The Pseudomonas aeruginosa genome (G + C content 65–67%, size 5.5–7 Mbp) is made up of a single circular chromosome and a variable number of plasmids. Sequencing of complete genomes or blocks of the accessory genome has revealed that the genome encodes a large repertoire of transporters, transcriptional regulators, and two-component regulatory systems which reflects its metabolic diversity to utilize a broad range of nutrients. The conserved core component of the genome is largely collinear among P. aeruginosa strains and exhibits an interclonal sequence diversity of 0.5–0.7%. Only a few loci of the core genome are subject to diversifying selection. Genome diversity is mainly caused by accessory DNA elements located in 79 regions of genome plasticity that are scattered around the genome and show an anomalous usage of mono- to tetradecanucleotides. Genomic islands of the pKLC102/PAGI-2 family that integrate into tRNA^Lys or tRNA^Gly genes represent hotspots of inter- and intraclonal genomic diversity. The individual islands differ in their repertoire of metabolic genes that make a large contribution to the pangenome. In order to unravel intraclonal diversity of P. aeruginosa, the genomes of two members of the PA14 clonal complex from diverse habitats and geographic origin were compared. The genome sequences differed by less than 0.01% from each other. One hundred ninety-eight of the 231 single nucleotide substitutions (SNPs) were non-randomly distributed in the genome. Non-synonymous SNPs were mainly found in an integrated Pf1-like phage and in genes involved in transcriptional regulation, membrane and extracellular constituents, transport, and secretion. In summary, P. aeruginosa is endowed with a highly conserved core genome of low sequence diversity and a highly variable accessory genome that communicates with other pseudomonads and genera via horizontal gene transfer.

Pseudomonas aeruginosaPAO1 is the most commonly used strain for research on this ubiquitous and metabolically versatile opportunistic pathogen. Strain PAO1, a derivative of the original Australian PAO isolate, has been distributed worldwide to laboratories and strain collections. Over decades discordant phenotypes of PAO1 sublines have emerged. Taking the existing PAO1-UW genome sequence (named after the University of Washington, which led the sequencing project) as a blueprint, the genome sequences of reference strains MPAO1 and PAO1-DSM (stored at the German Collection for Microorganisms and Cell Cultures [DSMZ]) were resolved by physical mapping and deep short read sequencing-by-synthesis. MPAO1 has been the source of near-saturation libraries of transposon insertion mutants, and PAO1-DSM is identical in its SpeI-DpnI restriction map with the original isolate. The major genomic differences of MPAO1 and PAO1-DSM in comparison to PAO1-UW are the lack of a large inversion, a duplication of a mobile 12-kb prophage region carrying a distinct integrase and protein phosphatases or kinases, deletions of 3 to 1,006 bp in size, and at least 39 single-nucleotide substitutions, 17 of which affect protein sequences. The PAO1 sublines differed in their ability to cope with nutrient limitation and their virulence in an acute murine airway infection model. Subline PAO1-DSM outnumbered the two other sublines in late stationary growth phase. In conclusion,P. aeruginosaPAO1 shows an ongoing microevolution of genotype and phenotype that jeopardizes the reproducibility of research. High-throughput genome resequencing will resolve more cases and could become a proper quality control for strain collections.

Summary: Clones C and PA14 are the worldwide most abundant clonal complexes in the Pseudomonas aeruginosa population. The microevolution of clones C and PA14 was investigated in serial cystic fibrosis (CF) airway isolates collected over 20 years since the onset of colonization. Intraclonal evolution in CF lungs was resolved by genome sequencing of first, intermediate and late isolates and subsequent multimarker SNP genotyping of the whole strain panel. Mapping of sequence reads onto the P. aeruginosa PA14 reference genome unravelled an intraclonal and interclonal sequence diversity of 0.0035% and 0.68% respectively. Clone PA14 diversified into three branches in the patient's lungs, and the PA14 population acquired 15 nucleotide substitutions and a large deletion during the observation period. The clone C genome remained invariant during the first 3 years in CF lungs; however, 15 years later 947 transitions and 12 transversions were detected in a clone C mutL mutant strain. Key mutations occurred in retS , RNA polymerase, multidrug transporter, virulence and denitrification genes. Late clone C and PA14 persistors in the CF lungs were compromised in growth and cytotoxicity, but their mutation frequency was normal even in mutL mutant clades.

