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ToolsHalford, Carl, Le Viet, Thanh, Edge, Katie, Russell, Paul, Moore, Nathan, Trim, Fiona, Moragues-Solanas, Lluis, Lukaszewski, Roman, Weller, Simon A. and Gilmour, Matthew (2024) Development of a clinical metagenomics workflow for the diagnosis of wound infections. BMC Medical Genomics, 17. ISSN 1755-8794
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Abstract
Background: Wound infections are a common complication of injuries negatively impacting the patient’s recovery, causing tissue damage, delaying wound healing, and possibly leading to the spread of the infection beyond the wound site. The current gold-standard diagnostic methods based on microbiological testing are not optimal for use in austere medical treatment facilities due to the need for large equipment and the turnaround time. Clinical metagenomics (CMg) has the potential to provide an alternative to current diagnostic tests enabling rapid, untargeted identification of the causative pathogen and the provision of additional clinically relevant information using equipment with a reduced logistical and operative burden. Methods: This study presents the development and demonstration of a CMg workflow for wound swab samples. This workflow was applied to samples prospectively collected from patients with a suspected wound infection and the results were compared to routine microbiology and real-time quantitative polymerase chain reaction (qPCR). Results: Wound swab samples were prepared for nanopore-based DNA sequencing in approximately 4 h and achieved sensitivity and specificity values of 83.82% and 66.64% respectively, when compared to routine microbiology testing and species-specific qPCR. CMg also enabled the provision of additional information including the identification of fungal species, anaerobic bacteria, antimicrobial resistance (AMR) genes and microbial species diversity. Conclusions: This study demonstrates that CMg has the potential to provide an alternative diagnostic method for wound infections suitable for use in austere medical treatment facilities. Future optimisation should focus on increased method automation and an improved understanding of the interpretation of CMg outputs, including robust reporting thresholds to confirm the presence of pathogen species and AMR gene identifications.
| Item Type: | Article |
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| Additional Information: | Funding Information: CH, KE, RL and SW were funded by the United Kingdom Ministry of Defence. The funder approved submission of the manuscript for publication, but had no role in study design, data collection and analysis, or preparation of the manuscript. LMS was funded by the MRC Doctoral Antimicrobial Research Training (DART) Industrial CASE Programme Project grant number MR/R015937/1. TLV was supported by the Quadram Institute Bioscience BBSRC funded Core Capability Grant (project number BB/CCG1860/1). The authors gratefully acknowledge the support of the Biotechnology and Biological Sciences Research Council (BBSRC) Institute Strategic Programme Microbes and Food Safety BB/X011011/1 and its constituent project BBS/E/F/000PR13636 (Theme 3, Flexible capabilities to reduce food safety threats and respond to national needs). |
| Uncontrolled Keywords: | clinical metagenomics,molecular diagnostics,nanopore sequencing,wound infections,genetics,genetics(clinical) ,/dk/atira/pure/subjectarea/asjc/1300/1311 |
| Faculty \ School: | Faculty of Medicine and Health Sciences > Norwich Medical School |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 16 Jan 2025 01:10 |
| Last Modified: | 16 Jan 2025 01:10 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/98224 |
| DOI: | 10.1186/s12920-024-02044-w |
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