Microbial profiling of dental plaque from mechanically ventilated patients

© 2015 The Authors. Micro-organisms isolated from the oral cavity may translocate to the lower airways during mechanical ventilation (MV) leading to ventilator-associated pneumonia (VAP). Changes within the dental plaque microbiome during MV have been documented previously, primarily using culture-based techniques. The aim of this study was to use community profiling by high throughput sequencing to comprehensively analyse suggested microbial changes within dental plaque during MV. Bacterial 16S rDNA gene sequences were obtained from 38 samples of dental plaque sampled from 13 mechanically ventilated patients and sequenced using the Illumina platform. Sequences were processed using Mothur, applying a 97 % gene similarity cut-off for bacterial species level identifications. A significant ‘microbial shift’ occurred in the microbial community of dental plaque during MV for nine out of 13 patients. Following extubation, or removal of the endotracheal tube that facilitates ventilation, sampling revealed a decrease in the relative abundance of potential respiratory pathogens and a compositional change towards a more predominantly (in terms of abundance) oral microbiota including Prevotella spp., and streptococci. The results highlight the need to better understand microbial shifts in the oral microbiome in the development of strategies to reduce VAP, and may have implications for the development of other forms of pneumonia such as community-acquired infection

Increased Sleep Fragmentation Leads to Impaired Off-Line Consolidation of Motor Memories in Humans

A growing literature supports a role for sleep after training in long-term memory consolidation and enhancement. Consequently, interrupted sleep should result in cognitive deficits. Recent evidence from an animal study indeed showed that optimal memory consolidation during sleep requires a certain amount of uninterrupted sleep

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges