (TM) module, CYSTM, found in a wide range of tail-anchored membrane proteins across eukaryotes. This superfamily includes Schizosaccharomyces Uvi15, Arabidopsis PCC1, Digtaria CDT1 and Saccharomyces proteins YDL012C and YDR210W, which have all been implicated in resistance/response to stress or pathogens. Based on the pattern of conserved cysteines and data from different chemical genetics studies, we suggest that CYSTM proteins might have critical role in responding to deleterious compounds at the plasma membrane via chelation or redox-based mechanisms. Thus, CYSTM proteins are likely to be part of a novel cellular protective mechanism that is widely active in eukaryotes, including humans

Comparative Analysis of the Global Transcriptome of Anopheles funestus from Mali, West Africa

Background: Anopheles funestus is a principal vector of malaria across much of tropical Africa and is considered one of the most efficient of its kind, yet studies of this species have lagged behind those of its broadly sympatric congener, An. gambiae. In aid of future genomic sequencing of An. funestus, we explored the whole body transcriptome, derived from mixed stage progeny of wild-caught females from Mali, West Africa. Principal Findings: Here we report the functional annotation and comparative genomics of 2,005 expressed sequence tags (ESTs) from An. funestus, which were assembled with a previous EST set from adult female salivary glands from the same mosquito. The assembled ESTs provided for a nonredundant catalog of 1,035 transcripts excluding mitochondrial sequences. Conclusions/Significance: Comparison of the An. funestus and An. gambiae transcriptomes using computational and macroarray approaches revealed a high degree of sequence identity despite an estimated 20–80 MY divergence time between lineages. A phylogenetically broader comparative genomic analysis indicated that the most rapidly evolving proteins – those involved in immunity, hematophagy, formation of extracellular structures, and hypothetical conserved proteins – are those that probably play important roles in how mosquitoes adapt to their nutritional and externa

A mammalian functional-genetic approach to characterizing cancer therapeutics

Supplementary information is available online at http://www.nature.com/naturechemicalbiology/. Reprints and permissions information is available online at http://npg.nature.com/reprintsandpermissions/.Identifying mechanisms of drug action remains a fundamental impediment to the development and effective use of chemotherapeutics. Here we describe an RNA interference (RNAi)–based strategy to characterize small-molecule function in mammalian cells. By examining the response of cells expressing short hairpin RNAs (shRNAs) to a diverse selection of chemotherapeutics, we could generate a functional shRNA signature that was able to accurately group drugs into established biochemical modes of action. This, in turn, provided a diversely sampled reference set for high-resolution prediction of mechanisms of action for poorly characterized small molecules. We could further reduce the predictive shRNA target set to as few as eight genes and, by using a newly derived probability-based nearest-neighbors approach, could extend the predictive power of this shRNA set to characterize additional drug categories. Thus, a focused shRNA phenotypic signature can provide a highly sensitive and tractable approach for characterizing new anticancer drugs.National Institute of Mental Health (U.S.) (grant RO1 CA128803-03)American Association for Cancer ResearchMassachusetts Institute of Technology. Dept. of BiologyNational Cancer Institute (U.S.). Integrative Cancer Biology Program (grant 1-U54-CA112967

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

<p>Abstract</p> <p>Background</p> <p>The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions.</p> <p>Results</p> <p>In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification.</p> <p>Conclusion</p> <p>High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.</p

Global Genotype-Phenotype Correlations in Pseudomonas aeruginosa

Once the genome sequence of an organism is obtained, attention turns from identifying genes to understanding their function, their organization and control of metabolic pathways and networks that determine its physiology. Recent technical advances in acquiring genome-wide data have led to substantial progress in identifying gene functions. However, we still do not know the function of a large number of genes and, even when a gene product has been assigned to a functional class, we cannot normally predict its contribution to the phenotypic behaviour of the cell or organism - the phenome. In this study, we assessed bacterial growth parameters of 4030 non-redundant PA14 transposon mutants in the pathogenic bacterium Pseudomonas aeruginosa. The genome-wide simultaneous analysis of 119 distinct growth-related phenotypes uncovered a comprehensive phenome and provided evidence that most genotypes are not phenotypically isolated but rather define specific complex phenotypic clusters of genotypes. Since phenotypic overlap was demonstrated to reflect the relatedness of genotypes on a global scale, knowledge of an organism's phenome might significantly contribute to the advancement of functional genomics

