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1.  Pseudomonas aeruginosa Enhances Production of a Non-Alginate Exopolysaccharide during Long-Term Colonization of the Cystic Fibrosis Lung 
PLoS ONE  2013;8(12):e82621.
The gram-negative opportunistic pathogen Pseudomonas aeruginosa is the primary cause of chronic respiratory infections in individuals with the heritable disease cystic fibrosis (CF). These infections can last for decades, during which time P. aeruginosa has been proposed to acquire beneficial traits via adaptive evolution. Because CF lacks an animal model that can acquire chronic P. aeruginosa infections, identifying genes important for long-term in vivo fitness remains difficult. However, since clonal, chronological samples can be obtained from chronically infected individuals, traits undergoing adaptive evolution can be identified. Recently we identified 24 P. aeruginosa gene expression traits undergoing parallel evolution in vivo in multiple individuals, suggesting they are beneficial to the bacterium. The goal of this study was to determine if these genes impact P. aeruginosa phenotypes important for survival in the CF lung. By using a gain-of-function genetic screen, we found that 4 genes and 2 operons undergoing parallel evolution in vivo promote P. aeruginosa biofilm formation. These genes/operons promote biofilm formation by increasing levels of the non-alginate exopolysaccharide Psl. One of these genes, phaF, enhances Psl production via a post-transcriptional mechanism, while the other 5 genes/operons do not act on either psl transcription or translation. Together, these data demonstrate that P. aeruginosa has evolved at least two pathways to over-produce a non-alginate exopolysaccharide during long-term colonization of the CF lung. More broadly, this approach allowed us to attribute a biological significance to genes with unknown function, demonstrating the power of using evolution as a guide for targeted genetic studies.
doi:10.1371/journal.pone.0082621
PMCID: PMC3855792  PMID: 24324811
2.  Correction: Prediction and Validation of Gene-Disease Associations Using Methods Inspired by Social Network Analyses 
PLoS ONE  2013;8(9):10.1371/annotation/5aeb88a0-1630-4a07-bb49-32cb5d617af1.
doi:10.1371/annotation/5aeb88a0-1630-4a07-bb49-32cb5d617af1
PMCID: PMC3779276
3.  Transiently Transfected Purine Biosynthetic Enzymes Form Stress Bodies 
PLoS ONE  2013;8(2):e56203.
It has been hypothesized that components of enzymatic pathways might organize into intracellular assemblies to improve their catalytic efficiency or lead to coordinate regulation. Accordingly, de novo purine biosynthesis enzymes may form a purinosome in the absence of purines, and a punctate intracellular body has been identified as the purinosome. We investigated the mechanism by which human de novo purine biosynthetic enzymes might be organized into purinosomes, especially under differing cellular conditions. Irregardless of the activity of bodies formed by endogenous enzymes, we demonstrate that intracellular bodies formed by transiently transfected, fluorescently tagged human purine biosynthesis proteins are best explained as protein aggregation.
doi:10.1371/journal.pone.0056203
PMCID: PMC3566086  PMID: 23405267
4.  Human Cell Chips: Adapting DNA Microarray Spotting Technology to Cell-Based Imaging Assays 
PLoS ONE  2009;4(10):e7088.
Here we describe human spotted cell chips, a technology for determining cellular state across arrays of cells subjected to chemical or genetic perturbation. Cells are grown and treated under standard tissue culture conditions before being fixed and printed onto replicate glass slides, effectively decoupling the experimental conditions from the assay technique. Each slide is then probed using immunofluorescence or other optical reporter and assayed by automated microscopy. We show potential applications of the cell chip by assaying HeLa and A549 samples for changes in target protein abundance (of the dsRNA-activated protein kinase PKR), subcellular localization (nuclear translocation of NFκB) and activation state (phosphorylation of STAT1 and of the p38 and JNK stress kinases) in response to treatment by several chemical effectors (anisomycin, TNFα, and interferon), and we demonstrate scalability by printing a chip with ∼4,700 discrete samples of HeLa cells. Coupling this technology to high-throughput methods for culturing and treating cell lines could enable researchers to examine the impact of exogenous effectors on the same population of experimentally treated cells across multiple reporter targets potentially representing a variety of molecular systems, thus producing a highly multiplexed dataset with minimized experimental variance and at reduced reagent cost compared to alternative techniques. The ability to prepare and store chips also allows researchers to follow up on observations gleaned from initial screens with maximal repeatability.
doi:10.1371/journal.pone.0007088
PMCID: PMC2760726  PMID: 19862318
5.  An Improved, Bias-Reduced Probabilistic Functional Gene Network of Baker's Yeast, Saccharomyces cerevisiae 
PLoS ONE  2007;2(10):e988.
Background
Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding specific gene functions and associations.
Methodology/Principal Findings
We report a significantly improved version (v. 2) of a probabilistic functional gene network [1] of the baker's yeast, Saccharomyces cerevisiae. We describe our optimization methods and illustrate their effects in three major areas: the reduction of functional bias in network training reference sets, the application of a probabilistic model for calculating confidences in pair-wise protein physical or genetic interactions, and the introduction of simple thresholds that eliminate many false positive mRNA co-expression relationships. Using the network, we predict and experimentally verify the function of the yeast RNA binding protein Puf6 in 60S ribosomal subunit biogenesis.
Conclusions/Significance
YeastNet v. 2, constructed using these optimizations together with additional data, shows significant reduction in bias and improvements in precision and recall, in total covering 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome). YeastNet is available from http://www.yeastnet.org.
doi:10.1371/journal.pone.0000988
PMCID: PMC1991590  PMID: 17912365

Results 1-5 (5)