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French, N.

Publications and source records attributed to French, N..

2 recordsLinked to original sources

Effect of Live Attenuated Influenza Vaccine on Pneumococcal Carriage

The widely used nasally-administered Live Attenuated Influenza Vaccine (LAIV) alters the dynamics of naturally occurring nasopharyngeal carriage of Streptococcus pneumoniae in animal models. Using a human experimental model (serotype 6B) we tested two hypotheses: 1) LAIV increased the density of S. pneumoniae in those already colonised; 2) LAIV administration promoted colonisation. Randomised, blinded administration of LAIV or nasal placebo either preceded bacterial inoculation or followed it, separated by a 3-day interval. The presence and density of S. pneumoniae was determined from nasal washes by bacterial culture and PCR. Overall acquisition for bacterial carriage were not altered by prior LAIV administration vs. controls (25/55 [45.5%] vs 24/62 [38.7%] respectively, p=0.46). Transient increase in acquisition was detected in LAIV recipients at day 2 (33/55 [60.0%] vs 25/62 [40.3%] in controls, p=0.03). Bacterial carriage densities were increased approximately 10-fold by day 9 in the LAIV recipients (2.82 vs 1.81 log10 titers, p=0.03). When immunisation followed bacterial acquisition (n=163), LAIV did not change area under the bacterial density-time curve (AUC) at day 14 by conventional microbiology (primary endpoint), but significantly reduced AUC to day 27 by PCR (p=0.03). These studies suggest that LAIV may transiently increase nasopharyngeal density of S. pneumoniae. Transmission effects should therefore be considered in the timing design of vaccine schedules.\n\nTrial registrationThe study was registered on EudraCT (2014-004634-26)\n\nFundingThe study was funded by the Bill and Melinda Gates Foundation and the UK Medical Research Council.

immunology

Identifying Streptococcus pneumoniae genes associated with invasive disease using pangenome-based whole genome sequence typing

Streptococcus pneumoniae is a normal commensal of the upper respiratory tract but can also invade the bloodstream or CSF (cerebrospinal fluid), causing invasive pneumococcal disease (IPD). In this study, we attempt to identify genes associated with IPD by applying a random forest machine-learning algorithm to whole genome sequence (WGS) data. We find 43 genes consistently associated with IPD across three geographically distinct WGS data sets of pneumococcal carriage isolates. Of these genes, 23 genes have previously shown to be directly relevant to IPD, while the other 18 are uncharacterized.

bioinformatics