Pseudomonas aeruginosa displays an epidemic population structure.

peer reviewedBacteria can have population structures ranging from the fully sexual to the highly clonal. Despite numerous studies, the population structure of Pseudomonas aeruginosa is still somewhat contentious. We used a polyphasic approach in order to shed new light on this issue. A data set consisting of three outer membrane (lipo)protein gene sequences (oprI, oprL and oprD), a DNA-based fingerprint (amplified fragment length polymorphism), serotype and pyoverdine type of 73 P. aeruginosa clinical and environmental isolates, collected across the world, was analysed using biological data analysis software. We observed a clear mosaicism in the results, non-congruence between results of different typing methods and a microscale mosaic structure in the oprD gene. Hence, in this network, we also observed some clonal complexes characterized by an almost identical data set. The most recent clones exhibited serotypes O1, 6, 11 and 12. No obvious correlation was observed between these dominant clones and habitat or, with the exception of some recent clones, geographical origin. Our results are consistent with, and even clarify, some seemingly contradictory results in earlier epidemiological studies. Therefore, we suggest an epidemic population structure for P. aeruginosa, comparable with that of Neisseria meningitidis, a superficially clonal structure with frequent recombinations, in which occasionally highly successful epidemic clones arise

Context-Dependent Dual Role of SKI8 Homologs in mRNA Synthesis and Turnover

Eukaryotic mRNA transcription and turnover is controlled by an enzymatic machinery that includes RNA polymerase II and the 3′ to 5′ exosome. The activity of these protein complexes is modulated by additional factors, such as the nuclear RNA polymerase II-associated factor 1 (Paf1c) and the cytoplasmic Superkiller (SKI) complex, respectively. Their components are conserved across uni- as well as multi-cellular organisms, including yeast, Arabidopsis, and humans. Among them, SKI8 displays multiple facets on top of its cytoplasmic role in the SKI complex. For instance, nuclear yeast ScSKI8 has an additional function in meiotic recombination, whereas nuclear human hSKI8 (unlike ScSKI8) associates with Paf1c. The Arabidopsis SKI8 homolog VERNALIZATION INDEPENDENT 3 (VIP3) has been found in Paf1c as well; however, whether it also has a role in the SKI complex remains obscure so far. We found that transgenic VIP3-GFP, which complements a novel vip3 mutant allele, localizes to both nucleus and cytoplasm. Consistently, biochemical analyses suggest that VIP3–GFP associates with the SKI complex. A role of VIP3 in the turnover of nuclear encoded mRNAs is supported by random-primed RNA sequencing of wild-type and vip3 seedlings, which indicates mRNA stabilization in vip3. Another SKI subunit homolog mutant, ski2, displays a dwarf phenotype similar to vip3. However, unlike vip3, it displays neither early flowering nor flower development phenotypes, suggesting that the latter reflect VIP3's role in Paf1c. Surprisingly then, transgenic ScSKI8 rescued all aspects of the vip3 phenotype, suggesting that the dual role of SKI8 depends on species-specific cellular context

Pseudomonas aeruginosa Population Structure Revisited

At present there are strong indications that Pseudomonas aeruginosa exhibits an epidemic population structure; clinical isolates are indistinguishable from environmental isolates, and they do not exhibit a specific (disease) habitat selection. However, some important issues, such as the worldwide emergence of highly transmissible P. aeruginosa clones among cystic fibrosis (CF) patients and the spread and persistence of multidrug resistant (MDR) strains in hospital wards with high antibiotic pressure, remain contentious. To further investigate the population structure of P. aeruginosa, eight parameters were analyzed and combined for 328 unrelated isolates, collected over the last 125 years from 69 localities in 30 countries on five continents, from diverse clinical (human and animal) and environmental habitats. The analysed parameters were: i) O serotype, ii) Fluorescent Amplified-Fragment Length Polymorphism (FALFP) pattern, nucleotide sequences of outer membrane protein genes, iii) oprI, iv) oprL, v) oprD, vi) pyoverdine receptor gene profile (fpvA type and fpvB prevalence), and prevalence of vii) exoenzyme genes exoS and exoU and viii) group I pilin glycosyltransferase gene tfpO. These traits were combined and analysed using biological data analysis software and visualized in the form of a minimum spanning tree (MST). We revealed a network of relationships between all analyzed parameters and non-congruence between experiments. At the same time we observed several conserved clones, characterized by an almost identical data set. These observations confirm the nonclonal epidemic population structure of P. aeruginosa, a superficially clonal structure with frequent recombinations, in which occasionally highly successful epidemic clones arise. One of these clones is the renown and widespread MDR serotype O12 clone. On the other hand, we found no evidence for a widespread CF transmissible clone. All but one of the 43 analysed CF strains belonged to a ubiquitous P. aeruginosa “core lineage” and typically exhibited the exoS+/exoU− genotype and group B oprL and oprD alleles. This is to our knowledge the first report of an MST analysis conducted on a polyphasic data set

