Metagenomic Profiling of Dust Samples for School-based Viral Surveillance

Boston Children'S Hospital, Boston MA

Investigators

Abstract

PROJECT SUMMARY/ABSTRACT: Respiratory viral infections are associated with significant morbidity in both children and adults. While genomic sequencing of wastewater samples has emerged as promising means of monitoring emerging viral strains, school-based sampling remains largely unexplored. The main objective of this proposal is to validate usage of viral sequencing of dust from elementary schools for early detection of emerging viral strains. The central hypothesis for this study is that viral metagenomic sequencing of dust samples obtained from elementary schools can be used for viral surveillance and identify key viral strains that can affect key clinical outcomes such as school absenteeism. The rationale for this project is that high viral diversity exists in elementary schools, and school-based environmental sampling can be more sensitive than clinical sampling at detecting viral strains. The central hypothesis will be tested through two specific aims: 1) evaluate early detection of emerging viral genomes using viral metagenomic sequencing of classroom dust samples; and 2) identify viral strains that best predict school absenteeism. To achieve these aims, an ancillary study will be designed based on the School Inner City Asthma Intervention Study (SICAS-2: ClinicalTrials.gov NCT02291302) using 571 dust samples longitudinally collected from 209 classrooms across 41 schools from 2015-2019. Dust samples will undergo viral metagenomic sequencing using a hybrid-capture approach. Under Aim 1, phylogenetic and time-based analyses will be used to compare viral genomes from school dust samples to clinical genomes in existing national databases. For Aim 2, predictive models using machine learning will determine the likelihood of increased absenteeism based on the presence of specific viral strains. This project uses an innovative sequencing approach to explore school environmental sampling for viral surveillance, offering critical insights to advance targeted public health interventions and reduce exposures. The long-term goal of the candidate is to develop expertise in virome sequencing in order to study the impact of environmental exposures on pediatric respiratory health. To accomplish this, the training plan will be focused on building skills in bioinformatics, machine learning, advanced biostatistics, and scientific and grant writing. This will be accomplished through formal coursework, collaborative work, conference participation, and mentorship from experts in the field, paving the way for a career development application and ultimately, an independent scientific career.