Chemical-genetic profile analysis in yeast suggests that a previously uncharacterized open reading frame, YBR261C, affects protein synthesis

<p>Abstract</p> <p>Background</p> <p>Functional genomics has received considerable attention in the post-genomic era, as it aims to identify function(s) for different genes. One way to study gene function is to investigate the alterations in the responses of deletion mutants to different stimuli. Here we investigate the genetic profile of yeast non-essential gene deletion array (yGDA, ~4700 strains) for increased sensitivity to paromomycin, which targets the process of protein synthesis.</p> <p>Results</p> <p>As expected, our analysis indicated that the majority of deletion strains (134) with increased sensitivity to paromomycin, are involved in protein biosynthesis. The remaining strains can be divided into smaller functional categories: metabolism (45), cellular component biogenesis and organization (28), DNA maintenance (21), transport (20), others (38) and unknown (39). These may represent minor cellular target sites (side-effects) for paromomycin. They may also represent novel links to protein synthesis. One of these strains carries a deletion for a previously uncharacterized ORF, <it>YBR261C</it>, that we term <it>TAE1 </it>for Translation Associated Element 1. Our focused follow-up experiments indicated that deletion of <it>TAE1 </it>alters the ribosomal profile of the mutant cells. Also, gene deletion strain for <it>TAE1 </it>has defects in both translation efficiency and fidelity. Miniaturized synthetic genetic array analysis further indicates that <it>TAE1 </it>genetically interacts with 16 ribosomal protein genes. Phenotypic suppression analysis using <it>TAE1 </it>overexpression also links <it>TAE1 </it>to protein synthesis.</p> <p>Conclusion</p> <p>We show that a previously uncharacterized ORF, <it>YBR261C</it>, affects the process of protein synthesis and reaffirm that large-scale genetic profile analysis can be a useful tool to study novel gene function(s).</p

Yeast Features: Identifying Significant Features Shared Among Yeast Proteins for Functional Genomics

Background&#xd;&#xa;High throughput yeast functional genomics experiments are revealing associations among tens to hundreds of genes using numerous experimental conditions. To fully understand how the identified genes might be involved in the observed system, it is essential to consider the widest range of biological annotation possible. Biologists often start their search by collating the annotation provided for each protein within databases such as the Saccharomyces Genome Database, manually comparing them for similar features, and empirically assessing their significance. Such tasks can be automated, and more precise calculations of the significance can be determined using established probability measures. &#xd;&#xa;Results&#xd;&#xa;We developed Yeast Features, an intuitive online tool to help establish the significance of finding a diverse set of shared features among a collection of yeast proteins. A total of 18,786 features from the Saccharomyces Genome Database are considered, including annotation based on the Gene Ontology&#x2019;s molecular function, biological process and cellular compartment, as well as conserved domains, protein-protein and genetic interactions, complexes, metabolic pathways, phenotypes and publications. The significance of shared features is estimated using a hypergeometric probability, but novel options exist to improve the significance by adding background knowledge of the experimental system. For instance, increased statistical significance is achieved in gene deletion experiments because interactions with essential genes will never be observed. We further demonstrate the utility by suggesting the functional roles of the indirect targets of an aminoglycoside with a known mechanism of action, and also the targets of an herbal extract with a previously unknown mode of action. The identification of shared functional features may also be used to propose novel roles for proteins of unknown function, including a role in protein synthesis for YKL075C.&#xd;&#xa;Conclusions&#xd;&#xa;Yeast Features (YF) is an easy to use web-based application (http://software.dumontierlab.com/yeastfeatures/) which can identify and prioritize features that are shared among a set of yeast proteins. This approach is shown to be valuable in the analysis of complex data sets, in which the extracted associations revealed significant functional relationships among the gene products.&#xd;&#xa

Global Functional Atlas of \u3cem\u3eEscherichia coli\u3c/em\u3e Encompassing Previously Uncharacterized Proteins

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans’ biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a “systems-wide” functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins

Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins