Metagenomic sequencing of the skin microbiota of the scalp predicting the risk of surgical site infections following surgery of traumatic brain injury in sub-Saharan Africa

Abstract

Background Surgical site infections (SSI) are a significant concern following traumatic brain injury (TBI) surgery and often stem from the skin’s microbiota near the surgical site, allowing bacteria to penetrate deeper layers and potentially causing severe infections in the cranial cavity. This study investigated the relationship between scalp skin microbiota composition and the risk of SSI after TBI surgery in sub-Saharan Africa (SSA). Methods This was a prospective cohort study, enrolling patients scheduled for TBI surgery. Sterile skin swabs were taken from the surrounding normal skin of the head and stored for analysis at -80°Celcius. Patients were monitored postoperatively for up to three months to detect any occurrences of SSI. 16S rRNA sequencing was used to analyze the skin microbiota composition, identifying different taxonomic microorganisms at the genus level. The analysis compared two groups: those who developed SSI and those who did not. Results A total of 57 patients were included, mostly male (89.5%) with a mean age of 26.5 years, predominantly from urban areas in Uganda and victims of assault. Graphical visualization and metagenomic metrics analysis revealed differences in composition, richness, and evenness of skin microbiota within samples (α) or within the community (β), and showed specific taxa (phylum and genera) associated with either the group of SSI or the No SSI. Conclusions Metagenomic sequencing analysis uncovered several baseline findings and trends regarding the skin microbiome’s relationship with SSI risk. There is an association between scalp microbiota composition (abundancy and diversity) and SSI occurrence following TBI surgery in SSA. We hypothesize under reserve that the scalp microbiota dysbiosis could potentially be an independent predictor of the occurrence of SSI; we advocate for further studies with larger cohorts.