A meta-analysis reveals the commonalities and differences in Arabidopsis thaliana response to different viral pathogens

Understanding the mechanisms by which plants trigger host defenses in response to viruses has been a challenging problem owing to the multiplicity of factors and complexity of interactions involved. The advent of genomic techniques, however, has opened the possibility to grasp a global picture of the interaction. Here, we used Arabidopsis thaliana to identify and compare genes that are differentially regulated upon infection with seven distinct (+)ssRNA and one ssDNA plant viruses. In the first approach, we established lists of genes differentially affected by each virus and compared their involvement in biological functions and metabolic processes. We found that phylogenetically related viruses significantly alter the expression of similar genes and that viruses naturally infecting Brassicaceae display a greater overlap in the plant response. In the second approach, virus-regulated genes were contextualized using models of transcriptional and protein-protein interaction networks of A. thaliana. Our results confirm that host cells undergo significant reprogramming of their transcriptome during infection, which is possibly a central requirement for the mounting of host defenses. We uncovered a general mode of action in which perturbations preferentially affect genes that are highly connected, central and organized in modules. © 2012 Rodrigo et al.This work was supported by the Spanish Ministerio de Ciencia e Innovacion (MICINN) grants BFU2009-06993 (S. F. E.) and BIO2006-13107 (C. L.) and by Generalitat Valenciana grant PROMETEO2010/016 (S. F. E.). G. R. is supported by a graduate fellowship from the Generalitat Valenciana (BFPI2007-160) and J.C. by a contract from MICINN grant TIN2006-12860. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Rodrigo Tarrega, G.; Carrera Montesinos, J.; Ruiz-Ferrer, V.; Del Toro, F.; Llave, C.; Voinnet, O.; Elena Fito, SF. (2012). A meta-analysis reveals the commonalities and differences in Arabidopsis thaliana response to different viral pathogens. PLoS ONE. 7(7):40526-40526. https://doi.org/10.1371/journal.pone.0040526S405264052677Peng, X., Chan, E. Y., Li, Y., Diamond, D. L., Korth, M. J., & Katze, M. G. (2009). Virus–host interactions: from systems biology to translational research. Current Opinion in Microbiology, 12(4), 432-438. doi:10.1016/j.mib.2009.06.003Dodds, P. N., & Rathjen, J. P. (2010). Plant immunity: towards an integrated view of plant–pathogen interactions. Nature Reviews Genetics, 11(8), 539-548. doi:10.1038/nrg2812Maule, A., Leh, V., & Lederer, C. (2002). The dialogue between viruses and hosts in compatible interactions. Current Opinion in Plant Biology, 5(4), 279-284. doi:10.1016/s1369-5266(02)00272-8Whitham, S. A., Quan, S., Chang, H.-S., Cooper, B., Estes, B., Zhu, T., … Hou, Y.-M. (2003). Diverse RNA viruses elicit the expression of common sets of genes in susceptibleArabidopsis thalianaplants. The Plant Journal, 33(2), 271-283. doi:10.1046/j.1365-313x.2003.01625.xBailer, S., & Haas, J. (2009). Connecting viral with cellular interactomes. Current Opinion in Microbiology, 12(4), 453-459. doi:10.1016/j.mib.2009.06.004Whitham, S. A., Yang, C., & Goodin, M. M. (2006). Global Impact: Elucidating Plant Responses to Viral Infection. Molecular Plant-Microbe Interactions, 19(11), 1207-1215. doi:10.1094/mpmi-19-1207MacPherson, J. I., Dickerson, J. E., Pinney, J. W., & Robertson, D. L. (2010). Patterns of HIV-1 Protein Interaction Identify Perturbed Host-Cellular Subsystems. PLoS Computational Biology, 6(7), e1000863. doi:10.1371/journal.pcbi.1000863Jenner, R. G., & Young, R. A. (2005). 