Integrating long-read metagenomics sequencing in precision medicine and antibiotic stewardship for acute respiratory tract infections.

Respiratory tract infections (RTIs) are one of the most common causes of mortality and morbidity among infectious diseases worldwide. However, the aetiology of RTIs is often undiagnosed due to the complicated presence of a myriad of bacterial, viral and fungal pathogens and opportunistic microorganisms in the complex respiratory microbiome. Moreover, RTI diagnosis is challenged by the current limitations of conventional culture-based tests and hypothesis-based narrow-spectrum molecular tests. With the causative pathogens often unknown at the time of treatment, not surprisingly, RTIs account for a high antibiotic consumption rate where most of the antibiotic prescriptions are empirical, especially for critical patients in intensive care units (ICUs). Accordingly, patients are exposed to the risks of antibiotic overtreatment, adverse effects and complications such as Clostridium difficile infections. In addition, empiric treatments with broad-spectrum antibiotics can promote the selection and dissemination of multidrug-resistant pathogens. Thus, a rapid and accurate microbiological diagnosis could prevent inadvertent antibiotic prescription or allow a timely switch to the required targeted antibacterial therapy. In this respect, metagenomics next-generation sequencing (mNGS), and more specifically long-read sequencing, has been speculated to offer enhanced diagnostic capabilities by providing a culture-independent, hypothesis-free all-in-one assay for pathogen identification in RTI diagnostics. Despite these advantages demonstrated by a number of proof-of-concept studies, applying metagenomics into clinical diagnosis is challenging, particularly for respiratory samples (such as bronchoalveolar lavage – BAL, endotracheal aspirate – ETA, sputum) due to the abundant presence of commensal flora, extracellular DNA and human host DNA. In this project, we aim to utilise state-of-the-art nanopore long-read sequencing to develop a complete, rapid mNGS workflow integrated into a point-of-care (POC) set-up to enable a one-step RTI diagnosis directly from respiratory samples. The designed workflow includes a patentable standardised method, "disclosure method A", for processing respiratory samples developed to overcome the sample-bound difficulties of high host DNA. In this workflow, we will also develop a bioinformatics pipeline method, "disclosure method B", for sequencing result analysis that can be protected with copyright. We also aim to evaluate the feasibility and demonstrate the superiority of this workflow and developed methods over conventional culture-based and molecular methods in terms of sensitivity, specificity, turn-around-time, and cost-effectiveness.

Keywords:RESPIRATORY INFECTIONS, DNA, DIAGNOSIS, SEQUENCING

Disciplines:Development of bioinformatics software, tools and databases, Microbial diagnostics, Clinical microbiology, Infectious diseases, Microbiome, Respiratory medicine, Health economy