Sepsis is responsible for >25% of neonatal deaths occurring within the first 4 weeks of life and for survivors, is often associated with morbid complications and severe long-term sequelae. Commensal bacterial species have emerged as the most common causative pathogens in neonatal late-onset sepsis (>3 days of age) and to date, it remains unclear why certain commensal bacteria appear pathogenic in the context of preterm neonatal sepsis. Furthermore, the neonatal response to invasion by commensal bacterial species is poorly characterised. Advances in next-generation sequencing may give us crucial new insights into sepsis pathogenicity by analysing the global gene expression changes occurring in both host as well as invading pathogen.
For my PhD project, I am developing a dual RNA-sequencing (dual RNA-seq) protocol and pipeline which allows me to simultaneously analyse transcriptional changes occurring in the blood cells of neonatal host as well as infecting pathogen during an episode of sepsis. I am currently optimising a clinically compatible RNA extraction protocol for the sensitive detection of low-abundance bacterial transcripts from human whole blood in an in vitro model of sepsis using clinically relevant neonatal sepsis pathogens. I aim to define a set of stereotypic and species-specific virulence and host defence genes upregulated during host-pathogen interactions in in vitro blood challenge models, and validate my findings by applying dual RNA-seq to a small set of clinical preterm neonatal sepsis samples collected from King Edward Memorial Hospital as part of a prospective, observational clinical study. The obtained transcriptional data will undergo comprehensive bioinformatic analysis and characterization to determine differentially expressed genes, enriched host/pathogen pathways, and interspecies correlation.
My work will elucidate the mechanisms of infection in the vulnerable population of preterm infants and may identify novel molecular targets for much-needed rapid sepsis diagnosis and therapy. Lastly, it will generate a universal platform for characterizing host-pathogen interactions in small volume pediatric samples in other infectious diseases.