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Virus Adaptation by Manipulation of Host’s Gene Expression. PLoS ONE, 3(6), e2397. doi:10.1371/journal.pone.0002397Ascencio-Ibáñez, J. T., Sozzani, R., Lee, T.-J., Chu, T.-M., Wolfinger, R. D., Cella, R., & Hanley-Bowdoin, L. (2008). Global Analysis of Arabidopsis Gene Expression Uncovers a Complex Array of Changes Impacting Pathogen Response and Cell Cycle during Geminivirus Infection. Plant Physiology, 148(1), 436-454. doi:10.1104/pp.108.121038Babu, M., Griffiths, J. S., Huang, T.-S., & Wang, A. (2008). Altered gene expression changes in Arabidopsis leaf tissues and protoplasts in response to Plum pox virus infection. BMC Genomics, 9(1), 325. doi:10.1186/1471-2164-9-325De Vienne, D. M., Giraud, T., & Martin, O. C. (2007). A congruence index for testing topological similarity between trees. Bioinformatics, 23(23), 3119-3124. doi:10.1093/bioinformatics/btm500Wise, R. P., Moscou, M. J., Bogdanove, A. J., & Whitham, S. A. (2007). Transcript Profiling in Host–Pathogen Interactions. Annual Review of Phytopathology, 45(1), 329-369. doi:10.1146/annurev.phyto.45.011107.143944Handford, M. G., & Carr, J. P. (2007). A defect in carbohydrate metabolism ameliorates symptom severity in virus-infected Arabidopsis thaliana. Journal of General Virology, 88(1), 337-341. doi:10.1099/vir.0.82376-0Hou, B., Lim, E.-K., Higgins, G. S., & Bowles, D. J. (2004). N-Glucosylation of Cytokinins by Glycosyltransferases ofArabidopsis thaliana. Journal of Biological Chemistry, 279(46), 47822-47832. doi:10.1074/jbc.m409569200Schwender, J., Goffman, F., Ohlrogge, J. B., & Shachar-Hill, Y. (2004). Rubisco without the Calvin cycle improves the carbon efficiency of developing green seeds. Nature, 432(7018), 779-782. doi:10.1038/nature03145Pagán, I., Alonso-Blanco, C., & García-Arenal, F. (2008). Host Responses in Life-History Traits and Tolerance to Virus Infection in Arabidopsis thaliana. 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PLoS ONE, 3(4), e0002051. doi:10.1371/journal.pone.0002051Stumpf, M. P. H., & Ingram, P. J. (2005). Probability models for degree distributions of protein interaction networks. Europhysics Letters (EPL), 71(1), 152-158. doi:10.1209/epl/i2004-10531-8Khanin, R., & Wit, E. (2006). How Scale-Free Are Biological Networks. Journal of Computational Biology, 13(3), 810-818. doi:10.1089/cmb.2006.13.810Daudin, J.-J., Picard, F., & Robin, S. (2007). A mixture model for random graphs. Statistics and Computing, 18(2), 173-183. doi:10.1007/s11222-007-9046-7Uetz, P. (2006). Herpesviral Protein Networks and Their Interaction with the Human Proteome. Science, 311(5758), 239-242. doi:10.1126/science.1116804Choi, I.-R., Stenger, D. C., & French, R. (2000). Multiple Interactions among Proteins Encoded by the Mite-Transmitted Wheat Streak Mosaic Tritimovirus. Virology, 267(2), 185-198. doi:10.1006/viro.1999.0117Guo, D., Saarma, M., Rajamäki, M.-L., & Valkonen, J. P. T. (2001). 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Nosocomial transmission of necrotising fasciitis

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Emergence and dissemination of multidrug resistant clones of Pseudomonas aeruginosa producing VIM-2 metallo-beta-lactamase in Belgium.

