Genome diversity of Pseudomonas aeruginosa PAO1 laboratory strains.

Pseudomonas aeruginosa PAO1 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. aeruginosa PAO1 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.

Genometa--a fast and accurate classifier for short metagenomic shotgun reads.

UNLABELLED: Metagenomic studies use high-throughput sequence data to investigate microbial communities in situ. However, considerable challenges remain in the analysis of these data, particularly with regard to speed and reliable analysis of microbial species as opposed to higher level taxa such as phyla. We here present Genometa, a computationally undemanding graphical user interface program that enables identification of bacterial species and gene content from datasets generated by inexpensive high-throughput short read sequencing technologies. Our approach was first verified on two simulated metagenomic short read datasets, detecting 100% and 94% of the bacterial species included with few false positives or false negatives. Subsequent comparative benchmarking analysis against three popular metagenomic algorithms on an Illumina human gut dataset revealed Genometa to attribute the most reads to bacteria at species level (i.e. including all strains of that species) and demonstrate similar or better accuracy than the other programs. Lastly, speed was demonstrated to be many times that of BLAST due to the use of modern short read aligners. Our method is highly accurate if bacteria in the sample are represented by genomes in the reference sequence but cannot find species absent from the reference. This method is one of the most user-friendly and resource efficient approaches and is thus feasible for rapidly analysing millions of short reads on a personal computer. AVAILABILITY: The Genometa program, a step by step tutorial and Java source code are freely available from http://genomics1.mh-hannover.de/genometa/ and on http://code.google.com/p/genometa/. This program has been tested on Ubuntu Linux and Windows XP/7.