As the interface between a microbe and its environment, the bacterial cell envelope has broad biological and clinical significance. While numerous biosynthesis genes and pathways have been identified and studied in isolation, how these intersect functionally to ensure envelope integrity during adaptive responses to environmental challenge remains unclear. To this end, we performed high-density synthetic genetic screens to generate quantitative functional association maps encompassing virtually the entire cell envelope biosynthetic machinery of Escherichia coli under both auxotrophic (rich medium) and prototrophic (minimal medium) culture conditions. The differential patterns of genetic interactions detected among >235,000 digenic mutant combinations tested reveal unexpected condition-specific functional crosstalk and genetic backup mechanisms that ensure stress-resistant envelope assembly and maintenance. These networks also provide insights into the global systems connectivity and dynamic functional reorganization of a universal bacterial structure that is both broadly conserved among eubacteria (including pathogens) and an important target.

BackgroundChemical-genetic profiling of inhibitory compounds can lead to identification of their modes of action. These profiles can help elucidate the complex interactions between small bioactive compounds and the cell machinery, and explain putative gene function(s).ResultsColony size reduction was used to investigate the chemical-genetic profile of cycloheximide, 3-amino-1,2,4-triazole, paromomycin, streptomycin and neomycin in the yeast Saccharomyces cerevisiae. These compounds target the process of protein biosynthesis. More than 70,000 strains were analyzed from the array of gene deletion mutant yeast strains. As expected, the overall profiles of the tested compounds were similar, with deletions for genes involved in protein biosynthesis being the major category followed by metabolism. This implies that novel genes involved in protein biosynthesis could be identified from these profiles. Further investigations were carried out to assess the activity of three profiled genes in the process of protein biosynthesis using relative fitness of double mutants and other genetic assays.ConclusionChemical-genetic profiles provide insight into the molecular mechanism(s) of the examined compounds by elucidating their potential primary and secondary cellular target sites. Our follow-up investigations into the activity of three profiled genes in the process of protein biosynthesis provided further evidence concerning the usefulness of chemical-genetic analyses for annotating gene functions. We termed these genes TAE2, TAE3 and TAE4 for translation associated elements 2-4.

Background: 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.

Protein-protein interactions (PPIs) play a critical role in many cellular functions. A number of experimental techniques have been applied to discover PPIs; however, these techniques are expensive in terms of time, money, and expertise. There are also large discrepancies between the PPI data collected by the same or different techniques in the same organism. We therefore turn to computational techniques for the prediction of PPIs. Computational techniques have been applied to the collection, indexing, validation, analysis, and extrapolation of PPI data. This chapter will focus on computational prediction of PPI, reviewing a number of techniques including PIPE, developed in our own laboratory. For comparison, the conventional large-scale approaches to predict PPIs are also briefly discussed. The chapter concludes with a discussion of the limitations of both experimental and computational methods of determining PPIs.

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A genome-wide screen of a yeast non-essential gene-deletion library was used to identify sick phenotypes due to oxygen deprivation. The screen provided a manageable list of 384 potentially novel as well as known oxygen responding (anoxia-survival) genes. The gene-deletion mutants were further assayed for sensitivity to ferrozine and cobalt to obtain a subset of 34 oxygen-responsive candidate genes including the known hypoxic gene activator, MGA2. With each mutant in this subset a plasmid based β-galactosidase assay was performed using the anoxic-inducible promoter from OLE1 gene, and 17 gene deletions were identified that inhibit induction under anaerobic conditions. Genetic interaction analysis for one of these mutants, the RNase-encoding POP2 gene, revealed synthetic sick interactions with a number of genes involved in oxygen sensing and response. Knockdown experiments for CNOT8, human homolog of POP2, reduced cell survival under low oxygen condition suggesting a similar function in human cells.

BackgroundOur knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods.ResultsOn the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments.ConclusionsThe speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-014-0383-1) contains supplementary material, which is available to authorized users.

Protein biosynthesis is an orderly process that requires a balance between rate and accuracy. To produce a functional product, the fidelity of this process has to be maintained from start to finish. In order to systematically identify genes that affect stop codon bypass, three expression plasmids, pUKC817, pUKC818 and pUKC819, were integrated into the yeast non-essential loss-of-function gene array (5000 strains). These plasmids contain three different premature stop codons (UAA, UGA and UAG, respectively) within the LacZ expression cassette. A fourth plasmid, pUKC815 that carries the native LacZ gene was used as a control. Transformed strains were subjected to large-scale β-galactosidase lift assay analysis to evaluate production of β-galactosidase for each gene deletion strain. In this way 84 potential candidate genes that affect stop codon bypass were identified. Three candidate genes, OLA1, BSC2, and YNL040W, were further investigated, and were found to be important for cytoplasmic protein biosynthesis.