BackgroundThe Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.ResultsHere, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.ConclusionWe conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.

Bacterial outer membrane vesicle (OMV)-mediated delivery of proteins to host cells is an important mechanism of host-pathogen communication. Emerging evidence suggests that OMVs contain differentially packaged short RNAs (sRNAs) with the potential to target host mRNA function and/or stability. In this study, we used RNA-Seq to characterize differentially packaged sRNAs in Pseudomonas aeruginosa OMVs, and to show transfer of OMV sRNAs to human airway cells. We selected one sRNA for further study based on its stable secondary structure and predicted mRNA targets. Our candidate sRNA (sRNA52320), a fragment of a P. aeruginosa methionine tRNA, was abundant in OMVs and reduced LPS-induced as well as OMV-induced IL-8 secretion by cultured primary human airway epithelial cells. We also showed that sRNA52320 attenuated OMV-induced KC cytokine secretion and neutrophil infiltration in mouse lung. Collectively, these findings are consistent with the hypothesis that sRNA52320 in OMVs is a novel mechanism of host-pathogen interaction whereby P. aeruginosa reduces the host immune response.

e Diverse microbial communities chronically colonize the lungs of cystic fibrosis patients. Pyrosequencing of amplicons for hypervariable regions in the 16S rRNA gene generated taxonomic profiles of bacterial communities for sputum genomic DNA samples from 22 patients during a state of clinical stability (outpatients) and 13 patients during acute exacerbation (inpatients). We employed quantitative PCR (qPCR) to confirm the detection of Pseudomonas aeruginosa and Streptococcus by the pyrosequencing data and human oral microbe identification microarray (HOMIM) analysis to determine the species of the streptococci identified by pyrosequencing. We show that outpatient sputum samples have significantly higher bacterial diversity than inpatients, but maintenance treatment with tobramycin did not impact overall diversity. Contrary to the current dogma in the field that Pseudomonas aeruginosa is the dominant organism in the majority of cystic fibrosis patients, Pseudomonas constituted the predominant genera in only half the patient samples analyzed and reported here. The increased fractional representation of Streptococcus in the outpatient cohort relative to the inpatient cohort was the strongest predictor of clinically stable lung disease. The most prevalent streptococci included species typically associated with the oral cavity (Streptococcus salivarius and Streptococcus parasanguis) and the Streptococcus milleri group species. These species of Streptococcus may play an important role in increasing the diversity of the cystic fibrosis lung environment and promoting patient stability.

While complex intra- and interspecies microbial community dynamics are apparent during chronic infections and likely alter patient health outcomes, our understanding of these interactions is currently limited. For example, Pseudomonas aeruginosa and Staphylococcus aureus are often found to coinfect the lungs of patients with cystic fibrosis (CF), yet these organisms compete under laboratory conditions. Recent observations that coinfection correlates with decreased health outcomes necessitate we develop a greater understanding of these interbacterial interactions. In this study, we tested the hypothesis that P. aeruginosa and/or S. aureus adopts phenotypes that allow coexistence during infection. We compared competitive interactions of P. aeruginosa and S. aureus isolates from mono- or coinfected CF patients employing in vitro coculture models. P. aeruginosa isolates from monoinfected patients were more competitive toward S. aureus than P. aeruginosa isolates from coinfected patients. We also observed that the least competitive P. aeruginosa isolates possessed a mucoid phenotype. Mucoidy occurs upon constitutive activation of the sigma factor AlgT/U, which regulates synthesis of the polysaccharide alginate and dozens of other secreted factors, including some previously described to kill S. aureus. Here, we show that production of alginate in mucoid strains is sufficient to inhibit anti-S. aureus activity independent of activation of the AlgT regulon. Alginate reduces production of siderophores, 2-heptyl-4-hydroxyquinolone-N-oxide (HQNO), and rhamnolipids—each required for efficient killing of S. aureus. These studies demonstrate alginate overproduction may be an important factor driving P. aeruginosa coinfection with S. aureus.

The quantity and breadth of genome-scale data sets that examine RNA expression in diverse bacterial and eukaryotic species are increasing more rapidly than for curated knowledge. Our ADAGE method integrates such data without requiring gene function, gene pathway, or experiment labeling, making practical its application to any large gene expression compendium. We built a Pseudomonas aeruginosa ADAGE model from a diverse set of publicly available experiments without any prespecified biological knowledge, and this model was accurate and predictive. We provide ADAGE results for the complete P. aeruginosa GeneChip compendium for use by researchers studying P. aeruginosa and source code that facilitates ADAGE’s application to other species and data types.