Neural networks have been trained to predict the subcellular location of proteins in prokaryotic or eukaryotic cells from their amino acid composition. For three possible subcellular locations in prokaryotic organisms a prediction accuracy of 81% can be achieved. Assigning a reliability index, 33% of the predictions can be made with an accuracy of 91%. For eukaryotic proteins (excluding plant sequences) an overall prediction accuracy of 66% for four locations was achieved, with 33% of the sequences being predicted with an accuracy of 82% or better. With the subcellular location restricting a protein's possible function, this method should be a useful tool for the systematic analysis of genome data and is available via a server on the world wide web.

Analysis of a GWA study followed by in silico and wet-lab replication steps identified the KIAA1462 gene, encoding a yet uncharacterized protein, on chromosome 10p11.23 with genome-wide significant association for CAD/MI. Further studies are needed to characterize the functional role of this locus in the aetiology of these diseases.

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Background: Phi29 polymerase based amplification methods provides amplified DNA with minimal changes in sequence and relative abundance for many biomedical applications. RNA virus detection using microarrays, however, can present a challenge because phi29 DNA polymerase cannot amplify RNA nor small cDNA fragments (<2000 bases) obtained by reverse transcription of certain viral RNA genomes. Therefore, ligation of cDNA fragments is necessary prior phi29 polymerase based amplification. We adapted the QuantiTect Whole Transcriptome Kit (Qiagen) to our purposes and designated the method as Whole Transcriptome Amplification (WTA).

Intubated patients frequently become colonized by Pseudomonas aeruginosa, which is subsequently responsible for ventilator-associated pneumonia. This pathogen readily acquires resistance against available antimicrobials. Depending on the resistance mechanism selected for, resistance might either be lost or persist after removal of the selective pressure. We investigated the rapidity of selection, as well as the persistence, of antimicrobial resistance and determined the underlying mechanisms. We selected 109 prospectively collected P. aeruginosa tracheal isolates from two patients based on their prolonged intubation and colonization periods, during which they had received carbapenem, fluoroquinolone (FQ), or combined ␤-lactam-aminoglycoside therapies. We determined antimicrobial resistance phenotypes by susceptibility testing and used quantitative real-time PCR to measure the expression of resistance determinants. Within 10 days after the initiation of therapy, all treatment regimens selected resistant isolates. Resistance to ␤-lactam and FQ was correlated with ampC and mexC gene expression levels, respectively, whereas imipenem resistance was attributable to decreased oprD expression. Combined ␤-lactam-aminoglycoside resistance was associated with the appearance of small-colony variants. Imipenem and FQ resistance persisted for prolonged times once the selecting antimicrobial treatment had been discontinued. In contrast, resistance to ␤-lactams disappeared rapidly after removal of the selective pressure, to reappear promptly upon renewed exposure. Our results suggest that resistant P. aeruginosa is selected in less than 10 days independently of the antimicrobial class. Different resistance mechanisms lead to the loss or persistence of resistance after the removal of the selecting agent. Even if resistant isolates are not evident upon culture, they may persist in the lung and can be rapidly reselected.