The genome sequence of the highly acetic acid-tolerant zygosaccharomyces bailii-derived interspecies hybrid strain ISA1307, isolated from a sparkling wine plant

In this work, it is described the sequencing and annotation of the genome of the yeast strain ISA1307, isolated from a sparkling wine continuous production plant. This strain, formerly considered of the Zygosaccharomyces bailii species, has been used to study Z. bailii physiology, in particular, its extreme tolerance to acetic acid stress at low pH. The analysis of the genome sequence described in this work indicates that strain ISA1307 is an interspecies hybrid between Z. bailii and a closely related species. The genome sequence of ISA1307 is distributed through 154 scaffolds and has a size of around 21.2 Mb, corresponding to 96% of the genome size estimated by flow cytometry. Annotation of ISA1307 genome includes 4385 duplicated genes (~90% of the total number of predicted genes) and 1155 predicted single-copy genes. The functional categories including a higher number of genes are 'Metabolism and generation of energy', 'Protein folding, modification and targeting' and 'Biogenesis of cellular components'. The knowledge of the genome sequence of the ISA1307 strain is expected to contribute to accelerate systems-level understanding of stress resistance mechanisms in Z. bailii and to inspire and guide novel biotechnological applications of this yeast species/strain in fermentation processes, given its high resilience to acidic stress. The availability of the ISA1307 genome sequence also paves the way to a better understanding of the genetic mechanisms underlying the generation and selection of more robust hybrid yeast strains in the stressful environment of wine fermentations.This research was supported by FCT and FEDER through POFC-COMPETE [contracts PEst-OE/EQB/ LA0023/2011_ research line: Systems and Synthetic Biology PTDC/AGR-ALI/102608/2008, PEst-C/BIA/ UI4050/2011, and post-doctoral grant to M.P. (SFRH/BPD/73306/2010) and PhD grants to J.F.G. (SFRH/ BD/80065/2011) and F.C.R. (SFRH/BD/82226/2011)]. U.G. acknowledges the Austrian Science Fund (FWF, special research project F3705)

Chemogenetic fingerprinting by analysis of cellular growth dynamics

<p>Abstract</p> <p>Background</p> <p>A fundamental goal in chemical biology is the elucidation of on- and off-target effects of drugs and biocides. To this aim chemogenetic screens that quantify drug induced changes in cellular fitness, typically taken as changes in composite growth, is commonly applied.</p> <p>Results</p> <p>Using the model organism <it>Saccharomyces cerevisiae </it>we here report that resolving cellular growth dynamics into its individual components, growth lag, growth rate and growth efficiency, increases the predictive power of chemogenetic screens. Both in terms of drug-drug and gene-drug interactions did the individual growth variables capture distinct and only partially overlapping aspects of cell physiology. In fact, the impact on cellular growth dynamics represented functionally distinct chemical fingerprints.</p> <p>Discussion</p> <p>Our findings suggest that the resolution and quantification of all facets of growth increases the informational and interpretational output of chemogenetic screening. Hence, by facilitating a physiologically more complete analysis of gene-drug and drug-drug interactions the here reported results may simplify the assignment of mode-of-action to orphan bioactive compounds.</p

Highly-multiplexed barcode sequencing: an efficient method for parallel analysis of pooled samples

