Lethal neonatal meningoencephalitis caused by multi-drug resistant, highly virulent <i>Escherichia coli</i>

<p>Neonatal meningitis is a rare but devastating condition. Multi-drug resistant (MDR) bacteria represent a substantial global health risk. This study reports on an aggressive case of lethal neonatal meningitis due to a MDR <i>Escherichia coli</i> (serotype O75:H5:K1). Serotyping, MDR pattern and phylogenetic typing revealed that this strain is an emergent and highly virulent neonatal meningitis <i>E. coli</i> isolate. The isolate was resistant to both ampicillin and gentamicin; antibiotics currently used for empiric neonatal sepsis treatment. The strain was also positive for multiple virulence genes including K1 capsule, fimbrial adhesion <i>fimH</i>, siderophore receptors <i>iroN</i>, <i>fyuA</i> and <i>iutA</i>, secreted autotransporter toxin <i>sat</i>, membrane associated proteases <i>ompA</i> and <i>ompT</i>, type II polysaccharide synthesis genes (<i>kpsMTII</i>) and pathogenicity-associated island (PAI)-associated <i>malX</i> gene. The presence of highly-virulent MDR organisms isolated in neonates underscores the need to implement rapid drug resistance diagnostic methods and should prompt consideration of alternate empiric therapy in neonates with Gram negative meningitis.</p

Lessons learned from the eMERGE Network: balancing genomics in discovery and practice

The Electronic Medical Records and Genomics (eMERGE) Network, established in 2007, is a consortium of academic and integrated health systems conducting discovery and implementation research in translational genomics. Here, we outline the history of the network, highlight major impacts and lessons learned, and present the tools and resources developed for large-scale genomic analyses and translation into a clinical setting. The network developed methods to extract phenotypes from the electronic medical record to perform genome-wide and phenome-wide association studies. Recruited cohorts were clinically sequenced off a custom panel for targeted sequencing of variants and monogenic disease risks and returned to participants to investigate the impact of return of genomic results. After generating a 105,000 participant-imputed genome-wide association study (GWAS) dataset for discovery, the network enrolled and sequenced 24,998 participants. Integration of these results into the medical record and the effects of results on participants provided key lessons to the field. These learned lessons inform genetic research in diverse populations and provide insights into the clinical impact of return and implementation of genomic medicine using the electronic medical record. The lessons produced by the eMERGE Network can be utilized by other consortia as translational genomic medicine research evolves