Metagenomic surveillance of pathogen and antimicrobial resistance gene transmission in hospitalized neonates

PROJECT SUMMARY Healthcare-associated infections (HAIs) are a major challenge in neonatal intensive care units (NICUs), resulting in prolonged hospital stays, and preventable morbidity and mortality. Infections in the NICU are more likely to be resistant, with the most common infections being central line-associated bloodstream infections,

surgical site infections, skin and soft tissue infections, and pneumonia. Current approaches to understanding HAI and antimicrobial resistance (AMR) are largely dependent on bacterial culture, which may fail to detect carriage of outbreak-associated pathogens, and which can be falsely negative in the setting of antibiotic pre-

treatment or fastidious organisms. In contrast, metagenomic next-generation sequencing (mNGS) offers a more comprehensive view of the neonatal microbiome, including viral and bacterial microbes, and the associated AMR genes. These proposed aims will evaluate the potential of mNGS surveillance to provide novel insights into

pathogen transmission and AMR acquisition, thereby better informing hospital infection prevention and AMR control strategies. This proposal leverages mNGS to study a prospective cohort of NICU patients sampled weekly with nasal and skin swabs, paired with weekly environmental surface swabs of patient rooms to study the dynamic

exchange of pathogens and AMR genes in the NICU with the following specific aims: Aim 1: Identify nosocomial transmission of viral and bacterial pathogens in the NICU through prospective mNGS surveillance of the nasal and skin microbiome. Aim 2: Characterize the microbiome and the associated AMR genes of environmental

surfaces in patient rooms and assess the microbial exchange between patients and their surroundings. Aim 3: Determine the impact of antibiotic exposures on the neonatal nasal and skin microbiome and the associated AMR genes. Findings from this research will provide critical preliminary data to support future R01-funded

investigations including: 1) utilizing mNGS for real-time pathogen surveillance in healthcare settings to enable more timely infection prevention interventions, and 2) validating AMR findings through a multi-center study to inform antimicrobial stewardship priorities. The candidate's long-term career goal is to become an independently funded physician-scientist

specializing in advanced genomic and metagenomic technologies to address the dual public health threats of HAI and AMR. The research is well supported by collaborations with UCSF's Medicine and Pediatric Infectious Disease Divisions, the Hospital Epidemiology and Infection Prevention program, and the Chan-Zuckerberg

Biohub. Through this K23 award, the candidate will receive practical and didactic training in study design, biospecimen management, computational analysis of high-dimensional metagenomic data, and infection prevention, enabling the candidate to establish a unique research niche focused on harnessing mNGS

technology to inform and enhance infection prevention and AMR control strategies.