Next-generation sequencing has proven an extremely effective technology for molecular counting applications where the number of sequence reads provides a digital readout for RNA-seq, ChIP-seq, Tn-seq and other applications. The extremely large number of sequence reads that can be obtained per run permits the analysis of increasingly complex samples. For lower complexity samples, however, a point of diminishing returns is reached when the number of counts per sequence results in oversampling with no increase in data quality. A solution to making next-generation sequencing as efficient and affordable as possible involves assaying multiple samples in a single run. Here, we report the successful 96-plexing of complex pools of DNA barcoded yeast mutants and show that such ‘Bar-seq’ assessment of these samples is comparable with data provided by barcode microarrays, the current benchmark for this application. The cost reduction and increased throughput permitted by highly multiplexed sequencing will greatly expand the scope of chemogenomics assays and, equally importantly, the approach is suitable for other sequence counting applications that could benefit from massive parallelization

Zebrafish Mutants calamity and catastrophe Define Critical Pathways of Gene–Nutrient Interactions in Developmental Copper Metabolism

Nutrient availability is an important environmental variable during development that has significant effects on the metabolism, health, and viability of an organism. To understand these interactions for the nutrient copper, we used a chemical genetic screen for zebrafish mutants sensitive to developmental copper deficiency. In this screen, we isolated two mutants that define subtleties of copper metabolism. The first contains a viable hypomorphic allele of atp7a and results in a loss of pigmentation when exposed to mild nutritional copper deficiency. This mutant displays incompletely penetrant skeletal defects affected by developmental copper availability. The second carries an inactivating mutation in the vacuolar ATPase that causes punctate melanocytes and embryonic lethality. This mutant, catastrophe, is sensitive to copper deprivation revealing overlap between ion metabolic pathways. Together, the two mutants illustrate the utility of chemical genetic screens in zebrafish to elucidate the interaction of nutrient availability and genetic polymorphisms in cellular metabolism

Integrated genomics of ovarian xenograft tumor progression and chemotherapy response

<p>Abstract</p> <p>Background</p> <p>Ovarian cancer is the most deadly gynecological cancer with a very poor prognosis. Xenograft mouse models have proven to be one very useful tool in testing candidate therapeutic agents and gene function <it>in vivo</it>. In this study we identify genes and gene networks important for the efficacy of a pre-clinical anti-tumor therapeutic, MT19c.</p> <p>Methods</p> <p>In order to understand how ovarian xenograft tumors may be growing and responding to anti-tumor therapeutics, we used genome-wide mRNA expression and DNA copy number measurements to identify key genes and pathways that may be critical for SKOV-3 xenograft tumor progression. We compared SKOV-3 xenografts treated with the ergocalciferol derived, MT19c, to untreated tumors collected at multiple time points. Cell viability assays were used to test the function of the PPARγ agonist, Rosiglitazone, on SKOV-3 cell growth.</p> <p>Results</p> <p>These data indicate that a number of known survival and growth pathways including Notch signaling and general apoptosis factors are differentially expressed in treated vs. untreated xenografts. As tumors grow, cell cycle and DNA replication genes show increased expression, consistent with faster growth. The steroid nuclear receptor, PPARγ, was significantly up-regulated in MT19c treated xenografts. Surprisingly, stimulation of PPARγ with Rosiglitazone reduced the efficacy of MT19c and cisplatin suggesting that PPARγ is regulating a survival pathway in SKOV-3 cells. To identify which genes may be important for tumor growth and treatment response, we observed that MT19c down-regulates some high copy number genes and stimulates expression of some low copy number genes suggesting that these genes are particularly important for SKOV-3 xenograft growth and survival.</p> <p>Conclusions</p> <p>We have characterized the time dependent responses of ovarian xenograft tumors to the vitamin D analog, MT19c. Our results suggest that PPARγ promotes survival for some ovarian tumor cells. We propose that a combination of regulated expression and copy number can identify genes that are likely important for chemotherapy response. Our findings suggest a new approach to identify candidate genes that are critical for anti-tumor therapy.</p