Evaluating the potential for respiratory metagenomics to improve treatment of secondary infection and detection of nosocomial transmission on expanded COVID-19 intensive care units

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Abstract

Background

Clinical metagenomics (CMg) has the potential to be translated from a research tool into routine service to improve antimicrobial treatment and infection control decisions. The SARS-CoV-2 pandemic provides added impetus to realise these benefits, given the increased risk of secondary infection and nosocomial transmission of multi-drug-resistant (MDR) pathogens linked with the expansion of critical care capacity.

Methods

CMg using nanopore sequencing was evaluated in a proof-of-concept study on 43 respiratory samples from 34 intubated patients across seven intensive care units (ICUs) over a 9-week period during the first COVID-19 pandemic wave.

Results

An 8-h CMg workflow was 92% sensitive (95% CI, 75–99%) and 82% specific (95% CI, 57–96%) for bacterial identification based on culture-positive and culture-negative samples, respectively. CMg sequencing reported the presence or absence of β-lactam-resistant genes carried by Enterobacterales that would modify the initial guideline-recommended antibiotics in every case. CMg was also 100% concordant with quantitative PCR for detecting Aspergillus fumigatus from 4 positive and 39 negative samples. Molecular typing using 24-h sequencing data identified an MDR- K. pneumoniae ST307 outbreak involving 4 patients and an MDR- C. striatum outbreak involving 14 patients across three ICUs.

Conclusion

CMg testing provides accurate pathogen detection and antibiotic resistance prediction in a same-day laboratory workflow, with assembled genomes available the next day for genomic surveillance. The provision of this technology in a service setting could fundamentally change the multi-disciplinary team approach to managing ICU infections. The potential to improve the initial targeted treatment and rapidly detect unsuspected outbreaks of MDR-pathogens justifies further expedited clinical assessment of CMg.

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  1. SciScore for 10.1101/2020.11.26.20229989: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIACUC: The full process for sample collection, nanopore sequencing, data linkage and anonymization was approved by a research ethical committee (North West Preston REC: reference 18/NW/0584).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line AuthenticationAuthentication: Galactomannan (GM) antigen detection was performed by Mycology Reference Laboratory, Bristol using the Platelia™ Aspergillus Antigen kit (BIO-RAD – 62794).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    and C. striatum SNP analysis: Representative complete reference genomes for each species were downloaded from RefSeq to generate consensus sequences (63) for K. pneumoniae reads from 8 patients (8 samples), C. striatum reads in 6 samples (4 patients) and K. aerogenes reads from 4 samples (3 patients
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)

    Results from OddPub: Thank you for sharing your data.


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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