Abstract
Severe Acute Respiratory Infections (SARI) are a major cause of hospitalisation and mortality worldwide and disproportionately affect Māori and Pacific peoples in Aotearoa New Zealand. Many cases remain undiagnosed using conventional PCR-based diagnostic panels, which target a limited range of predefined pathogens and often miss co-infections and unexpected or novel organisms. This diagnostic gap poses significant challenges for clinical management and early outbreak detection. In this thesis, I used an unbiased metatranscriptomic approach to characterise the total “infectome” in patients presenting with SARI whose nasopharyngeal samples tested negative for routine respiratory pathogens.
Using sentinel SARI surveillance samples collected from 2014 to 2021 across two Auckland hospitals, I sequenced total RNA from 300 PCR-negative samples and applied high-throughput sequencing with comprehensive bioinformatic analyses. This revealed actively transcribing pathogens across 129 patients, including 13 RNA viruses, three DNA viruses, nine bacterial species, and four fungal species. Co-infections were identified in 26% of cases, revealing complex, polymicrobial infections entirely missed by conventional diagnostics.
Human rhinoviruses were the most frequently detected viruses but were absent from PCR-based diagnoses, despite primer sequences matching recovered genomes. Additional respiratory pathogens not routinely screened in New Zealand, including common cold coronaviruses (OC43, 229E, NL63, HKU1), human parechovirus A1, and parainfluenza virus type 4, were also identified. Complete genomes of two viral species were recovered, demonstrating the value of metatranscriptomics for genomic analyses.
Bacterial pathogens, including Streptococcus pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus and Moraxella catarrhalis, were detected alongside active expression of virulence genes. Fungal species and antimicrobial resistance determinants, including up to 19 AMR genes in a single sample, further highlighted hidden clinical risks.
This work underscores the utility of metatranscriptomics to reveal undiagnosed microbial diversity and functional activity in SARI. Integrating this genomic approach into public health frameworks could enhance infectious disease diagnostics, surveillance and equitable response strategies in Aotearoa New Zealand.