Herpesviruses establish a lifelong latent infection posing the risk for virus reactivation and disease. In cytomegalovirus infection, expression of the major immediate early (IE) genes is a critical checkpoint, driving the lytic replication cycle upon primary infection or reactivation from latency. While it is known that type I interferon (IFN) limits lytic CMV replication, its role in latency and reactivation has not been explored. In the model of mouse CMV infection, we show here that IFNβ blocks mouse CMV replication at the level of IE transcription in IFN-responding endothelial cells and fibroblasts. The IFN-mediated inhibition of IE genes was entirely reversible, arguing that the IFN-effect may be consistent with viral latency. Importantly, the response to IFNβ is stochastic, and MCMV IE transcription and replication were repressed only in IFN-responsive cells, while the IFN-unresponsive cells remained permissive for lytic MCMV infection. IFN blocked the viral lytic replication cycle by upregulating the nuclear domain 10 (ND10) components, PML, Sp100 and Daxx, and their knockdown by shRNA rescued viral replication in the presence of IFNβ. Finally, IFNβ prevented MCMV reactivation from endothelial cells derived from latently infected mice, validating our results in a biologically relevant setting. Therefore, our data do not only define for the first time the molecular mechanism of IFN-mediated control of CMV infection, but also indicate that the reversible inhibition of the virus lytic cycle by IFNβ is consistent with the establishment of CMV latency. Cytomegalovirus (CMV) is a widespread herpesvirus that establishes a détente with the host immune system. Therefore, the CMV reactivates from latency in immunocompromised hosts, resulting in life-threatening disease of the vulnerable patients. However, the exact mechanism by which the immune system keeps CMV at bay remains incompletely understood. To address this question, we have used a reporter system, based on infection of cells with the mouse CMV. Our results showed that interferon (IFN), a well-known antiviral protein, blocks CMV replication at the earliest stages after the virus has entered the cell. More importantly, removing the IFN from the infected cells restarted MCMV replication, indicating that its effects are consistent with viral latency. We showed that IFN blocked virus replication by inducing the expression of proteins located in the nuclear domain 10 (ND10), a compartment in the nucleus of cells to which the incoming viral genomes are directed. Similarly, IFN was sufficient to block CMV reactivation from cells of latently infected mice. In conclusion, IFN had the ability to drive CMV into a quiescent state matching the formal definition of latency and was sufficient to prevent reactivation of bona fide latent CMV.

Background: Data mining in large DNA sequences is a major challenge in microbial genomics and bioinformatics. Oligonucleotide usage (OU) patterns provide a wealth of information for large scale sequence analysis and visualization. The purpose of this research was to make OU statistical analysis available as a novel web-based tool for functional genomics and annotation. The tool is also available as a downloadable package. Results: The SeqWord Genome Browser (SWGB) was developed to visualize the natural compositional variation of DNA sequences. The applet is also used for identification of divergent genomic regions both in annotated sequences of bacterial chromosomes, plasmids, phages and viruses, and in raw DNA sequences prior to annotation by comparing local and global OU patterns. The applet allows fast and reliable identification of clusters of horizontally transferred genomic islands, large multi-domain genes and genes for ribosomal RNA. Within the majority of genomic fragments (also termed genomic core sequence), regions enriched with housekeeping genes, ribosomal proteins and the regions rich in pseudogenes or genetic vestiges may be contrasted. Conclusion: The SWGB applet presents a range of comprehensive OU statistical parameters calculated for a range of bacterial species, plasmids and phages. It is available on the Internet at http://www.bi.up.ac.za/SeqWord/mhhapplet.php.