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Incidence and virulence determinants of verocytotoxin-producing Escherichia coli infections in the Brussels-Capital Region, Belgium, in 2008-2010.

The incidence of verocytotoxin-producing Escherichia coli (VTEC) was investigated by PCR in all human stools from Universitair Ziekenhuis Brussel (UZB) and in selected stools from six other hospital laboratories in the Brussels-Capital Region, Belgium, collected between April 2008 and October 2010. The stools selected to be included in this study were those from patients with hemolytic-uremic syndrome (HUS), patients with a history of bloody diarrhea, patients linked to clusters of diarrhea, children up to the age of 6 years, and stools containing macroscopic blood. Verocytotoxin genes (vtx) were detected significantly more frequently in stools from patients with the selected conditions (2.04%) than in unselected stools from UZB (1.20%) (P = 0.001). VTEC was detected most frequently in patients with HUS (35.3%), a history of bloody diarrhea (5.15%), or stools containing macroscopic blood (1.85%). Stools from patients up to the age of 17 years were significantly more frequently vtx positive than those from adult patients between the ages of 18 and 65 years (P = 0.022). Although stools from patients older than 65 years were also more frequently positive for vtx than those from patients between 18 and 65 years, this trend was not significant. VTEC was isolated from 140 (67.9%) vtx-positive stools. One sample yielded two different serotypes; thus, 141 isolates could be characterized. Sixty different O:H serotypes harboring 85 different virulence profiles were identified. Serotypes O157:H7/H- (n = 34), O26:H11/H- (n = 21), O63:H6 (n = 8), O111:H8/H- (n = 7), and O146:H21/H- (n = 6) accounted for 53.9% of isolates. All O157 isolates carried vtx2, eae, and a complete O island 122 (COI-122); 15 also carried vtx1. Non-O157 isolates (n = 107), however, accounted for the bulk (75.9%) of isolates. Fifty-nine (55.1%) isolates were positive for vtx1, 36 (33.6%) were positive for vtx2, and 12 (11.2%) carried both vtx1 and vtx2. Pulsed-field gel electrophoresis revealed wide genetic diversity; however, small clusters of O157, O26, and O63:H6 VTEC that could have been part of unidentified outbreaks were identified. Antimicrobial resistance was observed in 63 (44.7%) isolates, and 34 (24.1%) showed multidrug resistance. Our data show that VTEC infections were not limited to patients with HUS or bloody diarrhea. Clinical laboratories should, therefore, screen all stools for O157 and non-O157 VTEC using selective media and a method for detecting verocytotoxins or vtx genes.Journal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Marked increase of Pseudomonas aeruginosa serotype 012 in Belgium since 1982.

Routine typing was performed on a total of 7089 Pseudomonas aeruginosa strains isolated in 16 Belgian hospitals in the period from 1977 to 1986. The annual number of strains received ranged from 318 to 1346. The incidence of serotype O:12 was less than 2% until 1981 when it rose to 4%, steadily increasing to become the predominant serotype in 1984 (22%), 1985 (18%) and 1986 (22%). Since 1980 the O:12 isolates have exhibited characteristic patterns on pyocin and phage typing, 89% of O:12 isolates belonging to pyocin types 1, 39, 43, 45 or 105, whereas only 51% of isolates of other serotypes belonged to those pyocin types. Ninety-three per cent of serotype O:12 isolates belonged to phage types 68/119x, 68 or 119x, or were non-typable, whereas only 24.37% of other serotypes isolates exhibited these phage patterns. These distinctive patterns of pyocin and phage types suggest a high degree of homogeneity within the O:12 strains isolated in recent years in Belgium. Multi-centre or country-wide survey of Pseudomonas aeruginosa strains isolated in hospitals using epidemiological markers may be of value in identifying a sudden increase in epidemic strains.Journal ArticleSCOPUS: ar.jinfo:eu-repo/semantics/publishe